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BEGIN:VEVENT
UID:pretalx-foss4g-2023-WGL7YK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230627T110000
DTEND;TZID=Europe/Tirane:20230627T130000
DESCRIPTION:QGIS Chairman Marco Bernasocchi and core developer Matthias Kuh
n will be available for an hour to answer any QGIS-related questions. With
the two of them\, interested parties have access to over 20 years of comb
ined expert knowledge in the development\, use and organisation of QGIS an
d QGIS-based products. Questions about specific use cases\, upcoming devel
opments or the functioning of the QGIS project with its international cont
ributors will be tackled.
DTSTAMP:20240328T234514Z
LOCATION:KREN 2
SUMMARY:QGIS - Ask me anything! - Marco Bernasocchi\, Matthias Kuhn
URL:http://talks.osgeo.org/foss4g-2023/talk/WGL7YK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QZLTXP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230627T150000
DTEND;TZID=Europe/Tirane:20230627T170000
DESCRIPTION:Open source mapping: Connect and work with the Tech & Innovatio
n team at Humanitarian OpenStreetMapTeam (HOT)\n\nCome and meet the Tech &
Innovation team at the Humanitarian OpenStreetMap Team (HOT)\, hear about
the status of the existing and experimental open mapping tools\, and expl
ore how you can get involved!\n\nIn this side event\, you will hear about
the latest open source technology developments ranging from remote mapping
using HOT Tasking Manager\, field mapping using the Field Mapping Tasking
Manager (FMTM) to uploading imagery using Open Aerial Map\, exporting OSM
data using the HOT Export Tool and AI-assisted mapping with one of the mo
st recent projects we are working on - fAIr.\n\nWe want to connect with pe
ople who are working on anything from imagery to data visualization and pr
ovide a space to get hands-on and deep-dive into the various stages of the
open mapping workflow. Participants may choose any workflow they would li
ke to focus on\, and in groups\, deep dive into the topic of interest. We
are looking for YOUR contributions. Whatever your skills/interest might be
\, there will be something for YOU to input and collaborate on with our te
am!\n\nRegistration: Anyone is welcome to drop in the session! \nThis even
t will be held on June 27 from 15:00. Please register here - https://docs.
google.com/forms/d/e/1FAIpQLSdAYmcWCdZ2X7Oorx1pj-l698w4jBv6gHhV3O-cRtvqT9G
1Tw/viewform - and tell us what you are most interested in working on duri
ng the session. We will reach out to you before the side event. \nLook for
ward to meeting you in person!\n\nWhatever your technical background is\,
we will find an area that matches your interest! Take a look at the HOTOSM
Github repos: https://github.com/hotosm
DTSTAMP:20240328T234514Z
LOCATION:UBT B / N 014 - First Floor
SUMMARY:Open Source Geospatial Tools for Humanitarian Response - HOTOSM - Y
ogesh Girikumar\, Petya Kangalova\, Synne Marion Olsen\, Kshitij Raj Sharm
a
URL:http://talks.osgeo.org/foss4g-2023/talk/QZLTXP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-E7N8UZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T090000
DTEND;TZID=Europe/Tirane:20230628T093000
DESCRIPTION:Opening session with institutional greetings.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Opening session -
URL:http://talks.osgeo.org/foss4g-2023/talk/E7N8UZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TVR7QR@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T093000
DTEND;TZID=Europe/Tirane:20230628T100000
DESCRIPTION:In this keynote\, we will explore the significance of seeding i
n the context of open-source software. Using QField as an example\, we wil
l explore the steps needed to turn a student's project into the leading fi
eldwork app that helps hundreds of thousands of people with their work and
can help address many of the Sustainable Development Goals.\n\nWe will di
scuss the challenges faced during the initial stages of development and wh
at steps played a crucial role in overcoming them. We will also highlight
the importance of community and industry involvement and how these helped
QField reach global success and over 800K downloads.\n\nThrough this keyno
te\, attendees will gain insights into the role of seeding and commitment
in developing and growing open-source software\, highlighting its impact o
n innovation\, collaboration\, and sustainability.\n\nJoin us for an insig
htful discussion on planting seeds and the potential to drive positive cha
nge through open-source software.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:The Importance of Seeding - from 3 ECTS to Shaping a better world -
Marco Bernasocchi
URL:http://talks.osgeo.org/foss4g-2023/talk/TVR7QR/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UBQW93@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:Editors of OpenStreetMap can use my software to search for a pl
ace or region\, generating a list of candidate matches from Wikidata\, whi
ch can then be checked and saved to OpenStreetMap.\n\nLinking the two proj
ects isn't without controversy. They use different licenses which raises q
uestions about what information from one project can be copied to the othe
r.\n\nIn the presentation I will give details of a new version of the edit
ing tool.\n\nI will talk about the benefits of linking\, the process of fi
nding matches\, the community response - including the controversy - and h
ow people can get involved.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Tools for linking Wikidata and OpenStreetMap - Edward Betts
URL:http://talks.osgeo.org/foss4g-2023/talk/UBQW93/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-EVESEF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:In many surveying projects in construction\, civil engineering\
, mining\, surveying\, etc. it is common to work on coordinates referenced
to a local coordinate reference system (CRS) that is established ad hoc f
or the project site. These CRSs are necessary for applications with requir
ements that cannot be fulfilled by more common and affordable GNSS surveyi
ng techniques\, for example millimetre accuracy\, controlled distortion\,
etc. In these systems\, assigning coordinates to an on-site location with
the highest accuracy or solely relying on the control points that define t
he system is a laborious process that requires specialised and expensive t
ools and skills (for example\, knowing how to perform a point triangulatio
n using a total station\, a device commonly used in land surveying).\n\nOn
the other hand\, in the execution of a project not all tasks involving ge
olocation have such strict requirements. In many cases\, geolocation can b
e performed by less skilled staff by means of a GNSS receiver with real ti
me kinematics (RTK) or post processing kinematics (PPK) reducing costs and
work time. Geolocation can be done even without real time or post process
ing kinematics if the provided accuracy is enough\, requiring much cheaper
equipment. However\, coordinates still need to be referenced to the site
local system used in the project. In georeferencing terms\, the local syst
em is completely arbitrary and disconnected from any well known CRS. A sit
e calibration (or site localization) is the process of finding a bijection
between coordinates in a well known CRS and a site local system with a mi
nimal error in the area of interest. The problem is normally formulated as
a least squares optimization of the transformation between two sets of po
ints. This transformation allows the geolocation of new positions with cm
accuracy at a fraction of the cost of other high-accuracy surveying method
s.\n\nMany surveying devices provide a site calibration feature\, but the
algorithms are proprietary and the computed solution can only be exported
to and used by software that is compatible with the closed proprietary for
mats involved. This effectively ties the user to the vendor ecosystem or r
equires to perform a new and potentially different calibration for every i
ncompatible software tool used in the project. In this paper we present an
complete and interoperable solution that can be implemented purely in ter
ms of open source software and standards. While the mathematical formulati
on is a well known and solved problem\, to the best of our knowledge\, the
novelty of our approach resides in its complete openness.\n\nOur main con
tribution is the precise description of the workflow involved in obtaining
the mathematical solution of the site calibration problem and its represe
ntation as a self-contained coordinate reference system. The mathematical
problem can be solved using any linear algebra tool box\, but we show how
it can be implemented using functionality present in the open source libra
ry Eigen. As for the representation\, our method relies on the OGC 18-010r
7 open standard representation format [1]\, commonly known as WKT version
2. In this context\, self-contained means that the final description of a
site calibration embeds a well known CRS definition and the transformation
method and parameters to transform coordinates from this system to the si
te local system. We have tested these coordinate transformations using sev
eral possible representations in the open source programming library PROJ
version 9.2.0 [2]. The combination of WKT2 and PROJ allow for off-the-shel
f interoperability for any application using them in an open and standard
manner. The usage of WKT2 as a representation format is particularly conve
nient because it is a text-based representation that is very easy to store
\, transmit and process and on top of that\, it is human readable. Part of
the work carried out in this research has been contributed to PROJ 9.2.0
source code\, as previous versions lacked required functionality or suffer
ed from implementation issues.\n\nA site calibration can be solved in diff
erent ways ([3]\, [4]). Another important contribution of this paper is th
e comparison and accuracy analysis of two mathematical methods that result
in two different WKT2 representations. Following the terminology presente
d in the third version of ISO 19111 standard [5]\, the first and simpler m
ethod produces a derived projected system by solving a 3D problem and rely
ing on a PROJ-specific 3D transformation. The second one splits the proble
m into its horizontal and vertical components. The output is a compound co
ordinate reference system made of a derived projected horizontal system an
d vertical system with a vertical and slope derivation. This other method
relies only on well known transformations registered in the EPSG Geodetic
Parameter Dataset. We discuss the merits and disadvantages of each approac
h in terms of self-explainability of the solution and sensitivity to diffe
rent types of measuring errors\, in particular in the vertical axis\, wher
e GNSS receivers are known to have less accuracy.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Site Calibration with PROJ and WKT2 - Javier Jimenez Shaw
URL:http://talks.osgeo.org/foss4g-2023/talk/EVESEF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-9ALPLF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:SMASH \, the digital field mapping application for android and
IOS that superseded the well known app geopaparazzi has been around for so
me years now. The last two years were a positive development storm after a
quite calm year and brought many fixes as well as enhancements. Examples
are better postgis and geopackage support\, but also some hidden gems like
geocaching. \nThe big news is on the serverside though. A new survey serv
er has been developed in tight cooperation with a local government agency
to best create effective surveying workflows and tools for survey teams. T
o attract a wider developer community to contribute to the project\, the d
jango framework was chosen for the server backend.\nThis presentation will
give an overview of everything happened lately in the SMASH field mapping
world.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:SMASH and the new survey server - state of the art - Andrea Antonel
lo\, Silvia Franceschi
URL:http://talks.osgeo.org/foss4g-2023/talk/9ALPLF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-3397AJ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:Welcome to GeoServer\, a popular web service for publishing you
r geospatial data using industry standards for vector\, raster and mapping
.\n\nIf the previous sentence made no sense to you\, or if you are new to
foss4g\, or even just new to GeoServer\, attend this talk to get pointed i
n the right direction!\n\nThis presentation provides a gentle introduction
to FOSS4G and we will do our best to say the quiet part out loud:\n\n* De
mo: We have learned from experience\, and will introduce GeoServer using a
demo.\n* Usage: Concepts using both a demo\, and diagrams to connect to
your data and publish as a spatial service.\n* Checklist: Preflight check-
lists capturing common oversights when deploying GeoServer for the first t
ime.\n* Value: What role GeoServer plays in your organization and what val
ue the application provides.\n* Community: How the project is managed\, a
nd a discussion of the upcoming activities.\nAttend this presentation to g
et a running start on using GeoServer in your organization!\n\nAttend this
presentation to get a running start on using GeoServer in your organizati
on!
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:GeoServer Orientation and Demo - Ian Turton\, Jody Garnett
URL:http://talks.osgeo.org/foss4g-2023/talk/3397AJ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-VPBJY7@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:QGIS turned 20 years old last year. The first lines of code wer
e written in mid-February 2002 and when the programme was first compiled a
nd run\, it could do precisely one thing:\nConnect to a PostGIS database a
nd draw a vector layer.\n\nNowadays\, QGIS is the go-to GIS solution for m
illions of users\, and to make sure that QGIS's future is as bright as its
past\, we did a lot of work on communication\, strategy and outreach.\nIn
this talk\, I’ll overview all the work done\, the current status and th
e future of QGIS and its community.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:QGIS.org - The vision and mission for the next 20 years of QGIS awe
someness - Marco Bernasocchi
URL:http://talks.osgeo.org/foss4g-2023/talk/VPBJY7/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-HGC7AL@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:Over the recent years\, Cloud Optimized Raster format have gain
popularity not only because they ease access but also because the enable
fast visualisation of the data. During this talk I'll go over the principl
es of dynamic tiling and talk about the different cloud optimized raster f
ormat. I'll also present the latest news about TiTiler.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Dynamic Tiling: From Cloud Optimized Raster to Map tiles - Vincent
Sarago
URL:http://talks.osgeo.org/foss4g-2023/talk/HGC7AL/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-SAJLUY@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:Oskari is used world wide to provide web based map applications
that are built on top of existing spatial data infrastructures. Oskari of
fers building blocks for creating and customizing your own geoportals and
allows embedding maps to other sites that can be controlled with a simple
API. In addition to showing data from spatial services\, Oskari offers hoo
ks for things like using your own search backend and fetching/presenting s
tatistical data.\n\nThis presentation will go through the improvements to
existing functionalities and new features introduced in Oskari during the
last year including:\n\n- Theme support\n- UI rewrite progress\n- Cloud co
mpatibility improvements\n\nYou can try some of the functionalities Oskari
offers out-of-the-box on our sample application: https://demo.oskari.org.
\n\nLink: https://oskari.org
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:State of Oskari - Sami Mäkinen
URL:http://talks.osgeo.org/foss4g-2023/talk/SAJLUY/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FAHXCM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:The SpatioTemporal Asset Catalog (STAC) specifications are a fl
exible language for describing geospatial information across domains and f
or a variety of use cases. This talk will present the current state of the
specifications\, which includes the core STAC specification and the API s
pecification built on top of OGC APIs. While the core specification has be
en stable for roughly two years and doesn't need a lot of updates\, the AP
I specification got numerous updates and is finally close to a stable rele
ase. This presentation digs into additions to STAC extensions and the late
st community developments. We survey the updates to the open-source STAC e
cosystem\, which includes software written in Python\, Node.js\, and more.
Finally\, let's also look into the near future.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:State of STAC - Matthew Hanson\, Matthias Mohr
URL:http://talks.osgeo.org/foss4g-2023/talk/FAHXCM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-LQMAPV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:From detecting vegetation hazard to measuring catenary geometry
\, it all begins with **three trains equipped with LiDaR** mapping systems
\, roaming the french railway network.\n\nLet us see how **geospatial open
source softwares** enabled us to build a cost-effective and comprehensive
solution\, starting from basic raw data processing up to setting up a geog
raphic information system\, full of relevant data that **brings up railway
maintenance to another level**.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Digitizing the french railway network - an open source endeavour -
Guilhem Villemin
URL:http://talks.osgeo.org/foss4g-2023/talk/LQMAPV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KRASRT@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:Spatial data interoperability has been on the spot among the Op
en Geospatial Consortium members for almost 30 years\, but the current mom
ent is notable for several reasons. An enormous amount of data is growing
exponentially due to the novel sensors that bring observations from previo
usly inaccessible areas in such resolution. We can observe and explore the
global ocean with modern computational resources and AI models. Federated
Data Spaces initiatives emerge with the paradigm of multi-source data int
egration harmoniously supporting heterogeneous models.\nSpeakers will pres
ent recent advancements in the data mesh methods based on two environments
endorsing open source implementations used for the integrations.\nFirst i
s the Federated Marine SDI (FMSDI) Pilot\, which focuses on advancing the
implementation of open data standards\, architecture\, and prototypes for
use with the creation\, management\, integration\, dissemination\, and onw
ard use of marine and terrestrial data services for the Arctic. Use cases
developed in the recent phase of the FMSDI pilot further demonstrated the
capabilities and use of OGC\, IHO and other community standards in respons
e to a grounding event and the evacuation of a cruise ship or research ves
sel in the Arctic. \nThe approach collated with Iliad - Digital Twin of th
e Ocean and its interoperability patterns model. Based on the specific req
uirements for data transfer\, access and computation\, it looks to general
ise core architectural patterns with standard implementations. These patte
rns address the core issues of data publishing\, aggregation and extensive
analyses close to the data. Together\, they enable a viable overall digit
al twin ecosystem. Data mesh of observations with data lakes and assembly
are essential building blocks that allow the flow and synchronisation of d
ata between different data owners. A open\, common information model\, def
ined on the domain-specific and well-known generic ontologies\, Analysis R
eady Data\, and Essential Variables concepts\, allows for the traceability
of provenance and various expressions. It is a critical prerequisite to a
chieving data interoperability and explainable AI. Application packaging o
f processing chains allows for seamless compute-to-data\, remote computati
on\, or even mobile control when data is too big to flow. The computation
is executed in a controlled environment\, and the results harmonised for f
urther use or available as decision-ready information. \n Presenters will
describe these patterns and illustrate them with OGC and partners' open im
plementations (like OGC-NA\, EDR\, geoXACML\, HubOcean sync API) from the
projects.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Open resources and open standards for multi source marine twinning
- Piotr Zaborowski
URL:http://talks.osgeo.org/foss4g-2023/talk/KRASRT/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PE8USS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T103000
DTEND;TZID=Europe/Tirane:20230628T110000
DESCRIPTION:This talk is going to reveal the secret of building and running
development or\nuser environments as you always wanted. Each of your proj
ects can run in\nisolated\, fully self contained environment\, using the l
atest\, or really old\, or\nheavily customized geospatial packages regardl
ess of Linux distro or Mac version you\nuse. You can have as many environm
ents as you want\, and the environment will change as you\nchange between
your projects\, branches or commits.\n\nNo\, we are not going to run conta
iners\, Flatpaks of Snaps for that. We are going\nto enjoy the most advanc
ed package manager [Nix](https://nixos.org/)\, the\nlargest collection of
software in the world called [Nix packages\n(nixpkgs)](https://github.com/
NixOS/nixpkgs)\, unique tooling they provide and\n[Geonix](https://github.
com/imincik/geonix) [Devenv](https://devenv.sh/) projects built on top of
that.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Using Nix to build development environments as you always wanted -
Ivan Minčík - @imincik
URL:http://talks.osgeo.org/foss4g-2023/talk/PE8USS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-9TAFJZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:STAC is a well-known and acknowledged spatiotemporal metadata s
tandard within the community. There are many applications with open-source
data\; however\, there are few adoptions by premium satellite imagery pro
viders. At UP42\, we adopted STAC as the core metadata system within our a
pplications and provided STAC API for users to manage their data easily. T
he ongoing adoption challenges with multiple data providers taught many ta
keaways that we would like to share with the community.\n\n- UP42: a short
introduction \n- Data management challenges at UP42\n- Solution with STAC
& cloud-native asset format\n- STAC implementation: lessons learned \n- C
urrent state and way forward
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Standardized Data Management with STAC - Batuhan Kavlak\, Sam Eglin
gton
URL:http://talks.osgeo.org/foss4g-2023/talk/9TAFJZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RR7AU9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:With increasing digitalization and automation\, there is a need
to develop automatic methods to maintain and update public information st
ored in spatial databases. The building register stores public\, building-
related information and is the fundamental record for storing information
and other relevant data necessary for taxation\, public planning\, and eme
rgency services about buildings. Up-to-date building footprint maps are es
sential for many geospatial applications\, including disaster management\,
population estimation\, monitoring of urban areas\, updating the cadaster
\, 3D city modelling\, and detecting illegal construction cases (Bakirman\
, et al.\, 2022.). There are many approaches for building extraction from
various data sources\, including satellite\, aerial\, or drone images and
3D point clouds. However\, there is still a demand for developing methodol
ogies that can extract segment\, regularize and vectorize building footpri
nts using deep learning in and end-to-end workflow.\n\nToday\, automatic a
nd semi-automatic methods have achieved state-of-the-art results in buildi
ng footprint extraction by combining computer vision and deep learning tec
hniques. Semantic segmentation is a method for classifying each pixel in a
n image and extract building footprints from remote sensing data. In the c
ase of building segmentation\, the goal is to classify each pixel on an im
age belonging to its corresponding class. Recent advances in deep learning
for building segmentation have drastically improved the accuracy of the s
egmented building masks using Convolutional Neural Networks (CNNs).\n\nRec
ently proposed semantic segmentation architectures include the application
of advanced vision transformers for semantic segmentation. GeoSeg is one
of the open-source semantic segmentation toolboxes for various image segme
ntation tasks. The repository has 7 different models\, that can be used fo
r either multi-class or binary semantic segmentation tasks\, including fou
r vision transformers: U-NetFormer\, FT-U-NetFormer\, DCSwin\, BANet and t
hree regular CNN models: MANet\, ABCNet\, A2FPN.\n\nDeep learning methods
for building segmentation involve training the neural network on a labeled
image dataset\, referred to as supervised learning. Semantic segmentation
aims to distinguish between semantic classes in an image but does not ind
ividually label each instance. On the other hand\, instance segmentation a
ims at distinguishing between semantic classes and the individual instance
s of each class. Many popular instance segmentation architectures exist\,
such as Mask R-CNN and its predecessors\, R-CNN\, Fast R-CNN\, and Faster
R-CNN. While the implementation of instance segmentation can be more chall
enging\, the approach can be more effective in densely populated urban are
as\, where buildings may be close or overlapping.\n\nA common problem with
these methods is the irregular shape of the predicted segmentation mask.
Additionally\, the data contains various types of noise\, such as reflecti
ons\, shadows\, and varying perspectives\, making the irregularities more
prominent. Further post-processing steps are necessary to use the results
in many cartographic and other engineering applications (Zorzi et al.\, 20
21).\n\nThe solution for the irregularity of the building footprints is to
use regularization. Regularization is a technique in machine learning tha
t applies constraints to the model and the loss function during the traini
ng process to achieve a desired behaviour (Tang et al.\, 2018). Applying r
egularization constrains the segmentation map to be smoother\, with clearl
y defined and straight edges for buildings. As a result\, the building foo
tprint becomes less irregular when occluded and visually more appealing. M
ost studies apply regularization after image segmentation. \n\nWe propose
an end-to-end workflow for building segmentation\, regularization and vect
orization using four different convolutional neural network architectures
for binary semantic segmentation task: (1) U-Net\, (2) U-Net-Former\, (3)
FT-UNet-Former and (4) DCSwin. We further improve the building footprints
by applying the projectRegularization method proposed by (Li et al.\, 2021
). The technique uses a boundary regularization network for building footp
rint extraction in satellite images combining semantic segmentation and bo
undary regularization with an end-to-end generative adversarial network (G
AN). Our approach will perform semantic segmentation with our trained mode
ls and then perform boundary regularization on the segmentation masks. We
aim to prove the scalability of projectRegularization on a different segme
ntation task\, including aerial images as the data source. The last step i
n our approach is to develop a methodology for efficient vectorization of
the segmented building mask using open-source software solutions. We aim t
o make the results practically applicable in any GIS environment. The data
set used for testing our developed method will be the MapAI dataset used f
or the MapAI: Precision in Building Segmentation competition (Jyhne et al.
\, 2022) arranged with the Norwegian Artificial Intelligence Research Cons
ortium in collaboration with the Centre for Artificial Intelligence Resear
ch at the University of Agder (CAIR)\, the Norwegian Mapping Authority\, A
I:Hub\, Norkart\, and The Danish Agency for Data Supply and Infrastructure
.\n\nWe aim to produce better representations of building footprints with
more regular building boundaries. After successful application\, our metho
d generates regularized building footprints\, that are useful in many cart
ographic and engineering applications. Furthermore our regularization and
vectorization workflow is further developed into a working QGIS-plugin tha
t can be used to extent the functionality of QGIS. Our end-to-end workflow
aims to advance the current research in convolutional neural networks and
their application for automatic building footprint extraction and\, as a
result\, further enhance the state of open-source GIS software.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:An end-to-end deep learning framework for building boundary regular
ization and vectorization of building footprints - Simon Šanca
URL:http://talks.osgeo.org/foss4g-2023/talk/RR7AU9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QBHQNW@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:geoserverx is a modern Python package that provides an efficien
t and scalable way to interact with Geoserver REST APIs. It leverages the
asynchronous capabilities of Python to offer a high-performance and reliab
le solution for managing Geoserver data and services.\nWith geoserverx\, u
sers can easily access and modify data in Geoserver\, such as uploading an
d deleting shapefiles\, publishing layers\, creating workspaces\, styles\,
etc. . The package supports asynchronous requests along with synchronous
method to the Geoserver REST API\, which enables users to perform multiple
tasks simultaneously\, improving performance and reducing wait times.\nAp
art from being implemented in Python Projects\, geoserverx also provides C
LI support for all of it's operations. Which makes it useful for people wh
o want to avoid Python all-together. \nIn this talk we discover for the ve
ry first time about how geoserverx work and underlying code ideology. Alon
g with that we'll also spread some light on upcoming modules to be integra
ted in geoserverx
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:geoserverx - a new CLI and library to interact with GeoServer - Fra
ncesco Bartoli\, krishna lodha
URL:http://talks.osgeo.org/foss4g-2023/talk/QBHQNW/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PWVX3G@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:This presentation will delve into the intricacies of packaging
geospatial software for Debian Linux and its derivatives\, including Ubunt
u\, OSGeoLive\, and others.\n\nIt will begin by contrasting the difference
s between packaging for an operating system and application-level package
managers. The presentation will then provide an introduction to the Debian
GIS Team and their established practices for packaging\, including resour
ces for finding information. The focus will then shift to the crucial step
s involved in preparing the software for distribution\, such as creating m
etadata and dependencies\, building the package\, testing its functionalit
y\, and ultimately making it available to end-users for easy installation
and use.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Packaging Geospatial Software for Debian and Ubuntu Linux - Felix D
elattre
URL:http://talks.osgeo.org/foss4g-2023/talk/PWVX3G/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-8TD9UT@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:More than 250 years ago\, Giovanni Battista Nolli\, an Italian
architect\, engineer and cartographer\, was concerned with how and where s
pace is or is not publicly accessible. In his map 'La nuova topografia di
Roma Comasco'\, he mapped publicly accessible interior and exterior spaces
of Rome with an impressively high level of detail as a figure-ground map.
Since Nolli’s time\, both the character and diversity of public spaces
as well as cartographic technology have changed. In my Master thesis\, I a
im to adapt Nolli's underlying idea for today’s circumstances on the bas
is of open data\, and seek to develop methods for processing volunteered g
eographical information from OpenStreetMap (OSM) to identify\, categorize\
, and map public spaces based on thematic and geometric information.\n\nFi
rst\, it has to be clarified what is considered public space and what is n
ot. Given the data available via OSM as well as in terms of feasibility\,
I focus on the aspect of public accessibility and exclude indoor spaces. D
ata processing is implemented as a Python script based on existing OSM and
geospatial Python packages. The code is available as Open Source on [GitH
ub](https://github.com/ester-t-s/osm-public-space-mapper). The application
of the framework and methods is tested in two case studies in Vienna\, Au
stria. The result can be visualized as 'contemporary Nolli map'.\n\nIn my
talk\, I will give insights into the methodology and framework for data an
alysis I developed as part of my Master thesis
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:A Contemporary Nolli Map: Using OpenStreetMap Data to Represent Urb
an Public Spaces - Ester Scheck
URL:http://talks.osgeo.org/foss4g-2023/talk/8TD9UT/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KLVT3W@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:This talk gives an overview of the current state of the GRASS G
IS project for both users and developers. Latest version of GRASS includes
even more tools parallelized using OpenMP to speed up massive data proces
sing. The graphical user interface is changing as the single-window layout
matured and is becoming the number one choice and a default setting. This
adds to a quicker startup without a need for a welcome screen and streaml
ined data management. The code quality of C and C++ code improved signific
antly in the last year\, the code compiles with strict compiler settings a
nd we are heading towards pedantic compliance. Last but not least\, this s
ummer GRASS GIS celebrates its 40th birthday!
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:State of GRASS GIS - Anna Petrasova\, Vaclav Petras\, Veronica Andr
eo\, Markus Neteler\, Martin Landa
URL:http://talks.osgeo.org/foss4g-2023/talk/KLVT3W/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-THALGS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:A presentation and demonstration of data cube functionality imp
lemented based on OGC API Standards and draft Candidate Standards.\n\nIncl
uding:\n\n- OGC API - Tiles\,\n- OGC API - Maps\,\n- OGC API - Coverages\,
\n- OGC API - Discrete Global Grid Systems\,\n- OGC API - Processes - Part
1: Core\, and Part 3: Workflows and Chaining ("Nested Processes"\, "Colle
ction Input"\, "Collection Output")\,\n- OGC Common Query Language (CQL2)\
n\nwith a focus on providing efficient access to analysis-ready sentinel-2
data and additional processing close to the data\, in the context of wild
fire risk assessment.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:OGC API standards for geospatial data cubes - Jerome St-Louis
URL:http://talks.osgeo.org/foss4g-2023/talk/THALGS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-CNL7HK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:In the last decade\, 5 complementary assets have intersected\,
creating a series of new capabilities for our community. Modern geospatial
did not exist even five years ago\, and openness - the combination of ope
n standards\, open data all glued together with open source code is a key
contributing factor. \n\nThis talk will present the case for openness bein
g a competitive advantage for a modern\, innovative technology company. We
will discuss why we have been right all along\, and why we will end up be
ing even righter in the future. If you want a solid dose of confirmation b
ias\, this is the talk for you!
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Openness as a strategic advantage in modern geospatial - Will Cadel
l
URL:http://talks.osgeo.org/foss4g-2023/talk/CNL7HK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UXYVVE@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:Based on the implementation of the Global Statistical and Geosp
atial Framework (GSGF) proposed by the UN and implemented in Latin America
and the Caribbean by the Economic Commission for Latin America and the Ca
ribbean (ECLAC)\, a set of specific technological components were develope
d\, such as a geoportal\, a statistical manager and an API with the possib
ility of consuming information from different applications. At the same ti
me\, components already existing in the community were implemented such as
Kobo Toolbox\, GeoNode\, Airflow\, MapLibre\, Nominatim and Metabase for
the integration of information from the collection in the territory to the
publication of the data. The project was initially carried out with a gro
up of countries: Argentina\, Paraguay\, Honduras\, Guatemala\, Dominican R
epublic\, Costa Rica and Ecuador.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Implementation of Statistical Geoportals in Latin America and the C
aribbean - Ariel Anthieni\, Walter Shilman
URL:http://talks.osgeo.org/foss4g-2023/talk/UXYVVE/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XCWUHM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:Suomi.fi-maps offers to the public administration and governmen
t agencies a centralized service for utilizing maps and location data. In
the Suomi.fi-maps service\, a user may compile their own map views from th
e map layers available in the service\, as well as from their own objects
and materials provided by service interfaces of their own organization. \n
Oskari platform is used to implement the Suomi.fi-maps system. Suomi.fi-ma
ps is used to enable all the Finnish residents to use maps and the locatio
n data to find about the services they are interested in. \nIn addition to
other open data the open materials of the National Land Survey may also b
e used: various terrain and background maps\, property boundaries and aeri
al photographs. User may connect their own interfaces to the Suomi.fi-maps
service or add their own objects to the map to be published.\nThis presen
tation describes with examples\, how the Oskari platform and its features
are used used to implement the Suomi.fi-maps service and lessons learned.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Suomi.fi-maps - national service implementation with Oskari platfor
m - Arto Sinkkonen
URL:http://talks.osgeo.org/foss4g-2023/talk/XCWUHM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-JKBHTM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T110000
DTEND;TZID=Europe/Tirane:20230628T113000
DESCRIPTION:Protomaps is a simple\, self-hostable system for tiled vector d
atasets. In the year since last FOSS4G\, we've rolled out a new compressed
specification (V3)\, added support for tile generation tools\, and open s
ourced key integrations with content delivery networks. This talk will giv
e an overview of:\n\n* Why you might want to\, or not want to\, deploy Pro
tomaps for your application\n* PMTiles write support in the popular Tippec
anoe and Planetiler tools\n* The new open source integrations of Protomaps
with AWS Lambda and Cloudflare\n* Overview of real-world deployments for
users in web GIS\, journalism and the public sector
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Serverless Planet-scale Geospatial with Protomaps and PMTiles - Bra
ndon Liu
URL:http://talks.osgeo.org/foss4g-2023/talk/JKBHTM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TKCHPY@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:This paper introduces a scalable software for extracting Digita
l Terrain Models (DTM) from Digital Surface Models (DSM)\, called Bulldoze
r. DTMs are useful for many application domains such as remote sensing\, t
opography\, hydrography\, bathymetry\, land cover maps\, 3D urban reconstr
uction (LOD)\, military needs\, etc. Currant and incoming LiDAR and spati
al Earth Observation missions will provide a massive quantity of 3D data.
The spatial mission CO3D will deliver very high resolution DSMs at large s
cale over emerging landscapes. The IGN LiDAR HD mission is currently deliv
ering high density point clouds of French national territory. This trend m
otivated the French spatial agency (CNES) to focus on the development of t
ools to process 3D data at large scale. In this context\, we have develope
d a free open-source software\, called Bulldozer\, to extract a DTM from a
DSM at large scale without any exogenous data while being robust to noisy
and no-data values. Bulldozer is a pipeline of modular standalone functio
ns that can be chained together to compute a DTM. A pre-processing step co
ntains specific functions to clean the input DSM and prepare it for a futu
re DTM extraction such as disturbed area detection\, hole filling and oute
r/inner nodata management. Then the extraction of the DTM is based on the
original Drape Cloth principle\, which consists of an inversion of the Di
gital Surface Model\, followed by a multiscale representation of the inver
ted DSM on which an iterative drape cloth computation is applied to derive
the DTM. Finally a post-processing step is achieved to obtain the final D
TM.\n\nWe have addressed a number of limitations that this type of algorit
hm may encounter. Indeed\, when we do 3D stereoscopic satellite reconstruc
tion\, we can observe areas of residual noise in the DSM. They mainly come
from uniform areas (shadows\, water)\, or occlusions. These outliers dist
urb the drape cloth: it sticks to the edges of those disturbed areas and n
o longer fits the relief. This results in an underestimation of the DTM an
d generates pits in these noisy areas. To solve this problem\, we have imp
lemented a series of pre-processing steps to detect and remove these outli
ers. Once these areas are removed\, we use a filling function that is more
elegant than a basic interpolation method (e.g. rasterio fill nodata func
tion). In addition\, after the DTM extraction\, we detect and remove poten
tial residual sinks in the generated DTM. In order to keep track of the ar
eas that we have interpolated or filled in\, Bulldozer also provides a pix
el-wise quality mask indicating whether it was detected as disturbed (and
therefore removed and filled in) or as interpolated following a pit detect
ion.\n\nCurrent stereo and LiDAR DSMs have a centimetric spatial resolutio
n. However\, the need to have such a high spatial resolution for DTM is no
t always relevant for numerous downstream applications. The multi-scale ap
proach in Bulldozer allows to produce a coarser DTM by just stopping the p
rocess earlier in the pyramid. A final resampling of the DTM is done to fu
lfill the user-specific resolution. One main advantage of this feature is
the potentially short execution time to produce a high-quality DTM dependi
ng on the DTM coarseness.\n\nAnother main contribution of our work is the
adaptation of the original Drap Cloth algorithm to process DSMs of arbitra
ry size and from arbitrary sources. As explained in our previous paper\, w
e introduce the concept of a stability margin in order to use a tiling str
ategy while ensuring identical results to those obtained if the DSM were p
rocessed entirely in memory. This tiling strategy allows a memory-aware ex
traction of the DTM in a parallel environment. This scalable execution is
heavily based on the concept of shared memory introduced in Python 3.8 and
the multi-processing paradigm. \n\nSince our previous version we have be
en working on the accessibility of Bulldozer. Bulldozer can handle any inp
ut DSM as long as it is in a raster format. We have set up several interfa
ces to allow users of different levels to use it. A QGIS plugin was develo
ped in order to allow novice users to use Bulldozer. For more advanced use
rs\, there is a Command Line Interface (CLI) to launch the tool from a ter
minal. And finally\, for developers\, they can use the Python API to launc
h the complete pipeline or call the standalone functions from the pipeline
.\n\nThe efforts to improve the algorithmic performances allow the managem
ent of large DSMs while guaranteeing stability in the results\, memory usa
ge\, and runtime. Currently\, we achieve to extract a DTM from a 40000*700
00px input DSM in less than 10 minutes on a 16 core/64-GB RAM node. We bel
ieve that its ability to adapt to several kinds of sensors (high and low r
esolution optical satellites\, LiDAR)\, its simplicity of use\, and the qu
ality of the produced DTMs may interest the FOSS4G community. We plan to p
resent the tool during a workshop dedicated to CNES 3D tools\, but we thin
k that the method and the algorithmic optimizations could also interest th
e FOSS4G Academic Track audience through an academic paper. \n\nThe projec
t is available on github (https://github.com/CNES/bulldozer)\, and we are
currently trying to provide access to LiDAR and satellite test images in o
rder to allow the community to reproduce the results.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Bulldozer\, a free open source scalable software for DTM extraction
- Dimitri Lallement
URL:http://talks.osgeo.org/foss4g-2023/talk/TKCHPY/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-38LSAY@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:We will give a status report on the GDAL software\, focusing on
recent developments and achievements in the 3.6 and 3.7 GDAL versions rel
eased during the last year\, but also on the general health of the project
.\nThe discussed topics will be as various as the scope of GDAL is\, cover
ing the new single CMake build system\, the full open source write vector
support for the Esri FileGeodatabase format\, a Arrow-based columnar orien
ted read API for vector layers implement in the Arrow\, (Geo)Parquet\, Geo
Package and FlatGeoBuf drivers\, new vector layer API for table relationsi
hp management\, new raster drivers for the JPEG-XL\, KTX2\, BASISU\, NSIDC
bin formats\, multi-threaded read capabilities in the GeoTIFF driver\, mul
tiple performance improvements in the GeoPackage driver\, advanced API to
read raster compressed data\, a new vector driver for the General Transit
Feed Specification (GTFS)\, support for the new Seek Optimized ZIP (SOZip
) specification\, etc.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:State of GDAL (versions 3.6 and 3.7) - Even Rouault
URL:http://talks.osgeo.org/foss4g-2023/talk/38LSAY/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-X3NCBZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:Working in large open source projects\, with several people con
tributing to the code\, can be challenging\, especially trying to keep eve
ryone on the same page\, and generating code that has enough similarities
to allow shared maintenance.\n\nThe advent of platforms like GitHub also m
ade it easier for one time contributors to donate small and large bits of
code to the platform\, generating in the process a fair amout of “review
stress” in the project maintainers.\n\nThe presentation covers how pull
request checks\, formatting and static analysis tools have been used to s
treamline basic checks in the code:\n\n* Testing the code on a variety of
operating systems\, Java versions and integrations with data sources befor
e the code can be contributed to the project\n* Enforcing common formattin
g\n* Adding basic checks with CheckStyle\n* Locating obvious errors\, left
over code\, basic optimization issues using the Java compiler linting\, Er
rorProne\, PMD and SpotBugs\n* Improving readability of the code as well a
s enforcing best practices and common approaches with the same tools.\n* E
ffects on the dynamics of code reviews\n\nThe presentation will cover all
those aspects\, with examples from the author’s experience with the GeoT
ools\, GeoWebCache and GeoServer projects.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Adding Quality Assurance to open source projects: experiences from
GeoTools\, GeoWebCache an GeoServer - Andrea Aime
URL:http://talks.osgeo.org/foss4g-2023/talk/X3NCBZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZGYKXH@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:The Ontology discipline made its way into the Computer Science
domain in the\n1990s\, filling a gap in the architecture aspect of a still
infant engineering\ndomain. Its most visible impact happened around the i
ndustry consortium Object\nManagement Group (OMG)\, leading first to the U
nified Modelling Language (UML)\nand later to the Model Driven Architectur
e (MDA). MDA became the base\ninfrastructure of data architectures and exc
hange mechanisms specified by\ninstitutions such as the Open Geo-spatial C
onsortium (OGC) or the European\nCommission (through the INPIRE directive)
.\n\nHowever\, a parallel path has been treaded by the World Wide Web Cons
ortium\n(W3C). First with the specification of the Resource Description Fr
amework (RDF)\,\na new paradigm for data encoding leveraged on the WWW\, a
nd later with the Web\nOntology Language (OWL)\, a pragmatic approach to o
ntology encoding\, building on\nRDF. This infrastructure developed by the
W3C became known as the Semantic Web\,\nand also as Linked Data\, for the
innovative paradigm through which it connects\ndisparate data sources and
data domains.\n\nThe OGC would eventually approach the semantic web\, spec
ifying GeoSPARQL in\n2013\, an ontology and query language for linked geo-
spatial data. However\,\ntechnologies supporting this new standard were sl
ow in materialising.\n\nMore recently\, the specification by the OGC of a
new set of data standards based\non the OpenAPI technology set out a clear
path for the convergence of\ngeo-spatial data with the Semantic Web. New
software is emerging\, opening\nan entirely new world to geo-spatial data
provision\, a clear step forwards in\npractically\, usability and semantic
s.\n\nThis address starts by reviewing the core concepts of the Semantic W
eb and\nthen reviews state-of-the-art software for the management\, public
ation\nand exploration of linked geo-spatial data. This addressed is targe
ted at SDI\nprofessionals and data scientists wishing to upgrade the seman
tics of the data\nthey create and use.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Geo-Spatial meets Linked Data: open source solutions for semantic s
patial data exchange - Luís M. de Sousa
URL:http://talks.osgeo.org/foss4g-2023/talk/ZGYKXH/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PCA9TC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:MapStore is an open source product developed for creating\, sav
ing and sharing in a simple and intuitive way maps\, dashboards\, charts a
nd geostories directly online in your browser. MapStore is cross-browser a
nd mobile ready\, it allows users to: \n\n- Search and load geospatial con
tent served using widely used protocols (WMS\, WFS\, WMTS\, TMS\, CSW) and
formats (GML\, Shapefile\, GeoJSON\, KML/KMZ etc..)\n- Manage maps (creat
e\, modify\, share\, delete\, search)\, charts\, dashboard and stories dir
ectly online\n- Manage users\, groups and their permissions over the vario
us resources MapStore can manage\n- Edit data online via WFS-T with advanc
ed filtering capabilities\n- Deeply customize the look&feel to follow stri
ct corporate guidelines\n- Manage different application contexts through a
n advanced wizard to have customized WebGIS MapStore viewers for different
use cases (custom plugins set\, map and theme)\n\nYou can use MapStore as
a product to deploy simple geoportals by using the standard functionaliti
es it provides but you can also use MapStore as a framework to develop sop
histicated WebGIS portals by reusing and extending its core building block
s.\n\nMapStore is built on top of React and Redux and its core does not ex
plicitly depend on any mapping engine but it can support both OpenLayers\,
Leaflet and Cesium\; additional mapping engines could be also supported (
for example MapLibre GL) to avoid any tight dependency on a single engine.
\n\nThe presentation will give the audience an extensive overview of the M
apStore functionalities for the creation of mapping portals\, covering bo
th previous work as well work for the future releases. Eventually\, a ran
ge of MapStore case studies will be presented to demonstrate what our clie
nts (like City of Genova\, City of Florence\, Halliburton\, Austrocontrol
and more) and partners are achieving with it.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:MapStore\, a year in review - Stefano Bovio\, Matteo Velludini
URL:http://talks.osgeo.org/foss4g-2023/talk/PCA9TC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-JRRFQL@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:Oskari (https://www.oskari.org\, https://github.com/oskariorg)
provides a super-easy-to-use tool for creating mobile friendly maps that c
an be embedded onto websites or used as is. When embedding the maps on exi
sting websites one can utilise the RPC API to further leverage the capabil
ities of Oskari. The API allows for integrating with existing services and
external data sources so that the end result will be a seamless spatially
enabled service running on any modern web browser.\n\nWhile creating maps
with Oskari requires no expertise in programming\, utilising the RPC API
requires basic knowledge of JavaScript. This talk will present the possibi
lities of Oskari RPC API among with some examples of live services created
using it.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Oskari Embedded Maps and integrations with RPC API - Timo Aarnio
URL:http://talks.osgeo.org/foss4g-2023/talk/JRRFQL/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-3P7DAC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:The Open Science Persistent Demonstrator (OSPD) is a long-term
inter-agency initiative aiming to enable and communicate reproducible Eart
h Science across global communities of users and amplify inter-agency Eart
h Observation mission data\, tools\, and infrastructures. This talk will h
ighlight the status and roadmap of the initiative (kicked off in 2023) and
will provide an outlook on the first pilot activities of the demonstrator
\, as well as opportunities for participation for the FOSS4G community. \n
In the scope of this activity\, ESA\, NASA and OGC work together on the de
velopment of a long-term Open Science framework (e.g.\, a permanent open s
cience demonstrator) in which participating organisations provide data\, t
ools\, and infrastructure in a coordinated approach\, building on existing
investments where appropriate. \nIn the frame of this activity\, the OGC
supports the Open-Source and Open Science Community by developing a persis
tent demonstrator that makes Open Science more tangible to a bigger audien
ce\, helps in exploring new forms of communication of scientific results t
o stakeholders\, and helps develop the necessary standards to ensure the h
ighest levels of interoperability across participating organizations. At t
he same time\, it makes Earth Observation results available to other disci
plines and communities\, creates attention beyond the Earth Observation co
mmunity\, and directly impacts decision makers and political agendas.\nThe
goal here is to demonstrate interoperable\, collaborative research that a
llows reuse of existing components. These other resources are either offer
ed as part of emerging Open Science Environments or in the form of either
directly accessible “cloud-native” data/functions or by means of Web A
PIs. To reach this goal\, it is essential to empower communities of practi
ce to share FAIR (Findable\, Accessible\, Interoperable\, Reusable) descri
ptions of their resources and capabilities. To allow this system to scale\
, it is crucial to avoid infinite combinations of community and applicatio
n specific metadata\, functions\, data and products. \nOne focus is the f
acilitation of direct participation of the scientific community as the pri
mary users of this framework\, and of the open-source for geospatial commu
nity as essential contributors to the activity. To handle modelling comple
xity\, OGC\, NASA and ESA will define manageable processes and best practi
ces for communities conducting geoscience research in multiple domains usi
ng heterogeneous data and tools on a distributed infrastructure. These agr
eements will include\, but not limited to\, standards\, vocabularies\, and
ontologies for data and workflows and develop community-wide open source
science mechanisms\, modeling considerations and design patterns.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:ESA-NASA-OGC Open Science Persistent Demonstrator - Anca Anghelea\,
Piotr Zaborowski\, Manil Maskey
URL:http://talks.osgeo.org/foss4g-2023/talk/3P7DAC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UXNSMD@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:The SpatioTemporal Asset Catalog (STAC) (and Cloud Native Geosp
atial ecosystem) for/in JavaScript has evolved in the last year. This talk
will update you on the current state of the ecosystem and gives an outloo
k on what is missing. For STAC talk will cover libraries such as stac-js\,
stac-layer\, stac-browser\, stac-node-validator\, and more. We'll dive in
to what the libraries do\, how they relate to each other and give you some
hints how you get started. At the end\, a short excursion into the cloud-
native geospatial ecosystem in JavaScript for COG\, geoparquet\, geozarr a
nd other file formats will be provided as well.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:The STAC JavaScript Ecosystem + CNG Excursion - Matthias Mohr
URL:http://talks.osgeo.org/foss4g-2023/talk/UXNSMD/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-9R3QTM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:A typical GeoServer deployment involves exposing it as a front
service to publish a number of layers directly to the internet\, where a s
ingle instance\, or even a couple\, and an on-premise deployment model is
enough.\n\nWithin larger companies though\, more often than not GeoServer
is a critical component of a more significant infrastructure\, used to hos
t tens of thousands of layers to accommodate organization requirements acr
oss various departments and workflows that involve several other systems\,
and complex cloud deployments.\n\nThese scenarios are where GeoServer Clo
ud shine\, enabling devOps teams to set up clusters of GeoServer pods that
are scalable\, have improved resiliency\, security\, and resource utiliza
tion\; and increased observability and integration with telemetry systems
for monitoring\, debugging\, and tracing.\n\nIn this talk\, we'll explore
in depth how GeoServer Cloud achieves these goals\, from technology and de
sign choices to detailed overviews of technical improvements that were req
uired\, supported by success stories of current CampToCamp customers that
got GeoServer Cloud in production.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:GeoServer Cloud in depth - Gabriel Roldan
URL:http://talks.osgeo.org/foss4g-2023/talk/9R3QTM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-SC9WU8@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T113000
DTEND;TZID=Europe/Tirane:20230628T120000
DESCRIPTION:DigiAgriApp is a client-server application to manage different
kinds of data related to farming fields. It is able to store information a
bout crops (specie\, farming forms/system...)\, any kind of sensor data (i
ncluded sensors and device hardware\, weather\, soils...)\, irrigation inf
ormation (system type\, openings...)\, field operations (pruning\, mowing\
, treatments...)\, remote sensing data (taken from different devices as mo
biles\, drone\, satellites) and production quantities.\n\nThe DigiAgriApp
server is composed of a PostgreSQL/PostGIS database and a REST API service
to interface with it. The server is developed using Django and the Django
REST framework extension with other minor extensions are used to create t
he REST API. This service plays the key interface between the database and
the client. We choose a nested way to create the API\, of which the main
element is the farm\; this way the user can see only the farms related to
him and from there he can look to other nested elements\, first of all the
farm’s fields and later other elements like sensor and remote data or o
ther sub-fields like rows and plants. The REST API is using JavaScript Obj
ect Notation as input and output format to simplify and standardize the co
mmunication with it.\n\nTo obtain data from the sensors the server is also
composed of a growing number of services to work with data providers\, of
which currently only a few are implemented. The Message Queue Telemetry T
ransport provider is a demon listening continuously to a broker (backend s
ystem to coordinate different clients) and several topics to obtain data a
s soon as they are provided\; the second provided that is already implemen
ted is related to remote sensing data and uses the SpatioTemporal Asset Ca
talogs specification to obtain the data. STAC is a common language to desc
ribe geospatial information\, so it can more easily be worked with\, index
ed and discovered.\n\nThe client side instead is developed using Flutter\,
an open-source UI software development kit based on dart\, a programming
language designed for client development. Flutter is able to create cross-
platform applications and it was chosen precisely because of its ability t
o realize cross platform applications.\n\nAll the code is released as Free
and Open Source software with a GNU General Public License Version 3 lice
nse\; it is available in the DigiAgriApp repository on GitLab and the clie
nt application will be published also in the main stores for mobile apps.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:DigiAgriApp: the app to manage your agricultural field - Andrea Ant
onello\, Luca Delucchi
URL:http://talks.osgeo.org/foss4g-2023/talk/SC9WU8/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZDJSHB@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T120000
DTEND;TZID=Europe/Tirane:20230628T123000
DESCRIPTION:Join us for an in-depth exploration of the technological founda
tions of Re:Earth\, Eukarya Inc.'s open-source WebGIS platform. This 30-mi
nute session will provide a comprehensive analysis of the underlying mecha
nisms that empower Re:Earth's no-code\, user-friendly interface. We'll dis
sect the core architecture\, illustrate its data handling and visualizatio
n processes\, and elucidate the robust framework that facilitates plug-in
development. Aimed at both technology professionals and enthusiasts\, this
talk offers a rigorous\, detailed insight into the groundbreaking enginee
ring that positions Re:Earth at the forefront of geospatial data interacti
on.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Demystifying Re:Earth: A Technical Examination of Nocode WebGIS Pla
tform - Shinnosuke Komiya
URL:http://talks.osgeo.org/foss4g-2023/talk/ZDJSHB/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RGSUDP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T120000
DTEND;TZID=Europe/Tirane:20230628T123000
DESCRIPTION:When publishing (raster and vector) data in the form of a web m
apping application\, the first step is always to prepare a cache of the da
ta. Currently\, tiled images seem to be the industry standard - and the in
ternal format of the tiles is either PBF (for vector data) or PNG/JPEG/Web
P or similar raster data formats supported by current web browsers and des
ktop mapping applications (e.g. QGIS). \n\nMost of the tools out there are
going to store the raster tiles in a file-system structure\, using direct
ories for the Z and X tile coordinates and file names for the Y coordinate
. This is limiting for practical purposes as on some filesystems you can e
xceed the maximum number of files easily. While for the vector data\, the
OpenMapTiles project seems to be well established\, along with Tippecanoe
and Planetiler\, for the raster data tiles\, the field of tiling possibil
ities is wide open.\n\nThe tiling process can be very demanding on hardwar
e resources and time-consuming. Having the possibility to parallel process
the data or even use a cluster of machines for faster tiling could be cru
cial for some applications.\n\nIn this talk\, we will give an overview of
the current possibilities for tiling\, focused (but not exclusively) on th
e raster data tiles. Gdal2tiles\, QGIS tile generating tools\, mapproxy-s
eed\, mapcache_seed\, and others. Each of the tools has its place in the g
eospatial data provider ecosystem\, and so does MapTiler-Engine. With MapT
iler-Engine\, users can process large amounts of geospatial data and store
them in various output tile formats. It supports many input data formats
and adds modifications such as output color\, resolution\, and more. It al
so supports different tile matrix sets. MapTiler-Engine has a graphical us
er interface for easy usage\, but it also has a command line interface\, s
o you can make it part of a larger toolchain.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Tiling big piles of raster data using open source software and MapT
iler Engine - Jachym
URL:http://talks.osgeo.org/foss4g-2023/talk/RGSUDP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GGMTQL@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T120000
DTEND;TZID=Europe/Tirane:20230628T123000
DESCRIPTION:GeoServer is a web service for publishing your geospatial data
using industry standards for vector\, raster and mapping. It powers a numb
er of open source projects like GeoNode and geOrchestra and it is widely u
sed throughout the world by organizations to manage and disseminate data a
t scale.\n\nWhat can you do with GeoServer? This visual guide introduces s
ome of the best features of GeoServer\, to help you publish geospatial dat
a and make it look great! \n\nGeoServer has grown into an amazing\, capabl
e and diverse program - attend this presentation for:\n\n* A whirl-wind to
ur of GeoServer and everything it can do today.\n* A visual guide to some
of the best features of GeoServer.\n* Our favorite tricks we are proud of!
\n\nNew to GeoServer - attend this talk and prioritize what you want to lo
ok into first. Expert users - attend this talk and see what tricks and opt
imizations you have been missing out on.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:GeoServer Feature Frenzy - Andrea Aime\, Jody Garnett
URL:http://talks.osgeo.org/foss4g-2023/talk/GGMTQL/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-SQQSXP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T120000
DTEND;TZID=Europe/Tirane:20230628T123000
DESCRIPTION:Earth-Search is a publicly available SpatioTemporal Asset Catal
og (STAC) API providing an index for some of the public datasets available
through the AWS Registry of Open Data (RODA) and has been shown to be a v
aluable resource for accessing the Sentinel-2 archive as Cloud-Optimized G
eoTIFFs. A new version of Earth-Search is an update and enhancement of the
Sentinel-2 metadata as well as new Collections of data available on AWS\,
including Landsat Collection 2\, NAIP\, and Sentinel-1.\n\nThis talk will
include a summary of the STAC catalog\, what STAC extensions are used and
how the data is best accessed based on file formats. We will also dive in
to the datasets that are available through the API and will present the ar
chitecture for indexing including a discussion of data latency. We will pr
ovide resources and tutorials for how to get started with public geospatia
l datasets on AWS.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Earth-Search: A STAC API of Open datasets on AWS - Matthew Hanson
URL:http://talks.osgeo.org/foss4g-2023/talk/SQQSXP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TQEFNE@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T120000
DTEND;TZID=Europe/Tirane:20230628T123000
DESCRIPTION:In the OGC world\, you have a catalog to look for metadata/data
sets\, and the OGC API Features to fetch the data\, paginate\, filter and
so on.\nThe use cases have evolved since then and data consumers expect mo
re complete abilities from their data catalogs. Nowadays we want to analyz
e\, understand and reuse our datasets and providing such tools is a great
way to encourage data owners to share and open their warehouse. A data API
could then offer:\nFull text search on data points\nData fetching\, pagin
g\, sorting and filtering\nData analytics\, aggregation\, computation\nDat
a joining\nAnd those operations should perform in an optimized and scalabl
e manner.\nIt's what GeoNetwork has offered for decades now\, and GeoNetwo
rk is taking the move to opendata to address all those use cases.\n\nYou m
ight have heard about columnar formats\, and columnar vector formats such
as Arrow\, Parquet… After an introduction of the context and the expecta
tion of a well shaped data API\, we’ll present different approaches and
types of flow architectures\n- Warehouse formats\n - Static files (parque
t)\n - Index\n - Databases (PostGIS\, Cytus)\n- Api models and implement
ation\n - OGC API Features limitation\n - Duck DB\n - Pure SQL\nAnd com
pare the different stack in terms of efficiency depending on various use c
ases.\n\nThe final goal is to provide an API which serves search\, analyti
cs and dataviz purposes.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Open Data Analytics API in GeoNetwork - Olivia Guyot\, Florent Grav
in
URL:http://talks.osgeo.org/foss4g-2023/talk/TQEFNE/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-DVZYFC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T133000
DTEND;TZID=Europe/Tirane:20230628T140000
DESCRIPTION:We will discuss the algorithms inside [geowarp](https://github.
com/danieljdufour/geowarp)\, a high-performance and very low-level JavaScr
ipt library for reprojection\, resampling and cropping of data from GeoTIF
Fs and other rasters. This talk will be at the abstract algorithmic level
and is suitable for everyone. Here are some of the various algorithms th
at we will discuss:\n- [proj-turbo](https://github.com/danieljdufour/proj-
turbo): fit an unknown reprojection function to a simple affine transforma
tion \n- [fast-min](https://github.com/danieljdufour/fast-min)/[fast-max](
https://github.com/danieljdufour/fast-max): calculating the range of your
raster data leveraging the theoretical limits of the data types\n- near-ve
ctorize: automatically determining the optimal resampling algorithm based
on relative pixel size\n- [dufour-peyton-intersection](https://github.com/
GeoTIFF/dufour-peyton-intersection): calculate the pixels of an arbitrary
raster inside an arbitrary polygon\n- various resampling techniques includ
ing nearest\, bilinear\, vectorization\, and box-based statistical methods
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Algorithm Talk: How to Re-project a Raster at Warp Speed - Daniel J
. Dufour
URL:http://talks.osgeo.org/foss4g-2023/talk/DVZYFC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-NEHXDU@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T133000
DTEND;TZID=Europe/Tirane:20230628T140000
DESCRIPTION:Generalization is a crucial topic in the map production process
\, describing the derivation of a map of a smaller scale from another one.
It combines maintaining essential features and removing less important on
es to offer a readable map. Often\, this complex topic is reduced to a sel
ection of attributes\, creating label geometries\, and simplifying line an
d area geometries.\n\nThe presentation shares the knowledge of the cartogr
apher's toolkit by introducing the whole set of available generalization o
perators and showing less-known approaches for creating better maps. The e
ntire collection of operators consists of simplification\, smoothing\, agg
regation\, amalgamation\, collapse\, merging\, refinement\, exaggeration\,
enhancement\, and displacement\, which can be implemented by algorithms.\
n\nThe goal is to go behind the standards of creating centroids for labell
ing and using a Douglas-Peucker Algorithm for line simplification. A showc
ase of polygon simplification and creating label geometries are shown\, de
monstrating how to implement the operators using PostGIS with OpenStreetMa
p data. Several existing and working solutions for simplifying geometries
and labels are presented to showcase possibilities.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Cartographic generalization with Open Source - Mathias Gröbe
URL:http://talks.osgeo.org/foss4g-2023/talk/NEHXDU/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-WBBRH8@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T133000
DTEND;TZID=Europe/Tirane:20230628T140000
DESCRIPTION:The need to integrate geospatial data into products and service
s has resulted in a proliferation of Free and Open Source web APIs which o
ften do not adopt any standards\, thus requiring more development time and
a lack of interoperability between solutions. For instance a bounding box
has been written in multiple ways\, depending on whether developers use t
he coordinates of the four corners\, only upper left and lower right\, lat
itude or longitude first\, or some other variation.\n\nThe good news is th
at the Open Geospatial Consortium\, a neutral\, consensus-based organizati
on\, has been developing open standards for geospatial information. These
standards are [developed as building blocks](https://blocks.ogc.org/)\, wh
ich means they could be easily incorporated into existing applications in
order to enable a piece of geospatial functionality. The [location buildin
g blocks](https://blocks.ogc.org/register.html) are freely available to an
yone to download and use.\n\nIn this presentation\, we describe the concep
tual model for the existing building blocks\, which uses semantic annotati
ons to define the different components. We also describe a practical examp
le of how a building block could be integrated into an application and pro
vide some resources for developers who want to build applications with the
location building blocks.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Geo enabling your APIs with the location building blocks - Joana Si
moes\, Alejandro Villar\, Rob Atkinson\, Piotr Zaborowski
URL:http://talks.osgeo.org/foss4g-2023/talk/WBBRH8/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RR9KNT@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T133500
DTEND;TZID=Europe/Tirane:20230628T134000
DESCRIPTION:eoAPI is an open source project which aim to create a full Eart
h Observation API\, combining STAC metadata API (stac-fastapi)\, a Raster
dynamic tile service (TiTiler) and a Vector Tiles service (TiPg). \n\nUsin
g eoAPI AWS CDK template you're almost two command lines away of setting y
our own Earth Observation services.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:eoAPI - The Earth Observation API - Vincent Sarago
URL:http://talks.osgeo.org/foss4g-2023/talk/RR9KNT/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-LEN3PM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T134000
DTEND;TZID=Europe/Tirane:20230628T134500
DESCRIPTION:MIERUNE is a geospatial tech company in Japan. We set FOSS4G as
a foundation of us and continuously join the communities as an user\, a d
eveloper or a contributor. Thesedays we have been committing our new servi
ce - MIERUNE BASE. MIERUNE BASE is focussing on easily serving and sharing
datasets on a simple architecture based on serverless and FOSS4G. In this
talk\, we will introduce the architecture or techniques of MIERUNE BASE.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:MIERUNE BASE: The geospatial service for serving and sharing datase
ts - IGUCHI Kanahiro
URL:http://talks.osgeo.org/foss4g-2023/talk/LEN3PM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-DMTRUP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T134500
DTEND;TZID=Europe/Tirane:20230628T135000
DESCRIPTION:The quality of geospatial data is generally measured by its log
ical consistency\, completeness\,\npositioning quality\, semantic quality\
, temporal quality and genealogy [1]. In fact\, concerning the\nsituation
of geospatial data in Madagascar in the past\, since 1992\, the old orthop
hotos had been\nattached to the national reference system which is the int
ernational 1924 with Laborde as a\nprojection. The first old orthophotos w
ere achieved during the environmental program in 90s. In\nother hand\, the
remain old orthophotos were produced with the mission as national securin
g land\ntenure. However\, the geometric accuracy and details of all the ol
d orthophotos are different as well\nas they do not cover the national ter
ritory. If they cover a large area for about 60 000 km2\, some\nusers have
noticed discrepancies of a few meters or even more than a dozen meters on
certain\npoints\, even though the field of application is land. In Decemb
er 2019\, a ministerial order was\ndeveloped to define the technical speci
fications of photogrammetric work in the country. In this\nspecification\,
according to Chapter 4\, Section 14\, the accuracy of the orthophoto / or
thoimage is\nestimated by the planimetric root mean square deviation (emqX
Y) calculated from the differences\nbetween the ground coordinates and mea
sured orthoimage coordinates of certain clearly identifiable\ntopographic
features. For the orthophoto / orthoimages in urban areas\, the emqXY must
be better\nthan 1 m CE90 which is the circular error at the 90th percenti
le. For the rest of the territory other\nthan the urban area\, it must be
better than 3 m CE90 [2].\nTherefore\, not only is it crucial to be able t
o measure this quality\, but also to control\, to improve\,\nand finally t
o guarantee it [3]. The basic map in Madagascar is the topographic map at
the scale of 1\n: 100 000. However\, the average age of these maps is 60 y
ears. Consequently\, the contained\ninformation no longer meets the needs
of most users. On the other hand\, orthoimages produced later\nseem to be
much more accurate. To evaluate the accuracy of the 1 : 100 000 topographi
c map\, we\nfirst identified an orthophoto that could be used as a referen
ce. Furthermore\, we considered the\northobase elaborated in 2014 from the
SPOT5 image and the control result of the CASEF\n(Agricultural Growth and
Land Security) project orthoimage. The 2014 orthobase was produced\nwithi
n the framework of our cooperation with the La Reunion (France) region\, w
hile the CASEF\northoimage was developed for the purpose of land tenure se
curity in Madagascar.\nIn order to conduct this study\, we tried to answer
the following series of questions : 1) what is the\nmost accurate orthoim
age to serve as a reference\; 2) what is the average value of the deviatio
ns of\nthe objects on the 1 : 100 000 topographic maps as well as those of
these derived products (SCAN\n100 and BD 100) compared to those of the re
ference orthophotos. 3) Finally\, is there a set of\nparameters to reposit
ion the SCAN 100 / BD 100 on this orthoimage?\nTo achieve this study\, sev
eral steps were taken including literature reviews\, collection of a few\n
samples and observations of results from previous work. We also made resea
rches on the reference\ndata from which the BD 100\, the topographic maps
at 1 : 100 000 and SCAN 100 will be evaluated.\nFrom this comparison\, we
could see that the attachment to the national reference system of the\nCAS
EF orthoimage is more accurate than that of the orthobase. In addition to
that\, coordinate\npointing of identifiable geographic objects on both dat
asets were made with statistical evaluation of\nthe differences. Related t
o tools that we are adopting\, since that our budget has been limited in\n
terms of software license\, so that we are using open source geospatial so
ftware to make our\norganization better with QGIS during the evaluation pr
ocess.\nAfter evaluating four (04) sheets on the 1 : 100 000 map of Mahaja
nga\, Antalaha\, Manjakandriana\nand Toamasina\, we quantified the root me
an square errors at 109.3 m\, 108.6 m\, 128.4 m and 51.9 m\nrespectively.
The deviations are disparate\, therefore there is no single set of paramet
ers to reposition\nthe 1\,100\,000 topographic map. We concluded that the
BD 100 should be left as it is\, and that a newset of geographic databases
should be developed at different scales\, in particular the new version o
f\nthe BD 100.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Evaluation of the geometric accuracy of the base map 1 : 100 000 of
Madagascar compared to the CASEF ortho image - Marie Anna BAOVOLA
URL:http://talks.osgeo.org/foss4g-2023/talk/DMTRUP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KZMJRJ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T135000
DTEND;TZID=Europe/Tirane:20230628T135500
DESCRIPTION:Catasto-Open is an open-source set of tools for the Italian Cad
astre that manages geospatial data in a user-friendly and efficient manner
. The tool is designed to store\, retrieve and manipulate cadastral data\,
including property boundaries\, ownership information\, and other relevan
t details. By leveraging GeoServer and MapStore technologies\, it allows f
or the integration with existing GIS systems\, making it a versatile and v
aluable resource for managing geospatial data in an OGC-compliant pipeline
. The tool is accessible to a wide range of users\, including government a
gencies\, private companies\, and individual property owners\, also Catast
o-Open can be easily customizable to meet the specific needs of different
users.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Catasto-Open: open-source tools for the Italian Cadastre - Francesc
o Bartoli\, Antonio Cerciello\, Louis Nantenaina Andrianaivo
URL:http://talks.osgeo.org/foss4g-2023/talk/KZMJRJ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KUQR9L@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:The GeoNetwork-opensource project is a catalog application faci
litating the discovery of resources within any local\, regional\, national
or global "Spatial Data Infrastructure" (SDI). GeoNetwork is an establish
ed technology - recognized as an OSGeo Project and a member of the foss4g
community for over a decade. \n\nThe GeoNetwork team would love to share w
hat we have been up to in 2023! \n\nThe GeoNetwork team is excited to talk
about the different projects that have contributed with the new features
added to the software during the last twelve months. Our rich ecosystem of
schema plugins continues to improve\; with national teams pouring fixes\,
improvements and new features into the core application.\n\nWe will also
talk about the UI revamp through the geonetwork-ui framework\, and the new
perspectives it could bring to your catalogs. Progress of our main branch
es (4.2.x)\, and release schedule.\n\nAttend this presentation for the lat
est from the GeoNetwork community and this vibrant technology platform.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:State of GeoNetwork - Florent Gravin\, Jeroen Ticheler
URL:http://talks.osgeo.org/foss4g-2023/talk/KUQR9L/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KC9ALU@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:Vector tiles are changing the way we create maps. Client-side r
endering offers endless possibilities to the cartographer and has introduc
ed new map design tools and techniques. Let’s explore an innovative appr
oach to modern cartography based on simplicity and a comprehensive vector
tiles schema.\n\nTake a tour of vector tiles cartography basics and learn
about the latest trends through a number of examples illustrated with the
MapTiler maps. Get an overview of best practices and learn about simple op
en-source recipes\, towards advanced combinations of fills\, patterns\, fo
nts\, and symbols. Selected layer parameters and style expressions will be
discussed in a visual way and explained with basic syntax that you can ta
ke away.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Cartographic design for vector tiles: Best practices and open-sourc
e recipes for beautiful maps - Nicolas Bozon\, Petra Duriancikova
URL:http://talks.osgeo.org/foss4g-2023/talk/KC9ALU/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FLNJZX@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:Time dependent traffic speed information on a street level is i
mportant for routing services to estimate accurate arrival times and to re
commend routes which avoid traffic congestion. Still\, most open-source ro
uting machines that use OpenStreetMap (OSM) as the primary data source rel
y on static driving speeds for different highway types\, since comprehensi
ve traffic speed data is not openly available. In this talk\, we will pres
ent a method to model traffic speed by hour of day for the street network
of ten different cities worldwide and its integration in route planning us
ing the open-source routing engine openrouteservice.\n\nCurrent datasets o
n traffic speed are either not openly available (e.g. Google traffic layer
may be viewed but not downloaded)\, have very limited spatial coverage or
do not follow a consistent data format (e.g. data published by municipali
ties). In addition\, these datasets are often not based on the OSM street
network\, which means it would require extensive map matching procedures t
o transfer the traffic speed information to the OSM features. The most pro
mising data set is currently provided by Uber Movement containing hourly t
raffic speed data along OSM street segments in 51 cities worldwide from 20
15 until 2020. Still\, this data only covers roads for which enough Uber u
ser data is available. \n\nIn recent years\, several studies have proposed
methods and evaluated different data sources for traffic speed modelling.
Most of them model traffic speed using machine learning methods and diffe
rent indicators such as OSM tags (e.g. highway=*)\, points-of-interest (Ca
margo et al.\, 2020)\, centrality indicators (Zhao et al.\, 2017) or socia
l media data (Pandhare & Shah\, 2017). All of these indicators proved to b
e suitable for modelling traffic flow\, but none of these studies has eval
uated the effect of the modelled traffic speed on route planning and arriv
al time estimation.\n\nIn this study\, we modelled traffic speed by hour o
f day on a street level for 10 cities worldwide based on OSM tags\, an ada
pted betweenness centrality indicator and Twitter data. Uber traffic speed
data was used as reference data to train and evaluate a gradient boosting
regression model with different combinations of features. The simplest ba
seline model only used the OSM tags highway=* and maxspeed=* for predictio
n. The additional adapted betweenness centrality indicator was calculated
to identify highly frequented street segments in each city by simulating s
everal thousands of car trips in each city. In order to consider the geogr
aphic context\, the original centrality indicator calculation was adapted
to consider the spatial configuration of the city by including population
distribution and relevant POIs during the calculation. Finally\, Twitter d
ata was used to account for the spatio-temporal distribution of human acti
vity within the city. Using only the timestamp and geolocation of the twee
ts\, the number of tweets in the vicinity of a street segment aggregated b
y the time of day was used as an indicator. The quality of the different m
odels was evaluated with the help of the coefficient of determination (R2)
\, the root mean square error (RMSE) and the mean absolute error (MAE). In
all cities\, the Twitter indicators improved the model\, although this ef
fect was only visible for certain road types. The Twitter indicators impro
ved the accuracy especially for construction sites and motorways. For medi
um sized roads such as residential streets\, the prediction did not improv
e. The centrality indicator improved the model as well but to a lesser ext
ent. Best results were achieved in Berlin with an RMSE of 6.58 and R2 of 0
.82. \n\nTo use the modelled traffic speed data in route planning\, an exp
erimental traffic integration was implemented in openrouteservice using wh
ich traffic speed data can be passed to openrouteservice as a CSV file. Ea
ch row contains the traffic speed at a certain hour of the day and for a c
ertain OSM street segment specified by its OSM way id along with a start a
nd end node. The data is structured the same way as the Uber Movement data
making it possible to either integrate the raw Uber data or the modelled
traffic speed. The effect of using external traffic speed data on the trav
el time estimation was evaluated by calculating multiple random car trips
within different cities and at different times of the day and comparing it
to the estimated travel time of the Google Routing API as well as the ori
ginal openrouteservice implementation. In addition\, the raw as well as th
e modelled traffic data were compared. The comparison between travel times
in Google and openrouteservice showed regional differences in the accurac
y of estimated travel times. These differences could be partly alleviated
by incorporating raw or modeled traffic speed information. \n\nFuture rese
arch on traffic speed modelling using open data includes further developme
nt of the models and their transferability to other cities for which no Ub
er data is available. In this regard\, the potential of deep learning appr
oaches should be evaluated. Since Twitter has stopped providing their API
for free\, data from other social media platforms needs to be integrated.
The potential for this is high though\, since only the timestamp and geolo
cation of each tweet are used making the general approach easily transfera
ble. \n\nThe methods\, results and software generated within this study ar
e relevant to the FOSS4G community - in particular to the FOSS4G academic
track - since it combines scientific analysis in the form of traffic speed
modelling with open-source software development by integrating the result
s in openrouteservice. The source code for the prototypical traffic integr
ation is available on GitHub (https://github.com/GIScience/openrouteservic
e). The source code of the traffic speed model will be published along wit
h the paper.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Traffic speed modelling to improve travel time estimation in openro
uteservice - Christina Ludwig
URL:http://talks.osgeo.org/foss4g-2023/talk/FLNJZX/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-HNFAL8@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:Development of Tippecanoe\, a widely-used open-source C++ tool
for creating vector map tilesets\, has moved to Felt\, where it is a key c
omponent of the zero-configuration data ingestion pipeline that processes
Felt’s public data library layers as well as uploads from external users
.\n\nVersion 2 of Tippecanoe improves its automatic choice of zoom levels\
, and makes visual improvements to coordinate rounding\, small polygons\,
and the distribution of points in low zoom levels. It now runs faster and
uses less memory and disk space. There are new options to generate label p
oints for polygons\, to order features by attributes\, and to use Visvalin
gam line simplification. Tippecanoe now accepts FlatGeobuf input as well a
s GeoJSON and CSV\, and can generate output in PMTiles as well as MBTiles.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Faster\, easier\, more powerful map tile creation with Tippecanoe 2
.0 - Erica Fischer
URL:http://talks.osgeo.org/foss4g-2023/talk/HNFAL8/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-N7DXXW@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:There are no Free (as in Beer) and Open Source Cloud Datastores
. Let's have an opinionated look at some of the better alternatives to sto
re and modify\, private and public data for spatial applications.\n\nHavin
g build FOSS cloud interfaces 4 Geo since forever I decided to look at the
current state of data stores.\n\nWe have pretty much figured out how to d
o serverless in the cloud. Data at rest though is a completely different b
east. The going gets tough the closer you work to the metal. There is an o
verwhelming multitude of formats\, models and standards to chose from. Sho
uld we consider relational\, document\, and/or [column orientated] data fi
les?\n\nWith too many to discuss we put the spotlight on some exciting new
players such as bit.io and geoparquet.\n\nA recent Panorama (BBC) report
asked\; Is the cloud damaging the planet? Is it?\n\nIs there anything we c
an do? We want to share some best practices in regards to building data st
ore interfaces as well as running these services at scale\, and in product
ion.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Elephant in the room - Dennis Bauszus
URL:http://talks.osgeo.org/foss4g-2023/talk/N7DXXW/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FHMXWY@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:The OGC APIs are a fresh take at doing geo-spatial APIs\, based
on WEB API concepts and modern formats\, including:\n\n* Small core with
basic functionality\, extra functionality provided by extensions\n* OpenAP
I/RESTful based\n* JSON first\, while still allowing to provide data in ot
her formats\n* No mandate to publish schemas for data\n* Improved support
for data tiles (e.g.\, vector tiles)\n* Specialized APIs in addition to ge
neral ones (e.g.\, DAPA vs OGC API - Processes)\n* Full blown services\, b
uilding blocks\, and ease of extensibility\n\nThis presentation will provi
de an introduction to various OGC APIs and extensions\, such as Features\,
Styles\, Maps and Tiles\, STAC and CQL2 filtering. \nSome have reached a
final release\, some are in draft: we will discuss their trajectory toward
s official status\, as well as how good the GeoServer implementation is tr
acking them\, and show examples based on the GeoServer HTML representation
of the various resources.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Demystifing OGC APIs with GeoServer: introduction and status of imp
lementation - Andrea Aime
URL:http://talks.osgeo.org/foss4g-2023/talk/FHMXWY/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-8XAXBA@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:GeoMapFish is an open source WebGIS platform developed in close
collaboration with a large user group. It targets a variety of uses in pu
blic administrations and private groups\, including data publication\, geo
marketing and facility management. OpenLayers and an OGC architecture allo
w the use of different cartographic engines: MapServer\, QGIS Server\, Geo
Server. Recently new features have been added such as vector tiles integra
tion\, from raw data to visualization. In order to get rid of the AngularJ
S dependency\, a roadmap has been established for a migration to a web com
ponents architecture. K8S support is evolving with the implementation of t
he necessary tools for Azure environments. A highly integrated platform\,
a large number of features\, fine grained security and a mature reporting
engine are characteristics of the GeoMapFish solution. In this talk\, we w
ill present the key usages\, the state of the migration process to web com
ponents and latest functional developments\, including backend - frontend
decoupling allowing to plug in multiple front-end WebGIS clients.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:GeoMapFish Project Status - Yves Bolognini\, J. Wolfgang Kaltz
URL:http://talks.osgeo.org/foss4g-2023/talk/8XAXBA/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QSXAZ8@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:Redmine Geo-Task-Tracker (GTT) Plugin provides geospatial suppo
rt for Redmine. Redmine is a well-known OSS issue management system. GTT P
lugin enables to attach geospatial information(Point\, Polyline and Polygo
n) to each issues. It is effective in management many issues based on geos
patial infromation(ex. Road and park management). This talk introduces fea
tures and some use cases.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Redmine Geo-Task-Tracker (GTT) Plugin - Taro Matsuzawa
URL:http://talks.osgeo.org/foss4g-2023/talk/QSXAZ8/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-Q7TJLF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:Open source tools have played a significant role in enriching O
penStreetMap (OSM) with community mapping in Tanga\, Tanzania. These tools
have enabled local communities to actively participate in mapping their o
wn areas\, which has led to a more accurate and detailed representation of
the community on OSM. The use of open source tools in community mapping h
as also allowed for increased collaboration and sharing of data between co
mmunity members\, as well as with other organizations and researchers.\n\n
One such open source tool that has been used in community mapping in Tanga
is QGIS. This tool has been used to create detailed maps of the community
\, including roads\, buildings\, and other infrastructure. The use of QGIS
has also allowed for data analysis\, which has helped community members i
dentify areas in need of improvement and target resources more effectively
.\n\nAnother open source tool that has been used in community mapping in T
anga is OpenDataKit (ODK). ODK has been used to collect data in the field\
, such as information on the availability of healthcare facilities and ser
vices. This data has been used to create detailed maps of the community\,
which has helped community members identify areas in need of improvement a
nd target resources more effectively.\n\nThe use of open source tools in c
ommunity mapping in Tanga has also led to increased collaboration and shar
ing of data between community members\, as well as with other organization
s and researchers. For example\, community members have been able to share
their data with organizations working on healthcare and education project
s\, which has helped these organizations target resources more effectively
.\n\nOverall\, the use of open source tools in community mapping in Tanga
has been a significant factor in the success of OSM in the area. These too
ls have enabled local communities to actively participate in mapping their
own areas\, which has led to a more accurate and detailed representation
of the community on OSM. The use of open source tools in community mapping
has also allowed for increased collaboration and sharing of data between
community members\, as well as with other organizations and researchers\,
which has helped to improve the community and target resources more effect
ively.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:HOW OPEN SOURCE TOOLS ENRICHES OSM WITH COMMUNITY MAPPING IN TANGA-
TANZANIA - Antidius Kawamala
URL:http://talks.osgeo.org/foss4g-2023/talk/Q7TJLF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GK3YMN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T140500
DESCRIPTION:Get your preferred OSM dataset (ie. country) running in a local
Geoserver instance with only 2 commands and avoid any dependence on an ex
ternal provider.\nSimple\, fast\, clean solution. Lowering the barrier to
entry to geospatial technology use and development.\n\nDocker-compose setu
p which assembles the necessary components to implement a Geoserver instan
ce that publishes the OpenStreetMap (OSM) layers locally on a single host/
machine (Postgis is required to store the OSM layers).\nInstructions for t
his project are based on this repository OSM-Styles\, but make a much simp
ler execution plan. \nThe steps and scripts are intended to run in the con
text of Linux\, Mac and Windows environments.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Get your own OpenStreetMap dataset running in a Geoserver instance
in 2 steps - Jose Macchi
URL:http://talks.osgeo.org/foss4g-2023/talk/GK3YMN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-DSVJWG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140000
DTEND;TZID=Europe/Tirane:20230628T143000
DESCRIPTION:Landfill sites are for storing waste in a secure and secluded m
anner but they can cause a lot of damage to the environment by generating
greenhouse gases and contaminating soils by releasing heavy metals and tox
ins. Monitoring the area of landfill sites from space is a challenging pro
blem because of the huge amount of unstructured data and unavailability of
standard datasets and procedures. By combining open-source tools with geo
spatial data\, we present a global dataset that monitors the changes in th
e landfill area. We have achieved this by developing a deep learning based
segmentation model that uses multispectral satellite data and segments th
e landfill areas from them. In order to develop the model\, we have labell
ed landfill sites from optical imagery from all over the world. Our curren
t segmentation model has 31 million parameters and has achieved an accurac
y of 77.6% on the test set. Currently\, the dataset contains temporal data
from 2021 of the major landfill sites from more than 7 countries and it i
s growing daily as new data is coming in. In future\, we aim to enhance th
is dataset by adding more variables other than the area\, for instance hei
ght of the landfill and will also explore other higher resolution data for
validating our results further.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Monitoring Landfill sites from space - Saptarshi Pal
URL:http://talks.osgeo.org/foss4g-2023/talk/DSVJWG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-R798TN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T140500
DTEND;TZID=Europe/Tirane:20230628T141000
DESCRIPTION:The delivery of national census programs to aid nations in comi
ng up with better strategies for serving the population’s needs and bett
er plans for sustainability. While on the other hand\, several developing
nations around the world have not been able to deliver highly accurate cen
sus data and results to aid in these efforts. This leads to the implementa
tion of policies that are not inclusive among other limitations introduced
along the way. \nBy leveraging on open data platforms such as OpenStreetM
ap\, open-source geo applications can be built to aid developing nations i
n accurate and location-driven data-capturing processes. Having digital lo
cation strategies and innovation as the major component for census data co
llection can potentially lead to vast growth in digital economies across d
eveloping nations and unleash endless possibilities and potential innovati
ons which are inclusive and fit for purpose. This also provides a platform
and chance to have more contributions towards OSM at the national level w
hile delivering accurate and much-needed data.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Leveraging on OpenStreetMap (OSM) for Improved Census Data Delivery
- Kumbirai Matingo
URL:http://talks.osgeo.org/foss4g-2023/talk/R798TN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-7PLC3D@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T141000
DTEND;TZID=Europe/Tirane:20230628T141500
DESCRIPTION:UNVT Portable is a package for RaspberryPi that allows users to
access a map hosting server via a web browser within a local network\, pr
imarily for offline use during disasters. It is designed to aid disaster r
esponse by combining aerial drone imagery with OpenStreetMap and open data
tile datasets.\n\n"UNVT Portable" is a map server that allows you to free
ly use web maps from devices such as smartphones even in an offline enviro
nment. It is mainly designed to work in an offline environment in the even
t of a major disaster\, and various open data tiles are prepared in advanc
e\, such as drone aerial images taken after a disaster\, OpenStreetMap\, a
nd satellite images released for free by JAXA(Japan Aerospace Exploratio
n Agency)\, etc. Combine sets to create the maps you need in times of di
saster. We envision a use case for municipalities\, etc. to understand the
situation after a disaster and to respond to disasters. It is built using
open source software such as Apache and MapLibre and Raspberry Pi\, and i
s completely open source. Unlike tools such as Google Maps\, which are dif
ficult to use for secondary purposes\, it is being developed as open sourc
e so that it can be released in a form that can be easily used by anyone\,
including local governments\, international organisations and private com
panies.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Offline web map server "UNVT Portable" - ShogoHirasawa
URL:http://talks.osgeo.org/foss4g-2023/talk/7PLC3D/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FCXBLT@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T141500
DTEND;TZID=Europe/Tirane:20230628T142000
DESCRIPTION:The Web Map Service (WMS) is the most popular standard of shari
ng data remotely. It is commonly used as a basemaps\, a way of presenting
governmental spatial data\, and as a data source when creating vector data
sets. Creating a WMS requires original data to be read and then rendered.
This process can be slow\, especially if the source data is heavy and not
optimized. This is the case\, for example\, with Sentinel 1 global satelli
te data\, which is a collection of daily revisions with a total volume of
250 GB per one day. Here we demonstrate an efficient way to share such a v
ery large data set as WMS using Mapserver scaled with Kubernetes. \n\nMaps
erver is used as engine of our WMS\, because of it speed and ease of autom
ation. In order to optimise the performance of the service and therefore t
he user experience\, it is recommended to store the data in the right form
at\, with the right file structure also being aware of limitations of stor
age\, bucket or disk read speed. GDAL provides a set of options that can b
e executed in a single command to overwrite the original data with new\, c
loud optimized. It is usually good practice to store selected zoom levels
as a cache\, but for time series data that is enriched daily\, the cache i
s not overwritten as new data arrives\, but is incremented. \n\nDespite it
s popularity and advantages\, WMS as a standard of serving data has its li
mitations. The potentially large disk read time is multiplied by the numbe
r of users sending requests. Tests using JMeter (100 users sending 100 Get
Map requests in a loop) have shown that on a relatively strong processor (
32CPU)\, the greatly increased traffic acts as a distributed denial-of-ser
vice (DDoS) - the server stops responding. \n\nThis problem is solved usin
g Kubernetes (K8s) which allows metric-based automatic horizontal scaling
of containerised applications\, in this case – Mapserver. Prometheus as
a K8s cluster monitoring tool allows custom metrics to be defined e.g.\, n
umber of http requests per time interval. Prometheus makes it possible to
distribute the traffic between newly created pods so that all requests can
be answered. \n\nThe aim of the talk is to stimulate discussion\, confron
t the idea with experts and demonstrate good practice in creating a public
ly accessible WMS\, with a focus on optimising speed under heavy source da
ta conditions\, supported by a working example and statistics.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Why is popularity the biggest enemy of WMS? - Marcin Niemyjski
URL:http://talks.osgeo.org/foss4g-2023/talk/FCXBLT/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KXNZMV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T142000
DTEND;TZID=Europe/Tirane:20230628T142500
DESCRIPTION:Surface runoff is one of the processes with direct impact on wa
ter erosion. Surface runoff has two basic components: a) sheet runoff and
b) rill runoff. Observation of these phenomena at various scales and then
using mathematical models to describe their observations plays a key role
for soil protection. One of the models developed to compute these phenomen
a is SMODERP\, used for example in the flexible and adaptive approach to l
and management and landscape planning called Model of Living Landscape pro
ject. Innovative application of the SMODERP model (https://github.com/stor
m-fsv-cvut/smoderp2d) named SMODERP Line is presented in this contribution
. SMODERP Line is accessible through various interfaces including OGC Web
Processing Service (WPS) which can be easily integrated into user-defined
processing pipelines or web applications. Usage of SMODERP2D Line will be
demonstrated in the QGIS environment through a new OWSLib-based QGIS WPS C
lient Plugin (https://github.com/OpenGeoLabs/qgis-wps-plugin).\n\nThis con
tribution was supported by grant RAGO - Living landscape (SFZP 085320/2022
) and Using remote sensing to assess negative impacts of rainstorms (TAČR
- SS01020366).
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Surface Runoff Processes and Design of Erosion Control Measure in L
andscape and Artificial Slopes - Martin Landa\, Ondřej Pešek\, Petr Kavk
a
URL:http://talks.osgeo.org/foss4g-2023/talk/KXNZMV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-JJMSXT@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:**MapTiler SDK** is a TypeScript layer that adds new capabiliti
es on top of MapLibre GL\, both in terms of UI and core features. It also
comes with an interface to **MapTiler Cloud REST API**.\nThe features we h
ave added on top of MapLibre are of two kinds: many convenient helpers to
make the developers' life easier\, and plenty of built-in defaults that ar
e specially made to use MapTiler data without having to specify annoying U
RLs or {ZXY} patterns\, yet keeping it 100% backward compatible with MapLi
bre. In addition\, all our services from MapTiler Cloud API\, such as geoc
oding\, IP geolocation\, coordinate transforms\, or static maps generation
\, are now easily accessible with well-documented TypeScript functions. Al
l this with an open-source license.\n\nIn the talk\, we are going to prese
nt the library\, showing practical examples and outputs. We believe\, that
the SDK is going to make the life of the web mapper easier not only by pr
oviding a close integration of MapTiler services but also by the new compo
nents and library itself. \n\nThe demo will feature some nice weather visu
alization we’ve been working on lately!
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:MapTiler SDK\, the MapLibre experience on steroids - Jonathan Lurie
URL:http://talks.osgeo.org/foss4g-2023/talk/JJMSXT/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PDJAM9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T143500
DESCRIPTION:Chemical incidents\, such as accidents at heavy chemical plants
or large-scale toxic gas leaks\, are difficult to assess accurately becau
se of the large spatial extent of the damage and the rapidly changing scop
e/level/target of the damage over time. These characteristics also make it
hard to conduct experiments to recreate or simulate large-scale chemical
incidents in real world. In the case of large-scale chemical accidents or
release\, post-incident damage assessment is as important as prevention\,
but spatial ambiguity makes it difficult to assess the extent of damage to
victims\, and there is little way to identify fake victims from real ones
. \n\nIn this 5 year-long study\, we aim to combine the results of a chem
ical diffusion model and the location data of mobile service subscribers o
n the incident spot over time. For this\, FOSS4G based 3D geospatial web s
ervice using GeoServer\, Postgresql/PostGIS\, Cesium\, etc. will be develo
ped to assess the level of chemical exposure of each victim and calculate
the level of damage based on it. \n\nIn 2022\, the first year of the stud
y\, we developed a prototype that combines the time-dependent output of th
e chemical diffusion model with the time-dependent location data of indivi
duals and successfully visualized it in a Web 3D globe. In the coming year
\, we'll further develop this system into an integrated risk assessment pl
atform for chemical accidents by combining chemical exposure assessment mo
del and damage calculation model.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Visualization of accidental chemical release simulation - Sanghee S
hin\, Kim Jinho
URL:http://talks.osgeo.org/foss4g-2023/talk/PDJAM9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FFCRRB@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:The increasing availability and ease of access of global\, hist
orical and high-frequency remote sensing data has offered unprecedented po
ssibilities for monitoring and analysis of environmental variables. Recent
studies in the field of ecosystem resilience relied on indicators derived
from time-series analysis\, such as the temporal autocorrelation and the
variance of a system signal (Dakos et al.\, 2015). The aforementioned avai
lability of global\, temporally and spatially dense time-series of indicat
ors of biomass and greenness of vegetation\, such as the normalized differ
ence vegetation index (NDVI) among others\, has boosted ecosystem resilien
ce scientific applications to forests as well. The ecological definition o
f resilience corresponds with the capacity of a system to absorb and recov
er from a disturbance. When dealing with ecosystems increasingly affected
by natural and anthropogenic pressures such as forests\, monitoring their
health is particularly relevant. \n\nForest ecosystems play a crucial part
in the global carbon cycle and in any climate change mitigation strategy\
, despite being increasingly affected by natural and anthropogenic pressur
es. While anthropogenic action on forests is mainly represented by stand r
eplacement\, natural perturbations include wind throws and fires\, as well
as extended insects and disease outbreaks\, such as the recent outbreak a
ffecting Central Europe. These natural disturbances are strictly interconn
ected with the change in climate. A forest ecosystem with decreased resili
ence will be more susceptible to external drivers and their change and lik
ely to shift into an alternative system configuration by crossing a tippin
g point.\n\nHowever\, remote sensing data quantifying vegetation and fores
ts properties inherently carry information related to the climate as well.
If not accounted for\, these confounding factors\, such as short-term cli
mate fluctuations\, may hide the actual vegetation anomalies focus of a st
udy and the importance of other drivers in vegetation itself. In addition\
, the comparison of the same vegetation property between different geograp
hical areas naturally affected by different climates is hindered. \n\nIn o
rder to explore the relationships of a set of environmental metrics with a
n indicator of the resilience of forests and their relative predictive imp
ortances\, a machine learning (ML) model is implemented. In this paper\, w
e aim to present the general workflow and the challenges encountered in pr
ocessing and analyzing the time-series of vegetation\, climate and the oth
er environmental variables data. Rather than focusing on the scientific ou
tcomes of the implemented model\, the focus of this paper will be on a wor
kflow implemented to analyze the aforementioned time-series and on the met
hods and tools implemented to account for the climate effects on vegetatio
n. Deseasonalization\, detrending\, growing season identification and remo
val of climatic confounding effects will be targeted by the presented tool
s and methods\, being aware of the variety and heterogeneity of methodolog
ies existing in the field of time-series analysis. \n\nAll data leveraged
for this study are open. The long-term kNDVI is retrieved by processing th
e full time-series of daily MODIS Terra and Aqua Surface Reflectance at 50
0m from 2003 to 2021. The kNDVI is a nonlinear generalization of the NDVI
that shows stronger correlations than NDVI and NIRv with forest key parame
ters. kNDVI is also more resistant to saturation\, bias\, and complex phen
ological cycles\, and it is more robust to noise and more stable across sp
atial and temporal scales (Camps-Valls et al.\, 2021). Hourly ERA5-Land da
ta with the same timespan at 10km are used to retrieve the set of climatic
and environmental predictors including temperature\, precipitation\, etc.
Most data are computed as 8 days averages or sums in order to retrieve re
silience metrics from high temporal resolution time-series.\n\nThe data pr
ocessing takes place mainly within Google Earth Engine (GEE) and the Joint
Research Centre (JRC) Big Data Analytics Platform (BDAP). Google Earth En
gine is a cloud-based geospatial analysis platform providing a multi-petab
yte catalog of satellite imagery and geospatial datasets coupled with larg
e analysis capabilities (Gorelick et al.\, 2017). The JRC Big Data Analyti
cs Platform is a petabyte-scale storage system coupled with a processing c
luster. It includes open-source interactive data analysis tools\, a remote
data science desktop and distributed computing with specialized hardware
for machine learning and deep learning tasks (Soille et al.\, 2018). GEE i
s mainly used to pre-process MODIS data. The ERA5 pre-processing and the c
ore time-series analysis are performed within the JEODPP\, where main tool
s include R\, Climate Data Operator (CDO) and netCDF Operators (NCO). The
whole machine learning model is instead trained and run in R. The differen
t platforms and tools implemented in the study highlight as well the heter
ogeneity of data involved\, data availability and data formats\, ranging f
rom TIFF\, netCDF and R objects. \n\nThe final aim of this paper is to pre
sent one of the many workflows that can be implemented when dealing with t
ime-series of vegetation-related data in the geospatial domain\, where cli
mate plays a crucial role as a confounding effect. The importance of the a
vailability of open data and open source tools and platforms in making thi
s big data analysis possible is also strongly highlighted.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Methods and challenges in time-series analysis of vegetation in the
geospatial domain - Agata Elia
URL:http://talks.osgeo.org/foss4g-2023/talk/FFCRRB/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-HWMNYA@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:GeoServer is a web service for publishing your geospatial data
using industry standards for vector\, raster and mapping. Choose additiona
l extensions to process data (either in batch or on the fly) and catalog r
ecords.\n\nGeoServer is widely used by organizations throughout the world
to manage\, disseminate and analyze data at scale. GeoServer web services
power a number of open source projects like GeoNode and geOrchestra.\n\nTh
is presentation provides an update on our community as well as reviews of
the new and noteworthy features for the latest releases. In particular\, w
e will showcase new features landed in 2.22 and 2.23\, as well as a previe
w of what we have in store for 2.24 (to be released in September 2023).\n\
nAttend this talk for a cheerful update on what is happening with this pop
ular OSGeo project\, whether you are an expert user\, a developer\, or sim
ply curious what GeoServer can do for you.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:State of GeoServer - Andrea Aime\, Jody Garnett
URL:http://talks.osgeo.org/foss4g-2023/talk/HWMNYA/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-WZN3ZN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:The National Land Survey of Finland (NLS) is a government agenc
y that maintains finnish property register and uses various administrative
information systems that handle crucial data. To develop\, manage\, and m
aintain these systems\, NLS follows a Business Technology Standard model a
nd aims to publish its own production applications as open source software
and use open source applications in development when possible. \n\nDuring
the development of new information systems\, NLS follows an agreed and ap
proved management model and uses only components and software that meet de
velopment guidelines. Examples of such components are QGIS and PostgreSQL.
However\, if NLS needs to adopt and evaluate components that are not yet
included in the development guidelines\, it must evaluate associated open
source projects\, record and process considerations\, and accept them in a
ccordance with the change management process. \n\nTo evaluate the maturity
of open source projects\, NLS has developed a tool that continuously evol
ves to reflect the needs of the organization. The tool is a checklist of c
riteria that can be used to assess the maturity of a project and compare i
t to similar products. The presentation explains the items in the tool and
their significance as part of the metrics. \n\nThe tool that NLS has deve
loped could be valuable for individuals and companies in similar positions
when evaluating open source projects for their needs. The experiences gai
ned by NLS can also help improve weak points that open source software pro
ducers may not have considered in their own projects.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Evaluation and assesment of open source projects - Tero Rönkkö
URL:http://talks.osgeo.org/foss4g-2023/talk/WZN3ZN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-LW7AJX@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:Valhalla proved\, since its inception in 2015\, to be a valuabl
e part of the OSM software universe\, occupying an important niche in the
routing section. It's arguably one of the most feature-rich open-source ro
uting engines\, serving many different use cases and integrations/deployme
nts.\n\nHowever it's a fairly complex system which is hard to comprehensib
ly document and new users or developers are often overwhelmed. So\, I'd li
ke to introduce its general architecture\, capabilities and showcase "new"
features (the last talk was given in 2016 on FOSS4G NA)\, as well as the
accompanying open-source software\, like various libraries\, clients and d
ocker image(s).
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Valhalla Routing Engine - Nils Nolde
URL:http://talks.osgeo.org/foss4g-2023/talk/LW7AJX/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-YL8DVJ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:This talk is about a prototype that enables collaborative mappi
ng without the need of any internet connectivity\, only a local network is
required. It runs fully in the browser\, hence is cross-platform\, it bas
ically runs on any smartphone. The users form a peer-to-peer network in or
der to exchange their data.\n\nIt can be used in situations where there ei
ther is no internet infrastructure\, it's spotty or it was destroyed. In t
he disaster response case\, only a local network\, without any server infr
astructure\, would be needed.\n\nIn the talk you'll learn about content-ad
dressing\, WebRTC and peer-to-peer networks and of course experience a liv
e demonstration of the prototype.\n\nThe tech-stack is [Svelte] for the ap
plication\, [OpenLayers] for displaying the map\, [IPFS] for the storage\,
[libp2p] for the networking. The project is licensed under the Apache/MIT
licenses.\n\n[Sevelte]: https://svelte.dev/\n[OpenLayers]: https://openla
yers.org/\n[IPFS]: https://ipfs.tech/\n[libp2p]: https://libp2p.io/
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Collaborative mapping without internet connectivity - Volker Mische
URL:http://talks.osgeo.org/foss4g-2023/talk/YL8DVJ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-W9TDES@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:MapComonents is an open-source framework extending React for ma
pping applications. It can be used to develop browser-based applications t
hat do not require any backend\, as well as web clients that use an arbitr
ary number of backend services. MapComponents uses MapLibre for rendering\
, raster\, and vector tiles. \n\nIt provides working defaults wherever pos
sible enabling the usage with minimal parameters. At the same time\, it ex
poses the entire MapLibre API allowing very granular control of the result
where it is needed. Solutions for more complex and common requirements su
ch as PDF export\, a feature editor\, layer tree\, WMS loader\, measure to
ols\, or bookmarks are provided as ready-to-use and highly configurable dr
op-in components. Exotic requirements include the swipe tool\, the magnify
ing glass that partially shows two synchronized MapLibre instances or comp
onents that render 3D meshes or deck.gl.\n\nLayers on the map are covered
by several components and example codes in our lab repository. It can be c
ombined with a backend for managing a more extensive data set. In addition
\, it also works as a progressive web app offline with most functions. Cre
ating dashboards and complex user interfaces that combine maps and diagram
s MapComponents is more straightforward than traditional approaches\, give
n the declarative nature of React and its vast ecosystem of existing compo
nents. \n\nThe presentation will show and explain an actual example and it
s function. MapComponents framework is available under the MIT license and
developed by WhereGroup GmbH.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:MapComponents for your React application - Mathias Gröbe
URL:http://talks.osgeo.org/foss4g-2023/talk/W9TDES/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-8YVPDP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:These days we have an incredible amount of (open-source) geo-sp
atial data\, remote sensing data and insights\, plus the tools to share th
em with the world! But when building a web map application or dashboard we
often end up with too cluttered visualizations\, confusing jargon\, scary
technology or struggle in communicating with the geo-data illiterate. GIS
technology can be hard to understand. \n\nHow do we design and build a ma
p application showing a huge amount of geo-data accompanied by the elabora
te functionality to discover it? \nAs GIS experts we think from a technolo
gical perspective\, adding more and more buttons\, layers\, panels\, pop-u
ps\, legends\, draw tools\, scale-bars. But these GIS terms makes an appli
cation confusing\, scary and technically hard to understand for the user..
\nOn the other hand\, UX and IX designers think about usability\, smooth
experiences and helping users to easily navigate\, see\, use and interpret
an application. But they lack the understanding of specific map related d
esign requirements and map related interactivity. Here\, the map is taken
for granted and is often not well designed..\n\nI often find myself mediat
ing between the GIS and cartographic professionals\, web-developers\, UX a
nd IX designers and data-designers. I believe there is still a lot we can
improve with each other! \nSo let’s bridge the gap and join the conversa
tion about Interactive Cartography! In this talk I will give some clear us
eful examples. What is Interactive Cartography and what can we learn in th
is? Be amazed with some simple examples which can quickly improve your we
b map application!
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:“Let’s put it on the map!” a manifestation about : Cartograp
hic interaction\, a two-way dialogue between a user and a map mediated by
a computing device. - Niene Boeijen
URL:http://talks.osgeo.org/foss4g-2023/talk/8YVPDP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-BSMTUZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:One decade ago\, we saw the launch of the first earth observati
on cubesats by Planet Labs. In the years since we have seen hundreds of sa
tellites launched\, and dozens of startup companies launching taskable sat
ellites. While this has led to incredible opportunities to leverage multip
le sensors and sensor modalities\, the massive increase of data has also c
reated challenges in data management\, discovery\, and usage. The communit
y driven SpatioTemporal Asset Catalog (STAC) specification was an importan
t step forward in exposing data to users in a standard way that enables cl
oud-native workflows and has been successful across government and industr
y.\n\nThe process of actually tasking satellites\, however\, is still very
much non-standard\; each data provider exposes a unique API\, if at all.
Some data aggregators have created a single tasking API that proxies and t
ranslates to multiple data provider APIs\, but this is still non-standard\
, and proprietary. \n\nElement 84 has been leading an effort to create a c
ommunity standard API around how users order future data and how providers
respond to those requests. Working with government groups\, commercial sa
tellite operators\, and data integrators\, we have hosted working sprints
to develop a specification and open-source tooling demonstrating the power
of a tasking API specification.\n\nThis talk will cover the current statu
s of the community tasking API specification\, future plans\, and a demons
tration of how to use the API to order data.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Standardizing Satellite Tasking for Consumers - Matthew Hanson
URL:http://talks.osgeo.org/foss4g-2023/talk/BSMTUZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PHZ3JS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143000
DTEND;TZID=Europe/Tirane:20230628T150000
DESCRIPTION:IDeAMapSudan is a 2.5-year project finishing in March 2023. The
project aims to develop a community-led geospatial database for mapping d
eprived urban areas (e.g.\, informal settlements) that will support the de
cision-making process for displacement and socio-economic reconstruction i
n Khartoum\, Sudan. To that end\, nine trainers from different governmenta
l and non-governmental organizations were selected to be trained by a team
of international experts from the Faculty ITC of the University of Twente
\, The Netherlands\; the Universite Libre de Bruxelles\, Belgium\; and fro
m the African Population and Health Research Center Kenya. These nine trai
ners were taught the essential competencies in using Free\, and Open Sourc
e Geospatial Software to produce\, compile\, curate and distribute spatial
data. Once the training of the nine trainers was completed\, a series of
community workshops were organized so that the trainers could train local
community actors in tasks related to spatial data curation in close relati
on to their communities. The datasets produced from this process were then
used to create a deprivation model and additional open data sets that can
be used to help local communities and actors to take actions to mitigate
several types of deprivations:\nUnplanned urbanization - e.g. small\, high
-density\, disorganized buildings\nSocial risk - e.g. no social safety net
\, crime\nEnvironmental risk - e.g. flood zone\, slopes\nLack of facilitie
s - e.g. schools\, health facilities\nLack of infrastructure - e.g. roads\
, bus service\nContamination - e.g. open sewer\, trash piles\nLand use/rig
hts - e.g. non-residential zoning\n\nThis talk will describe three signifi
cant aspects of the project: the curriculum of competencies and the softwa
re tools used to teach these competencies\; the phases and challenges of a
ssembling a team and infusing it with a sense of community and participati
on\; and the importance of disseminating results and evaluate the social i
mpact open source software and open data can have.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:IdeaMap Sudan - Building a geodata community in a data scarse conte
xt - Andre da Silva Mano
URL:http://talks.osgeo.org/foss4g-2023/talk/PHZ3JS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RKGNWM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T143500
DTEND;TZID=Europe/Tirane:20230628T144000
DESCRIPTION:Here comes a developer story about **contributing to GeoDjango*
*.\n\nAn unfortunate combination of a valid\, but unconventional spatial r
eference on the one hand\, and "smart" logic for a mixed-geometry dataset:
Geometries supposed to be located in Austria ended up in the Near East.\n
\nInvestigation showed that GeoDjango's behaviour for returning the SRID o
f the dataset was not according to its documentation (see [Django ticket #
34302](https://code.djangoproject.com/ticket/34302)). While fixing the iss
ue\, additionally\, an incorrect type cast from `None` to string was disco
vered.\n\nIn this talk **you will also learn**:\n1. How to set up the GeoD
jango test suite with a PostGIS docker container\n2. How the Django code r
eview process looks like
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:How I discovered\, tested and fixed a bug in GeoDjango - Stefan Bra
nd
URL:http://talks.osgeo.org/foss4g-2023/talk/RKGNWM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-J8FDC3@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T144000
DTEND;TZID=Europe/Tirane:20230628T144500
DESCRIPTION:Ground-based weather sensor networks are essential in monitorin
g local weather patterns and climate. Integration of such data into GIS en
vironments is critical to supporting manifold applications including urban
planning\, public health studies\, and weather forecasting.\nThese networ
ks use scattered geolocalized sensors to measure multiple atmospheric vari
ables (e.g. air temperature\, wind speed\, precipitations). Often\, data i
s distributed online by network managers which can be either local/nationa
l authorities\, private companies\, or volunteers. Due to the diversity of
data providers\, both formats and access patterns of meteorological senso
r data are heterogeneous and the preprocessing tasks (e.g. temporal aggreg
ations\, spatial filtering) are generally time-consuming.\nGiven the above
and to increase end-users exploitation of such sensor data\, we present t
he development of an experimental QGIS plugin facilitating access and prep
rocessing of openly available data from ground-based sensor networks and e
nabling their direct use in QGIS. The plugin is designed to implement REST
APIs connections and HTTP requests to download data. A user interface all
ows for selecting time intervals and types of observation to be downloaded
. Once data is retrieved\, the plugin provides options for filtering\, out
liers removal\, time aggregation with summary statistics as well as observ
ation mapping into a standard GIS layer. These functionalities are only pa
rtially available in similar existing QGIS plugins. The plugin leverages F
OSS Python libraries for data handling including Pandas. The Dask parallel
computing library is also exploited to speed up I/O operations on raw dat
a.\nThe current version of the plugin is developed to retrieve and process
weather sensor data provided by the Environmental Protection Agency of Lo
mbardy Region (ARPA Lombardia)\, Northern Italy. The data retrieval is bas
ed on the Sodapy Python library\, a Python client for the Socrata Open Dat
a API. The plugin's work-in-progress source code is available at (https://
github.com/gisgeolab/ARPA_Weather_plugin) released under MIT license. The
plugin is being developed within the LCZ-ODC project (agreement n. 2022-30
-HH.0) funded by Italian Space Agency (ASI)\, which aims to identify Local
Climate Zones within the Metropolitan City of Milan.\nOngoing work includ
es the extension of the plugin functionalities to incorporate additional d
ata providers\, starting from other Italian regional ARPAs. The goal of th
is project is to provide a reproducible framework to access and handle wea
ther data into QGIS\, thus extending the capability of the software to sup
port a wider range of practitioners and applications.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:A QGIS plugin for local weather sensor data - Emanuele Capizzi
URL:http://talks.osgeo.org/foss4g-2023/talk/J8FDC3/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-NC7PT8@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T144500
DTEND;TZID=Europe/Tirane:20230628T145000
DESCRIPTION:OpenStreetMap is an open source data which any one can access i
t free. This data is contributed by the local communities or individuals v
oluntarily. For them to gather together\, we use mapathons to bring them f
or the mapping. A lot of data is added during these mapathons to help vuln
erable people around the Globe.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Organising Mapathons - Awania Morish
URL:http://talks.osgeo.org/foss4g-2023/talk/NC7PT8/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-38Q87Y@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T153000
DESCRIPTION:We will discuss the state of [GeoRasterLayer](https://github.co
m/geotiff/georaster-layer-for-leaflet)\, a JavaScript library that renders
GeoTIFFs directly on a LeafletJS map without a server. This will include
an introduction of new features\, including the following:\n- shifting wa
rping off the main thread to a pool of web workers\n- improved support for
extent calculations by increasing vertex density of polygon representatio
ns of bounding boxes\n- high-resolution support by using [geowarp](https:/
/github.com/danieljdufour/geowarp)\n\nWe will also look to the future and
discuss the following:\n- support for raster types other than GeoTIFF/COG\
n- geozarr support\n- similar integrations into other web mapping librarie
s\n\nAudience feedback and ideas will be most welcome!
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:State of GeoRasterLayer (for Leaflet) - Daniel J. Dufour
URL:http://talks.osgeo.org/foss4g-2023/talk/38Q87Y/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-D38YER@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T153000
DESCRIPTION:Motivation: \nSpatial Data Infrastructures (SDI) developed for
the exchange of environmental\nhas heretofore been greatly shaped by the s
tandards issued by the Open\nGeospatial Consortium (OGC). Based on the Sim
ple Object Access Protocol (SOAP)\,\nservices like WMS\, WFS\, WCS\, CSW b
ecame digital staples for researchers and\nadministrative bodies alike. \n
\nIn 2017 the Spatial Data on the Web Working Group (SDWWG) questioned the
overall\napproach of the OGC\, based on the ageing SOAP technology\n[@SDW
WG2017]. The main issues identified by the SDWWG can be summarised as:\n\n
- Spatial resources are not identified with URIs.\n- Modern API frameworks
\, e.g. OpenAPI\, are not being used.\n- Spatial data are still shared in
silos\, without links to other resources.\n- Content indexing by search en
gines is not facilitated.\n- Catalogue services only provide access to met
adata\, not the data.\n- Data difficult to understand by non-domain-expert
s.\n\nTo address these issues the SDWWG proposed a five point strategy ins
pired on the\nFive Star Scheme [@BernersLee2006]:\n\n- **Linkable**: use s
table and discoverable global identifiers.\n- **Parseable**: use standardi
sed data meta-models such as CSV\, XML\, RDF\, or JSON.\n- **Understandabl
e**: use well-known\, well-documented\, vocabularies/schemas.\n- **Linked*
*: link to other resources whenever possible.\n- **Usable**: label data re
sources with a licence.\n\nThe work of the SDWWG triggered a transformatio
nal shift at the OGC towards\nspecifications based on the OpenAPI. But whi
le convenience of use has been the\nfocus\, semantics has been largely unh
eeded. A Linked Data agenda has not\nbeen pursued.\n\nHowever\, the OpenAP
I opens the door to an informal coupling of OGC services with\nthe Semanti
c Web\, considering the possibility of adopting JSON-LD as\nsyntax to OGC
API responses. The introduction of a semantic layer to digital\nenvironmen
tal data shared through state-of-the-art OGC APIs is becoming a\nreality\,
with great benefits to researchers using or sharing data.\n\nThis communi
cation lays down a simple SDI set up to serve semantic environmental\ndata
through a SensorThings API created with the `glrc` software. A use case
is\npresented with soil data services compliant with the GloSIS web ontolo
gy.\n\nSensorThings API:\n\nSensorThings API is an OGC standard specifying
a unified framework to\ninterconnect Internet of Things resources over th
e Web [@liang2016ogc].\nSensorThings API aims to address both the semantic
\, as well as syntactic\,\ninteroperability. It follows ReST principles [@
fielding2002principled]\,\npromotes data encoding with JSON\, the OASIS OD
ata protocol\n[@chappell2011introducing] and URL conventions. \n\nThe Sens
orThings API is underpinned on a domain model aligned with the ISO/OGC\nst
andard Observations & Measurements (O&M) [@Cox2011]\, targeted at the\nint
erchange of observation data of natural phenomena. O&M puts forth the\ncon
cept of `Observation` has an action performed on a `Feature of Interest`\n
with the goal of measuring a certain `Property` through a specific `Proced
ure`.\nSensorThings API mirrors these concepts with `Observation`\, `Thing
`\,\n`ObservedProperty` and `Sensor`. This character makes of SensorThings
API a\nvehicle for the interoperability of heterogeneous sources of envir
onmental\ndata.\n\n\n`glrc`:\n\n`grlc` (pronounced "garlic") is a lightwei
ght server that translates SPARQL\nqueries into Linked Data web APIs [@mer
ono2016grlc] compliant with the OpenAPI\nspecification. Its purpose is to
enable universal access to Linked\nData sources through modern web-based m
echanisms\, dispensing the use of the\nSPARQL query language. While losing
the flexibility and federative capacities\nof SPARQL\, web APIs present d
evelopers with an approachable interface that can\nbe used for the automat
ic generation of source code.\n\n\nA `glrc` API is constructed from a SPAR
QL query to which a meta-data section is\nprepended. This section is decla
red with a simplified YAML syntax\, within a\nSPARQL comment block\, so th
e query remains valid SPARQL. The meta-data provide\nbasic information for
the API set up and most importantly\, the SPARQL end-point\non which to a
pply the query. The listing shows an example. \n\n```\n#+ endpoint: http:/
/dbpedia.org/sparql\n\nPREFIX dbo: \nPREFIX
dbr: \nPREFIX rdfs: \nPREFIX rdf:
\n\nSELECT ?band_label { \n ?band rdf:type dbo:Band \;\n dbo:g
enre dbr:Hard_Rock \;\n rdfs:label ?band_label .\n} ORDER BY ?ban
d_label\n```\n\nA special SPARQL variable formulation is used to map into
API parameters. By\nadding an underscore (`_`) between the question mark a
nd the variable name\,\n`glrc` is instructed to create a new API parameter
. A prefix separated again\nwith an underscore informs `glrc` of the param
eter type. The `?band_label`\nvariable in [Listing @lst:1] can be expanded
to `?_band_label_iri` to create a\nnew API parameter of the type IRI.\n\n
\nUse case: GloSIS: \n\nThe Global Soil Partnership (GSP) is a network of
stakeholders in the soil\ndomain established by members of the United Nati
ons Food and Agriculture\nOrganisation (FAO). Its broad goals are to raise
awareness to the importance of\nsoils and to promote good practices in la
nd management towards a sustainable\nagriculture. \n\nAcknowledging diffic
ulties in exchanging harmonised soil data as an important\nobstacle to its
goals\, the GSP launched in 2019 an international consultancy to\nassess
the state-of-the-art and propose a path towards a Global Soil Information\
nSystem (GloSIS) based on a unified exchange. A domain model resulted\, ba
sed\non the ISO 28258 standard for soil quality [@SchleidtReznik2020]\, au
gmented with\ncode-lists compiled from the FAO Guidelines for Soil Descrip
tion [@Jahn2006].\nThis domain model was then transformed to a Web Ontolog
y\, relying on the Sensor\,\nObservation\, Sample\, and Actuator ontology
(SOSA) [@Janowicz2019]\, and other\nSemantic Web standards such as GeoSPAR
QL\, QUTD and SKOS. The GloSIS web ontology\nhas been successfully demonst
rated as a vehicle to exchange soil information as\nLinked Data [@GloSIS].
\n\nA prototype API for the GloSIS ontology\, formulated in compliance wi
th the\nSensorThings API specification\, will be presented in this communi
cation. It\ndemonstrates how the same set of SPARQL queries can be used to
query through a\nReST API any end-point available over the internet\, sha
ring linked soil data in\naccordance with the GloSIS ontology. Thus provid
ing a clear step towards the\nfederated and harmonised system envisioned b
y the GSP.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:The template for a Semantic SensorThings API with the GloSIS use ca
se - Luís M. de Sousa
URL:http://talks.osgeo.org/foss4g-2023/talk/D38YER/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-78EKDS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T153000
DESCRIPTION:At Bellingcat\, a non-profit investigative organization in the
Netherlands\, we research war crimes\, find tiger smugglers\, monitor envi
ronmental degradation and track extremist hate. To do this\, we use "open
sources"\, including public databases\, social media posts\, and a wide ra
nge of geospatial data and tools. The use of these new online sources has
dramatically changed investigative journalism and humanitarian accountabil
ity research in the past five years\, and there remains tremendous potenti
al for further development\, especially in the geospatial realm.\n\nIn thi
s talk\, Bellingcat data scientist Logan Williams will present case studie
s from our research to illustrate how invaluable open source geospatial to
ols and data are for "open source" investigative research. Some of the mos
t useful tools for investigators are designed for very different purposes\
, from academic meterology to outdoor recreation. Additionally\, some of B
ellingcat's own FOSS geospatial tools\, based on Open Street Map and Coper
nicus satellite data\, will be showcased. Finally\, the talk will discuss
opportunities for deepening the connections between the open source geospa
tial community and the open source investigation community.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Investigating war crimes\, animal trafficking\, and more with open
source geospatial data - Logan Williams
URL:http://talks.osgeo.org/foss4g-2023/talk/78EKDS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-T9CZTQ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T150500
DESCRIPTION:The world's oceans are being affected by human activities and s
trong climate change pressures. Mapping and monitoring marine ecosystems i
mply several challenges for data collection and processing: water depth\,
restricted access to locations\, instrumentation costs and weather availab
ility for sampling. Nowadays\, artificial intelligence (AI) and GIS open s
ource software could be combined in new kinds of workflows\, to generate\,
for instance\, marine habitat maps from deep learning models predictions.
However\, one of the major issues for geoAI consists in tailoring usual A
I workflow to better deal with spatial data formats used to manage both ve
ctor annotation and large georeferenced raster images (e.g. drone or satel
lite images). A critical goal consists in enabling computer vision models
training directly with spatial annotations (Touya et al.\, 2019\, Courtial
et al.\, 2022) as well as delivering model predictions through spatial da
ta formats in order to automate the production of marine maps from raster
images. \nIn this paper\, we describe and share the code of a generic meth
od to annotate and predict objects within georeferenced images. This has b
een achieved by setting up a workflow which relies on the following proces
s steps: (i) spatial annotation of raster images by editing vector data di
rectly within a GIS\, (ii) training of deep learning models (CNN) by split
ting large raster images (orthophotos\, satellite images) and keeping rast
er (images) and vector (annotation) quality unchanged\, (iii) model predic
tions delivered in spatial vector formats. The main technical challenge in
the first step is to translate standard spatial vector data formats (e.g.
GeoJSON or shapefiles) in standard data formats for AI (e.g. COCO json fo
rmat which is a widely used standard for computer vision annotations\, esp
ecially in the object detection and instance segmentation tasks) so that G
IS can be used to annotate raster images with spatial polygons (semantic s
egmentation). The core process of the workflow is achieved in the second s
tep since the large size of raster images (e.g. drone orthophoto or satell
ite images) does not allow their direct use into a deep learning model wit
hout preprocessing. Indeed\, AI models for computer vision are usually tra
ined with much smaller images (most of the time not georeferenced) and do
not provide spatialized predictions (Touya et al.\, 2019). To train the mo
dels with geospatial data\, both wide geospatial raster data and related v
ector annotation data have thus to be split into a large number of raster
tiles (for instance\, 500 x 500 pixels) along with smaller vector files sh
aring the exact same boundaries as the raster tiles (converted in GeoJSON
files). By doing so\, we successfully trained AI models by using spatial d
ata formats for both raster and vector data. The last step of the workflow
consists in translating the predictions of the models as geospatial vecto
r polygons either on small tiles or large images. Finally\, different stat
e-of-art models\, already pre-trained on millions of images\, have been tu
ned thanks to the transfer learning strategy to create a new deep learning
model trained on tiled raster images and matching vector annotations. \nW
e will present and discuss the results of this generic framework which is
currently tested for three different applications related to marine ecosys
tem monitoring dealing with different geographic scales: orthomosaics made
of underwater or aerial drone images (for coral reef habitats mapping) an
d satellite images (for fishing vessels recognition). However\, this metho
d remains valid beyond the marine domain. The first use case was done with
underwater orthomosaics of coral reef made with a photogrammetry model an
d annotated with masks. This dataset was composed of 3 different sites of
orthomosaic acquisition. The second use case was on the recognition of spe
cies and habitat from geolocated underwater photos collected in different
Indian Ocean lagoons. The last implementation of this method was done usin
g satellite images of fishing harbors in Pakistan where vessels were label
ed with bounding boxes. For the three use cases\, model metrics are curre
ntly weak compared to similar computer vision tasks in the terrestrial dom
ain but will be improved by using better training datasets in the coming y
ears. Nevertheless\, the technical workflow which manages spatialized pred
ictions has been validated and already provides results which proves that
AI-assisted mapping will value different types of marine images. Special
attention is paid to large objects that can be spread over several tiles w
hen splitting the raster. In this case\, the model can indeed make errors
by predicting different classes for the parts of the same object. Thus\, a
decision rule must make it possible to choose the most probable class amo
ng the different classes predicted by the model to designate the whole obj
ect. The spatialization of the results of the model can then be decisive f
or reducing the misclassified objects.\n\nThe code is implemented with fre
e and open source software for geospatial and AI. The whole framework reli
es on Python libraries for both geospatial processing and AI (e.g. PyTorch
) and will be shared on GitHub and assigned a DOI on Zenodo\, along with s
ample data. Moreover\, a QGIS plugin is under development in order to faci
litate the use of pre-trained deep learning models to automate the product
ion of maps whether on underwater orthomosaics\, simple georeferenced phot
os or satellite images.\n\nBeyond the optimization of model scores\, one o
f the major perspectives of this work is to improve and ease AI-assisted m
apping\, as well as to include spatial information as input variables into
a multi-channel deep learning model to make the most from spatial imagery
(Yang et Tang\, 2021\, Janowicz et al\, 2020).
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:GeoAI for marine ecosystem monitoring: a complete workflow to gener
ate maps from AI model predictions - Justine Talpaert
URL:http://talks.osgeo.org/foss4g-2023/talk/T9CZTQ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-JNJBB3@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T153000
DESCRIPTION:Welcome to GeoNetwork and FOSS4G! GeoNetwork is a leading open-
source web catalog for keeping track of the spatial information.\n\nThis i
s an orientation session\, so if you are new to foss4g we can help explain
how everything fits together\, and how the pieces of the puzzle form a wh
ole. If you are migrating from ESRI environment this is a critical talk to
attend as open source technology is often presented in isolation.\n\n\nJo
dy is an experienced open source developer\, digging how this technology w
orks. Jonna is part of the QGIS community looking how to successfully use
GeoNetwork.\n\nThis presentation shares our findings and experience with y
ou\, and touches on what makes GeoNetwork succeed:\n\n* We look at what Ge
oNetwork is for\, the business challenge it is faced with\, and the amazin
g technical approach taken by the technology.\n* We will demo the the publ
ishing workflow to see what is required\, and look at how harvesting can j
ump start your catalog contents \n* We peek under the hood at how the edit
or works\, and discover the central super-power of GeoNetwork\n* Look at e
xamples of how GeoNetwork has been extended by organizations to see what i
s possible with this technology\n\nGeoNetwork is an established technology
- recognized as an OSGeo project and member of the foss4g community for o
ver a decade. We would love to welcome you to the conference and share wha
t this project has to offer.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:GeoNetwork Orientation and Demo - Jody Garnett\, Jonna Bosch
URL:http://talks.osgeo.org/foss4g-2023/talk/JNJBB3/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZEVKTG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T153000
DESCRIPTION:Securing a modern API in an effective way is critical to preven
t unauthorized access and ensure the privacy and integrity of data. In gen
eral\, there are three common mechanisms that can be used for API security
: API keys\, OAuth2/OpenID Connect\, and JSON Web Tokens (JWT). Each of th
ese mechanisms provides a different level of security and flexibility\, de
pending on the requirements of the API. Modern OGC APIs are agnostic and r
ely completely on the adoption of OpenAPI security schemes so the implemen
ters can use the mechanism that perfectly fits with their requirements. \n
fastgeoapi is a new open-source tool designed to be an authentication and
authorization layer on top of a vanilla pygeoapi that offers out-of-the-bo
x a secured infrastructure easily pluggable and configurable through the a
standard OpenID Connect protocol. \nThis talk aims to describe the recipe
to configure and protect a vanilla pygeoapi with Keycloak and Open Policy
Agent in order to publish secured OGC APIs in a standard manner.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:How to secure pygeoapi and streamline protected OGC APIs - Francesc
o Bartoli\, Antonio Cerciello
URL:http://talks.osgeo.org/foss4g-2023/talk/ZEVKTG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GYWNBH@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T153000
DESCRIPTION:This presentation will introduce the attendees to those which a
re GeoNode's current capabilities and to some practical use cases of parti
cular interest in order to also highlight the possibility of customization
and integration. We will provide a summary of new features added to GeoNo
de in the last release together with a glimpse of what we have planned for
next year and beyond\, straight from the core developers.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:State of GeoNode - Alessio Fabiani\, Giovanni Allegri
URL:http://talks.osgeo.org/foss4g-2023/talk/GYWNBH/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PDHANZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T153000
DESCRIPTION:The public administration of the Swiss canton Aargau chose to u
se OSS for the publication of all open WMS\, using GeoServer-Cloud and Pos
tgreSQL. Meanwhile\, the decentral offices\, which gather geographical dat
a and style this data are used to using proprietary software for this purp
ose. The strategy chosen was to provide a soft transition to OSS\, by prov
iding automated conversion processes based on a new FOSS project and by im
proving existing OSS with regards to styling conversions towards SLD.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:A Soft Transition to FOSS in a Decentral Administration - Thomas Ma
rti\, J. Wolfgang Kaltz
URL:http://talks.osgeo.org/foss4g-2023/talk/PDHANZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ND8SYJ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T150500
DESCRIPTION:Do you get regular data-drops from suppliers\, and struggle wit
h viewing changes between releases and keeping everything synchronised? In
this talk we'll explain how from both a consumer and a publisher point of
view you can use Kart to make your life easier.\n\n—\n\nWe’re drownin
g in data\, but the geospatial world lags badly behind in versioning tools
compared to our software counterparts. Kart (https://kartproject.org) is
solving this with a practical open tool for versioning datasets\, enabling
you to work more efficiently and collaborate better.\n\nKart allows you t
o quickly and easily manage history\, branches\, data schemas\, and synchr
onisation for large & small datasets between different working copy format
s\, operating systems\, and software ecosystems.\n\nModern version control
unlocks efficient collaboration\, both within teams and across organisati
ons meaning everyone stays on the same page\, you can review and trace cha
nges easily: ultimately using your time more efficiently.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Synchronising data updates with Kart version control - Robert Coup
URL:http://talks.osgeo.org/foss4g-2023/talk/ND8SYJ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RMSK39@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T153000
DESCRIPTION:Following the work we did with TiTiler (a python module which i
s designed to create Raster services)\, we decided to develop the same kin
d of project but for Vector. Using Postgres/PostGIS as datasource and Fast
API/Pydantic for the web framework\, TiPG is a lightweight application whi
ch user can include into their own FastAPI application and easily customiz
ed. \n\nDuring this session I'll go over the design principle of the TiPg
python module and also show some of its great features.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:TiPg: a Simple and Fast OGC Features and Tiles API for PostGIS. - V
incent Sarago
URL:http://talks.osgeo.org/foss4g-2023/talk/RMSK39/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-N9DGTE@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150000
DTEND;TZID=Europe/Tirane:20230628T150500
DESCRIPTION:This talk will describe the usage of Jason-3 Altimeter data\, w
hich records the topographic height of the surface of the earth every ~10
days\, to help measure the changes in water level of reservoirs across the
globe. The use of NASA Common Metadata Repository (CMR) API to download a
nd subset is described along with navigating the maze of various Jason-3 L
evel-2 Products depending on the use-case. \nThis talk introduces to this
open dataset and various other altimetry missions\, to allow for multi-mis
sion monitoring of reservoirs of the world. It further uses Free and Open
Source Software (CMR Specification\, Xarray) to pre-process the data for u
se.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Measuring Water Level Changes in Reservoir using Jason-3 Altimetry
Mission - Aman Bagrecha
URL:http://talks.osgeo.org/foss4g-2023/talk/N9DGTE/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-D7QVLV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150500
DTEND;TZID=Europe/Tirane:20230628T151000
DESCRIPTION:[Background and Purpose]\nThere are currently more than 7.5 mil
lion workers worldwide working in the field of fire\, medical\, and variou
s emergency services with a total budget exceeding 400 billion euros. Addi
tionally\, approximately 15 billion euros are spent on equipment and other
needs.\nWater pollution caused by a downpour and climate change have a fa
tal impact on our health and the number of waterborne diseases continues t
o increase domestically and internationally. Therefore\, the significance
of technology which properly responds to various disasters caused by the c
limate crisis is increasing. Technologies regarding natural disasters have
been widely developed\; however\, disaster response systems related to me
dical and biological emergencies are lacking. Many technologies for natura
l disasters have been developed\, but there is no technology development a
nd response system platform related to biological and medical risks\, whic
h are considered social disasters. \n \nFurthermore\, we aim to develop ra
pid and accurate pathogen detection technology which contains situational
awareness\, control/response methods\, risk assessment\, and epidemiologic
al investigation methods. Eventually\, by combining all these methods\, we
want to establish a user-centered GIS platform. \n\n[Methods]\nA decision
support system that manages pathogen contamination was developed by using
information obtained from sensors and fields. Moreover\, risk assessment
and epidemiological investigation technology which was developed through a
rtificial intelligence and big data were included. The following three tec
hnologies were applied to analyze contaminated areas. \n\nFirst\, it provi
des a preview of data taken by satellites and collects images of aquatic r
egions to analyze and inform the pollution degree. Moreover\, the turbidit
y of the water is provided from the data of aquatic regions which are cons
tantly being filmed. Lastly\, it also builds a water quality monitoring sy
stem based on data analyzed from water samples that are acquired from dron
es. \n\nThese images were taken from regions that humans cannot easily acc
ess. The technology provides both the spatial analysis result and images t
o users. Data and photos on social media are also analyzed to provide the
severity of water pollution along with the specific spatial locations. To
effectively provide and manage information on the platform\, the system co
nsists of seven layers: source management\, data collection\, interoperabi
lity\, data harmonization\, data application\, data process\, and security
. All components in the data collection\, interoperability\, data harmoniz
ation\, and security layers provide geographic information and statistics
for users. \n\n\n\n[Results]\nConsidering the functions of the system\, th
e following platform can be applied in three fields: "Detection of pathoge
ns and water pollution/situational response/post-investigation"\, "Infecti
on management and decision support system " and "Protection and management
of the first responder".\n\nTwo test locations were selected and the pilo
t case study was conducted in each location.\n\nLimassol Pilot Case Study\
n- An earthquake near Limassol caused flash floods and landslides\, pollut
ing the Kouris Dam which is a primary reservoir in Limassol.\n \n- The wat
er pollution over time can be checked by satellite images analyzed through
PathoSAT. The turbidity and temperature of water detected by PathoSENSE a
nd the results of satellite image analysis can be checked on the PathoGIS
platform.\n\n- The user can check the areas heavily affected by flood and
the magnitude of the tide is visualized on the PathoGIS data panel through
graphs.\n\n- A warning alert appears when the pollution level exceeds the
threshold and the user can check. If victims report the location of pollu
ted areas on Twitter\, it can be checked through PathoTweet.\n\nKorean Pil
ot Youth Case Demonstration\nA person in close contact with ASF wild pigs
visited a farm near Soyang Dam and all pigs on the farm had to be dislocat
ed due to mass infection. Many positive ASF cases were reported near the S
oyang River inevitably.\n\n- Due to the unusually high precipitation in su
mmer\, the Soyang River Dam overflowed and caused leaked leachate to flow
into the Soyang River Dam.\n\n- PathoSAT satellite images can be used to i
dentify the boundaries of areas that can be potentially damaged by floodin
g. The time series visualization shows that water pollution is more severe
near the location of ASF-positive cases.\n\n-Since the government needs t
o respond to the rapidly increasing number of ASF cases\, the results of A
SF case analysis can be checked using the analysis application. Using such
data to prevent African swine fever from spreading south\, analysts can d
etermine the optimal distance from SLL (Southern Limit Line)\, CLL (Civil
Defense Limit Line)\, primary fence\, or the need for additional fence ins
tallation.\n\n- As the number of ASF-positive cases increases\, pollution
in tap water can be easily found in Seoul since a large portion of water o
riginates from Soyanggang Dam.\n\n- The PathoSENSE turbidity sensor notifi
es the current situation regarding water pollution. If the turbidity of ta
p water increases\, Twitter reports on health problems also increase in Se
oul simultaneously.\n\n\n[Conclusion]\nA platform that contains a database
related to the spread of pathogens and provides AI-based information rega
rding the dangers of the situation will certainly help in responding to in
fectious diseases. \n\nIt will be able to strengthen its ability to respo
nd to infectious diseases and disasters by using it as a tool to improve t
he capability of the first responder and reduce the time required to detec
t and respond to the situation.\n\nIn particular\, there will be an effect
of reducing industrial accidents by improving the ability to respond to u
nidentified risk situations that are likely to be encountered by first-tim
e field responders.\n\nBy improving the ability to respond to unidentified
situations\, the number of industrial accidents will likely decrease. Sho
rtly\, when database expansion and the cost of maintenance becomes stable\
, in-depth data analysis of epidemiologic big data will be possible using
pattern recognition and deep learning models.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:GIS-based intelligent decision making support system for the disast
er response of infectious disease - MIN YOUNG LEE
URL:http://talks.osgeo.org/foss4g-2023/talk/D7QVLV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-CL9XDK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150500
DTEND;TZID=Europe/Tirane:20230628T151000
DESCRIPTION:Recently\, [sveltekit](https://kit.svelte.dev/) is becoming a m
ore popular framework for developing web application. It has been released
as v1.0.0 last December. However\, there are still not many use cases of
developing maplibre applications in sveltekit compared to other frameworks
like react. The author is involved in developing maplibre application wit
h sveltekit in United Nations Development Programme ([geohub](https://gith
ub.com/UNDP-Data/geohub))\, and also developing sveltekit based Web-GIS ap
plications for water asset management at Eastern African countries ([water
gis](https://github.com/watergis)). Hence\, several useful maplibre boiler
plate and components were developed in sveltekit during those projects' wo
rk. [watergis/sveltekit-maplibre-boilerplate](https://github.com/watergis/
sveltekit-maplibre-boilerplate) is a template which can start developing m
aplibre application in sveltekit with minimuum source code. Furthermore\,
[watergis/svelte-maplibre-components](https://github.com/watergis/svelte-
maplibre-components) consists of various useful maplibre components to add
more functionality easily to your web application (all components are doc
umented [here](https://svelte-maplibre.water-gis.com/)). For instance\, th
is component library provides you features of exporting maps\, adding lege
nds\, styling maps\, sharing maps\, measuring distance and integrating wit
h Valhalla api\, etc. In this talk\, these maplibre boilerplate and compon
ents will be briefly introduced.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Development of maplibre applications in sveltekit - Jin Igarashi
URL:http://talks.osgeo.org/foss4g-2023/talk/CL9XDK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZAMYEB@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T150500
DTEND;TZID=Europe/Tirane:20230628T151000
DESCRIPTION:Maybe you've heard of Kart\, the great new geodata versioning t
ool from the team at Koordinates? But did you know that Kart also has a QG
IS plugin so you can do real data versioning without needing to leave QGIS
?\n\nIn just 5 minutes we'll demonstrate how to import data into a new Kar
t repository\, make and review some changes\, merge a branch\, and push ev
erything to a remote server. All from QGIS!\n\n—\n\nWe’re drowning in
data\, but the geospatial world lags badly behind in versioning tools comp
ared to our software counterparts. Kart (https://kartproject.org) is solvi
ng this with a practical open tool for versioning datasets\, enabling you
to work more efficiently and collaborate better.\n\nKart allows you to qui
ckly and easily manage history\, branches\, data schemas\, and synchronisa
tion for large & small datasets between different working copy formats\, o
perating systems\, and software ecosystems.\n\nModern version control unlo
cks efficient collaboration\, both within teams and across organisations m
eaning everyone stays on the same page\, you can review and trace changes
easily: ultimately using your time more efficiently.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:QGIS Data Versioning with Kart - Robert Coup
URL:http://talks.osgeo.org/foss4g-2023/talk/ZAMYEB/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QUBWB8@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T151000
DTEND;TZID=Europe/Tirane:20230628T151500
DESCRIPTION:Geospatial information from satellites is increasingly being us
ed by decision-makers and scientists alike. However\, there are two fundam
ental issues with this kind of data and related handling technologies. Fir
stly\, data processing typically requires long time and a-priori expert kn
owledge compared to traditional data sources. Second\, integrating satelli
te data into processing pipelines can be expensive in terms of software an
d application development efforts. The OpenDataCube (ODC) was created to h
elp users solve these issues. Although ODC offers an alternative to being
used as a data management application\, its deployment is typically challe
nging for inexperienced users. Therefore\, the primary purpose of this wor
k is to provide potential ODC users with a ready-to-use\, portable instanc
e of this software.\nThe software is produced and published in a Docker co
ntainer. In comparison to the traditional installation and configuration o
f the ODC\, the tool proposed here provides an environment where the ODC d
atabase is already set up. It helps to avoid occasional conflicts that are
common in SQL and Python installations. Even though other ODC implementat
ions are available as a Docker container\, the proposed solution has some
advantages. Specifically\, Python geospatial libraries are integrated in t
he container to support data manipulation. While available ODC instances a
re designed to process satellite images only (mainly Sentinel and Landsat
data)\, the tool contains scripts to automatically adapt and ingest non-sa
tellite data (e.g. raw ground-sensor network data\, land cover/soil maps\,
etc.) by creating also metadata files when they are missing. The proposed
solution makes available processing pipelines to re-grid\, georeference a
nd import datasets into the ODC. Both scripts and pipelines can be used th
rough Jupyter notebook interfaces\, which allow users also to perform expl
oratory analyses on the ingested data.\nThe source code is available at (h
ttps://github.com/gisgeolab/LCZ-ODC) and is released under a MIT license.
The software is being developed within the LCZ-ODC project (agreement n. 2
022-30-HH.0) funded by the Italian Space Agency (ASI) and aimed to identif
y Local Climate Zones within the Metropolitan City of Milan. Given the nat
ure of the datacube development\, this tool promotes Open Geospatial Conso
rtium (OGC) compliant data sharing. Ongoing work focuses on the developmen
t and integration of additional pre-processing scripts with the aim of sup
porting the ingestion of additional types of data as well as providing new
ready-to-use embedded processing functionalities.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:OpenDataCube Fast Deploy using Docker (Fast Cubing) - J. R. Cedeno
Jimenez
URL:http://talks.osgeo.org/foss4g-2023/talk/QUBWB8/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MUZU3B@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T151000
DTEND;TZID=Europe/Tirane:20230628T151500
DESCRIPTION:The recognition of spatial and temporal patterns in pandemic di
stribution plays a pivotal role in guiding policy approaches to its manage
ment\, containment and elimination.\nTo provide information about spatial
and temporal patterns of a phenomenon four steps are required: the collect
ion of data\, the organization and management of data\, data representatio
n as tables\, charts and maps\, and finally their analysis with geo-statis
tical tools (Trias-Llimós et al 2020).\nThe collection of pandemic data p
oses a challenge: on the one hand\, the highest spatial and temporal resol
ution is required to make the detection of patterns more effective (Carbal
lada et al. 2021)\, allowing the application of containment tools as local
as possible\, on the other hand it presents major privacy problems.\nFor
these reasons public COVID-19 datasets and maps are usually available at l
ow spatial and temporal resolutions (Franch-Pardo et al. 2020)\, because a
veraging over time and space automatically provides a layer of anonymizati
on by data aggregation.\nIn this research project\, a database has been bu
ilt and is continuously updated for the COVID-19 pandemic in the Trentino
region\, in the eastern Italian alps\, near the border between Italy and A
ustria.\nThe Province of Trento\, with a population of about 542\,000 inha
bitants\, represents the primary corridor for transporting people and prod
ucts between Italy\, Austria and Germany. The area has also an intense tou
rist development\, in particular for winter sports\, with the presence of
ski slopes\, ski lifts and hotels.\nThese two features have been an import
ant role in the diffusion of COVID-19 in the region because the movement o
f people\, both through the main communication routes and the movement of
tourists in the lateral valleys\, has been the main driver in the virus sp
read. Therefore\, the availability of a reliable database collecting COVID
-19 cases\, is fundamental to map the pandemic evolution (Mollalo et al. 2
020).\nAt the same time the status of autonomous region of the Provincia A
utonoma di Trento\, allows greater discretion in the organization of healt
h data\, their scientific use and their dissemination. In this context the
local government and the University of Trento\, in particular its the Geo
-cartographic Center (GeCo)\, have signed an Agreement for sharing COVID-1
9 data and their analysis (Gabellieri et al. 2021).\nThe resulting dataset
collects the official number of the infected\, clinically recovered\, dec
eased people\, and their age group. The dataset contains daily data at the
municipal level\, starting from the beginning of the COVID-19 epidemic in
March 2020 until the whole 2022.\nData anonymization has been carried out
by aggregating data on a weekly basis and by hiding data with small numbe
rs\, with the threshold set to 5.\nThe sole use of official data created b
y public agencies tasked with managing public health\, specifically the lo
cal Health Authority (Agenzia Provinciale per i Servizi Sanitari\, APSS)\,
ensures the validity of their production process and strict observance of
patient data confidentiality. rules\nA database management system and a W
ebGIS has been created using Free and Open Source Software.\nThe back end
of the system runs a database management system (DBMS)\, which manages the
data\, including the spatial components\, and a web server\, which provid
es access to the users.\nThe DBMS runs on MySQL\, a relational database ma
nagement system (RDBMS) available as Free Software under the GNU General P
ublic License. MySQL provides the capability of storing and processing geo
graphic data\, following the OpenGIS data model. A custom procedure has be
en created to update the dataset\, with the capability to import data from
suitably formatted spreadsheets. A roll back option is provided in case o
f failure of the import procedure. Data base management and update functio
nalities are available only to authenticated WebGIS administrators and acc
essible through a dedicated web page.\nThe main goals in the design and de
velopment of the WebGIS have been the ease of use and clarity of data pres
entation\, both on large screens and on mobile devices. This approach maxi
mizes the user performance while exploring the data\, by splitting the pro
cessing tasks and load between server and clients.\nThe system is compris
ed of a back end\, running on a server\, and a front end running in the us
er’s web browser.\nCartographic data include background maps from the Op
enStreetMap (OSM) project and a map of the municipalities boundaries for t
he Province of Trento\, which serves as a spatial basis for the dataset. T
abular data are linked to the respective geographic components using the u
nique municipal code field as key. OSM maps are available with the Open Da
tabase License\, while the municipalities boundaries have been provided by
the Provincia Autonoma di Trento under a CC0 1.0 Universal (CC0 1.0) Publ
ic Domain Dedication license.\nA virtual machine that houses both software
and data powers the system on the server side.\nThe client side uses the
Open Source Leaflet Javascript language libraries\, available under BSD 2-
Clause License\, with custom scripts\, which create the user interface and
render geographic data into maps. This approach ensures flexibility and
responsiveness on on desktop and mobile devices.\nThe exchange of the data
between the server and the client is performed using geojson tables\, cre
ated on the fly according to the user’s request. In a similar way\, the
data temporal variation graph is created by the js library\, which automat
ically reads the dates and times of the analyses\, extracts the relevant d
ata from the database and display the graph.\nAs long as they fit within t
he database structure\, the system automatically uses all of the accessibl
e data. To protect the privacy of the patients\, WebGIS users cannot acces
s the source data even though maps and graphs can be downloaded as picture
s.\nThe WebGIS is available at http://covid19mappa-trentino.geco.unitn.it/
geosmart/index.php\nGeo-statistical analysis aimed at the detection of spa
tial and temporal patters is underway.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Mapping COVID-19 epidemic data using FOSS. - Paolo Zatelli
URL:http://talks.osgeo.org/foss4g-2023/talk/MUZU3B/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-7E8KE7@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T151000
DTEND;TZID=Europe/Tirane:20230628T151500
DESCRIPTION:Static type hints according to [PEP 484](https://peps.python.or
g/pep-0484/) (and its extensions) have been a part of Python since version
3.5\, which came out in 2015. [Research from 2021](https://lp.jetbrains.c
om/python-developers-survey-2021/#stacked-chart-863) shows that 3 out of 4
Python developers already use optional type hinting at least sometimes in
their projects. Time is ripe for static type hints to enter the FOSS4G Py
thon world!\n\nA [GitHub issue on `fiona`'s issue tracker to add static ty
pe hints to the library](https://github.com/Toblerity/Fiona/issues/1125) r
ecently gained some traction. Currently\, it is [envisioned](https://githu
b.com/Toblerity/Fiona/issues/1125#issuecomment-1424553816) to create type
stubs for `fiona` 1.9 and possibly move the type hints into core `fiona` w
ith the future 2.0 version.\n\nThis talk will give an overview on the curr
ent status of the effort to add type hints to `fiona`. Furthermore it will
briefly discuss considerations and the reasoning behind design decisions
taken up until then. Contributions to the effort are very much welcome –
just take part in the [discussion on GitHub](https://github.com/Toblerity
/Fiona/issues/1125).
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Adding static type hints to fiona - Stefan Brand\, Fabian Schindler
-Strauss
URL:http://talks.osgeo.org/foss4g-2023/talk/7E8KE7/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XDXMDB@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T151500
DTEND;TZID=Europe/Tirane:20230628T152000
DESCRIPTION:How do you run an aid station in case of a disaster? Scenarios
are planned for each city\, but there are limitations in applying them to
actual aid station operations. In our presentation\, we will present a cas
e study on the development and simulation of a aid station management tool
using digital twin technology and share various visualization techniques
in a 3D city model environment. \n\nThe study site is Ulju-gun\, a county
of about 220\,000 people in southern South Korea\, with two nuclear power
plants operating within a few kilometers of each other. Moving people to s
helters to protect them in the event of a disaster such as a radioactive l
eak is very essential and crucial part of disaster management. \n\nThe aid
station management tool presented in this presentation leverages ground-t
ruth 3D modeling data of the shelter buildings that will be operational du
ring a disaster to provide facility placement and editing capabilities. Th
is allows relief tents to be automatically placed or edited based on the s
cenario. It also provides the ability to monitor the overall changes that
may occur at the shelter through a dashboard\, including real-time victim
status\, food\, beverage\, and medical support\, supply status\, shelter i
nformation\, and disaster situation information.\n\nThe Cesium platform is
used to service the data and the Three.js library is used to handle the v
iewing and placement of 3D model data in glTF format. Other open source im
plementations include React\, Turf.js\, Apache ECharts\, and GeoServer.\n\
nWe believe that the findings mentioned in this study provide a good examp
le of how 3D city model-based shelter operations and visualization techniq
ues can be applied to disaster preparedness systems to support effective d
ecision-making and resource allocation.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:3D City Model-based Aid Station Operation Visualization and Managem
ent using Cesium.js - Sanghee Shin
URL:http://talks.osgeo.org/foss4g-2023/talk/XDXMDB/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MXTDB7@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T151500
DTEND;TZID=Europe/Tirane:20230628T152000
DESCRIPTION:Because environmental impact assessment(EIA) process is a combi
nation of detailed fields that require a lot of expertise (e.g.\, noise\,
air pollution\, odor\, water pollution\, ecological environment\, living e
nvironment\, etc.)\, despite its long history\, the process is still compl
ex and slow\, and it is not easy to break away from the document/drawing-c
entered work process. Since the nature of the environment involves many ge
ographic/spatial context\, if it can be assisted with a spatio-temporal sy
stem\, it can be expected to show very high efficiency compared to the cur
rent process.\n\nTo verify the feasibility of such a system\, we adopted a
FOSS4G-based approach and developed a pilot system in this study. Specifi
cally\, we used GeoServer and Postgresql/PostGIS for handling and providin
g data spatially\, and Cesium for 3D geospatial based visualization. We fo
cused on the design and implementation of APIs to assemble the sub-process
es of EIA\, as well as the visualization and UI of the pilot system. \n\nT
his system demonstrates how the noise propagate during and after the const
ruction in an interactive way. We expect the system will increase the non-
expert stakeholder's understanding of noise propagation visually. \n\nThro
ugh this presentation\, we will discuss our findings implemented in a EIA
process centered on the noise\, from the first step of applying for approv
al from the civil/construction operator to the last step of deriving the f
inal evaluation opinion by the noise expert in charge\, and provide clues
to the future of Digital EIA. \n\nIn the future\, we believe that the expa
nsion to other EIA media and the smooth implementation of current legal an
d administrative tasks will make it a system that can be used in the field
.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Application of FOSS4G for improving the environmental impact assess
ment process - a noise case - Sanghee Shin
URL:http://talks.osgeo.org/foss4g-2023/talk/MXTDB7/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QUJQTQ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T151500
DTEND;TZID=Europe/Tirane:20230628T152000
DESCRIPTION:In May 2020\, NASA\, ESA\, and JAXA initiated a collaborative e
ffort aiming at the establishment of the COVID-19 Earth Observation Dashbo
ard and later in March 2021\, extended its scope to global environmental c
hange. Noting the increasing use of the joint Dashboard and the continuous
users' requests for more information\, NASA\, ESA\, and JAXA will continu
e through June 2024 to advance their joint work in the global understandin
g of the changing environment with human activities. This decision continu
es the collaboration on the analysis of three agencies' datasets and open
sharing of data\, indicators\, analytical tools\, and stories sustained by
our scientific knowledge and expertise\, to provide a precise\, objective
\, and comprehensive view of our planet as an easy-to-use resource for the
public\, scientists\, decision-makers\, and people around the world. The
dashboard provides an easy-to-use resource for all kinds of the public fro
m the scientist to the decision-maker\, including people not familiar with
satellites. Based on accurate remote sensing observations\, it showcases
examples of global environmental changes on 7 themes: Atmosphere\, Oceans\
, Biomass\, Cryosphere\, Agriculture\, Covid-19\, and Economy. The dashboa
rd offers a precise\, objective\, and factual view without any artifacts o
f our planet. You can explore countries and regions around the world to se
e how the indicators in specific locations changed over time.\n\nESA\, JAX
A\, and NASA will continue to enhance this dashboard as new data becomes a
vailable. This session explores this EO dashboard architecture\, function\
, examples of thematic content through storytelling\, and its utility amon
gst the broader EO and Data Science community. \n\nTo monitor COVID-19 env
ironmental and economic impacts from space through provision of related in
dicators to the general public and decision makers\, JAXA has developed an
d implemented earth observation (EO) dashboard jointly with ESA and NASA.
In parallel\, jointly developed EO dashboard\, to provide climate change a
nd earth science information to world wide users\, JAXA also develops and
operates one stop shopping portal site named “Earth-graphy” as JAXA's
website for all news\, articles\, images related to JAXA's Earth Observati
on activities. Recently\, to enhance JAXA’s “Earth-graphy” with inte
rconnect with EO Dashboard through API\, JAXA has developed the “JAXA Ea
rth API” service to provide a wide variety of JAXA Earth observation sat
ellite image data in an easy-to-use format and to promote the efficient an
d effective use of satellite data. \n\nFor earth observation satellite dat
a provision\, JAXA develops and operates G-Portal which is a portal system
allowing users to search (satellite/sensor/physical quantity)\, and downl
oad products acquired by JAXA's Earth observation satellite including ALOS
-2 ScanSAR data. With G-Portal standard product dissemination system\, JAX
A provides value added product services including Global Satellite Mapping
of Precipitation (GSMaP)\, Himawari Monitor\, JASMES\, etc. For example\,
GSMaP provides a global hourly rain rate with a 0.1 x 0.1 degree resoluti
on. JASMES provides the information on the current status and seasonal/int
erannual variability of climate forming physical quantities including sola
r radiation reaching the earth’s surface (photosynthetically available r
adiation)\, cloudiness\, snow and sea ice cover\, dryness of vegetation (w
ater stress trend)\, soil moisture\, wildfire\, precipitation\, land and s
ea surface\, etc. (https://kuroshio.eorc.jaxa.jp/JASMES/index.html)\n\nTo
provide easy access of JAXA’s earth observation data and information\, J
AXA developed JAXA Earth-graphy with API. The JAXA Earth API service consi
sts of three main components shown in Figure 1: an API (Python language ve
rsion\, popular in fields such as data science\, and a JavaScript language
version (under development) for browser applications)\, a database\, and
a web application. First one is “JAXA Earth Data Explorer” which is a
browser application that allows you to check various satellite data stored
in a database. Second one is “JAXA Earth API for Python” allows users
to acquire and use satellite data for any area\, without being aware of d
ifferences in satellite\, sensor type\, resolution\, etc. efficiently\, ef
fectively\, and freely The API also has an IF function with the free GIS s
oftware QGIS\, allowing for immediate acquisition and display of data. Fin
al one is “JAXA Earth Database” which contains 74 types of data includ
ing elevation\, surface temperature\, vegetation index\, precipitation\, a
nd land cover classification maps. The database contains data by cloud opt
imized GeoTIFF (COG) format and metadata by STAC format named “CEOS Anal
ysis Ready Data for Land (CARD4L)”. And also\, JAXA implement prototypi
ng system of OGC WMS/WMTS system as a frontend system of JASMES and Earth-
graphy to provide data and information to Trilateral cooperation EO dashbo
ard since 2022. \n\nThrough this WMS/WMTS and JAXA Earth API\, JAXA’s EO
dashboard is linked with jointly developed EO dashboard. Thus\, worldwide
users can access JAXA’s data and information through joint developed EO
dashboard. Furthermore\, JAXA also started to develop Japanese language v
ersion of UI for joint developed EO dashboard with increasing products and
information. This paper describes overview of JAXA’s EO dashboard syste
m development. Especially Japanese Advanced Land Observing Satellite-2 (AL
OS-2) L-band SAR data for forest monitoring.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:JAXA EARTH OBSERVATOIN DASHBOARD WITH COG AND WMS/WMTS - Shinichi S
obue
URL:http://talks.osgeo.org/foss4g-2023/talk/QUJQTQ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-P7D3SC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T152000
DTEND;TZID=Europe/Tirane:20230628T152500
DESCRIPTION:Travel time estimation is used for daily travel planning and in
many research fields such as geography\, urban planning\, transportation
engineering\, business management\, operational research\, economics\, hea
lthcare\, and more (Hu et al.\, 2020). In public health and medical servic
e accessibility studies it is often critical to know the travel time betwe
en patient locations and health services\, clinics\, or hospitals (Weiss e
t al.\, 2020). In support of a study aiming to characterize the quantity a
nd quality of pediatric hospital capacity in the U.S.\, we needed to calcu
late the driving time between U.S. ZIP code population centroids (n=35\,35
2) and pediatric hospitals\, (n=928) a total of over 32 million calculatio
ns. There currently exist numerous methods available for calculating trave
l time including (1) Web service APIs provided by big tech companies such
as Google\, Microsoft\, and Esri\, (2) Geographic Information System (GIS)
desktop software such as ArcGIS\, QGIS\, PostGIS\, etc\, and (3) Open sou
rce packages based on program languages such as OpenStreetMap NetworkX (OS
Mnx) (Boeing\, 2017) and Open Source Routing Machine (OSRM) (Huber & Rust\
, 2016). Each of these methods has its own advantages and disadvantages\,
and the choice of which method to use depends on the specific requirements
of the project. For our project\, we needed a low-cost\, accurate solutio
n with the ability to efficiently perform millions of calculations. Curren
tly\, no comparative analysis study evaluates or quantifies the existing m
ethods for performing travel time calculations at the national level\, and
there is no benchmark or guidance available for selecting the most approp
riate method.\n\nTo address this gap in knowledge and choose the best driv
e time estimator for our project we created a sample of 10\,000 ZIP/Hospit
al pairs covering 49 of the 50 U.S. states with variable drive times rangi
ng from a few minutes to over 4 hours. With this sample\, we calculated th
e drive time using the Google Map API\, Bing Map API\, Esri Routing Web Se
rvice\, ArcGIS Pro Desktop\, OSRM\, and OSmnx and performed a comparative
analysis of the results.\n\nFor the Google\, Bing\, and Esri web services
we used the Python requests package to submit requests and parse the resul
ts. Within ArcGIS Pro\, we manually used the Route functions to calculate
routes on a road network provided by Esri and stored locally. For OSMnx we
utilized Python to perform the street network analysis using input data f
rom OpenStreetMap. For OSRM we utilized C++ through the web API. OSRM prov
ides a demo server to enable testing the routing without loading the road
network data locally\, and we used this for calculating drive times for ou
r 10\,000 samples. For generating visualizations we used Networkx and Igra
h to display the shortest path of the drive time routing result\, and grap
hs of our comparative analysis.\n\nWhen comparing drive time estimations u
sing these 6 technologies we found: (1) There are very little differences
among Google\, Bing\, OSRM\, ESRI web service\, and ArcGIS Pro when the ro
ute drive time is less than roughly 50 minutes (2) For travel time estimat
ions of routes greater than 50 minutes the Google and Esri methods were ex
tremely close. The OSRM estimates produced travel times about 10% longer t
han other methods\, and Bing’s estimates were about 10% lower than Googl
e and ESRI. (3) Overall\, OSmnx estimates travel times lower than any othe
r method because it estimates the shortest distance using the maximum velo
city. In general\, the different methods employ different strategies for c
onsidering traffic conditions. When long-distance travel is estimated the
use of highways is required\, and each method employs specific parameters
to account for traffic and resulting travel speed. Because of the complexi
ty of modeling traffic conditions\, it is difficult to say which method pr
ovides the most accurate and realistic driving times without empirical dat
a being collected. Regarding cost\, the OSmnx and OSRM are both open-sourc
e\, while the other methods have a cost for API usage (Google\, Esri\, Bin
g) and desktop software (ArcGIS Pro). For processing efficiency\, Google\,
Esri and Bing were all efficient\, each able to process the dataset in ro
ughly one hour. We found the processing power of OSMnx was limited in the
size of the road network it could handle\, so we had to divide the ZIP/Hos
pital pairs into subsets by state\, and calculate them separately\, which
was a laborious process. We found OSRM to be the most efficient\, able to
handle 10\,000 requests in less than a minute. We ran OSRM in a high-perfo
rmance cluster computing environment. This process included one hour of se
tup to download the OpenStreetMap data for the entire U.S. onto the cluste
r. Then we used Python requests to calculate the drive times and parse the
result for analysis. The total processing time for the 32 million calcula
tions ended up being 12 minutes.\n\nUsing OSRM provided us with a low-cost
\, accurate\, efficient solution to calculating drive times between 32M or
igin/destination pairs. We feel our study provides valuable guidance on ca
lculating drive time in the United States\, offering a benchmark compariso
n model between 6 different methods. We encourage others to utilize the co
de produced for this project\; all of it is in the process of being publis
hed on GitHub as open-source. Our analysis was just for the U.S.\, and per
forming similar analyses in other countries will provide more insight into
how useful the different methods are globally. In summary\, this comparat
ive study allowed us to produce drive times in the most efficient manner i
n order to support the larger objective of characterizing the quantity and
quality of pediatric hospital capacity in the U.S.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:A Comparative Study of Methods for Drive Time Estimation on Big Geo
spatial Data: A Case Study in the U.S. - Xiaokang Fu\, Devika Kakkar
URL:http://talks.osgeo.org/foss4g-2023/talk/P7D3SC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-3R7JKS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T152500
DTEND;TZID=Europe/Tirane:20230628T153000
DESCRIPTION:The concept of 15-minute cities\, which aims to provide residen
ts with access to amenities and services within a 15-minute walk\, has gai
ned popularity in recent years [1]. In Korea\, there have been discussions
about supporting the planning of walkable neighborhoods based on Chrono-U
rbanism\, a concept that is the basis of the 15-minute city concept that r
esidents can receive services necessary for their daily lives in the same
place where they live. Planning support based on Chrono-Urbanism measures
the walkability of services for various age groups based on the distance t
o reach physical activity centers such as walking and bicycling from small
living area units\, and places necessary living infrastructure (urban ame
nities). The bottom-up planning approach that reflects the needs and livin
g conditions of citizens\, such as walking routines\, can generate plannin
g issues that reflect the needs of citizens through iterative alternative
generation and evaluation in support of planning decisions by learning the
surrounding environmental conditions using AI techniques.\nHowever\, to i
mplement this concept\, it is necessary to develop tools based on free and
open source technologies for spatial planning. Previous studies have deve
loped open source-based tools using Open Street Map (OSM) or open data of
each city and used them effectively for urban planning [2\,3]. In this stu
dy\, we aim to develop a tool that supports the measurement of walkability
and the distribution of urban amenities considering age groups as well as
walkability\, bicycle accessibility\, and public transportation accessibi
lity by utilizing free and open source software (FOSS4G) tools for spatial
information.\nFirst\, we design walkability\, including pedestrian walkab
ility\, bicycle accessibility\, and transit accessibility\, based on each
home-based or residence-based trip.\nTo measure the walkability of a city\
, we need to consider pedestrian-friendly urban infrastructure elements su
ch as sidewalks and crosswalks. When designing for measurement\, design a
walking network that provides information on the physical characteristics
of the road network and a database that contains the distribution of resid
ents by gender and age. By analyzing data based on the pedestrian network
for different age groups\, it is possible to determine the level of walkab
ility in different urban space conditions. Similarly\, the same data can b
e used to measure bicycle accessibility\, taking into account bike lanes\,
bike parking facilities\, and other factors. Access to public transportat
ion can be measured using data from transportation agencies\, including in
formation about the frequency and routes of public transportation.\n\nSeco
nd\, we design a tool to measure accessibility to urban amenities based on
Python spatial information and distribute the location of urban amenities
according to accessibility.\nWe develop a tool that integrates data such
as walkability\, bicycle accessibility\, and public transportation accessi
bility to determine the best locations for urban amenities. A network-base
d method of minimizing travel costs will be used to determine the location
s [4]. The tool will be developed using QGIS and the Python programming la
nguage. The tool is designed by considering various parameters such as res
ident and traveling population\, distance from existing amenities\, and ur
ban environment in various living areas. \nThird\, the tool is used to eva
luate local 15-minute cities.\nThe implemented tool is designed to be used
and evaluated by officials\, planners\, and researchers working on 15-min
ute cities. The tool can be used to identify areas that need more urban am
enities and to deploy existing amenities in ways that enhance walkability.
The tool can also be used to determine the feasibility of locating new fa
cilities such as parks\, community centers\, and other public spaces. In a
ddition\, the tool is designed to be customizable to meet the environmenta
l needs of different cities.\nThe development of a FOSS4G-based urban amen
ity distribution tool based on walkability measures can provide the follow
ing benefits. First\, it provides an age- and facility-related data-driven
approach to the placement of urban amenities\, ensuring that amenities ar
e located in areas that are easily accessible to citizens. Second\, it pro
vides a spatial structure that can promote the use of sustainable transpor
tation modes such as walking\, biking\, and public transit. Third\, it can
encourage more inclusive urban development by ensuring that amenities are
distributed in a more equitable manner. \nIn conclusion\, the development
of a FOSS4G-based urban amenity distribution tool can play an important r
ole in the realization of the concept of walkable livability\, a 15-minute
city concept in South Korea. This tool can measure and distribute urban a
menities based on walkability\, bicycle accessibility\, and public transpo
rtation accessibility\, providing a way to create healthier\, more equitab
le living areas. Implementing the tool to generate a range of alternatives
will allow planners to learn from the alternatives about desirable walkab
le urban amenity alternatives. For urban planners and practitioners\, open
-source tools make it easy to take data-driven action and learn and innova
te from what others have done. Transparency in the planning process allows
citizens to understand the planning process and engage with planners\, as
well as be part of the planning process.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Developing a FOSS4G based Walkable Living Area Planning Support Mod
ule to Assists the Korean 15-minute City - Junyoung CHOI
URL:http://talks.osgeo.org/foss4g-2023/talk/3R7JKS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MVYVGR@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:Mapillary is an open platform for street-level imagery and map
data that began in 2013. Since then around 1.8 billion images have been co
ntributed from around the world. Imagery has been contributed from horseba
ck in Kyrgyzstan\, boats in the canals of Amsterdam\, and bicycles on the
streets and trails of Sydney. As Mapillary approaches 2 billion images\, w
e’d like to summarize the latest features\, acknowledge some of the amaz
ing contributions\, and hint at some of the updates that are coming.\n\nSo
me of the things that we have been working on include:\n\nDesktop Uploader
improvements including support for videos and popular cameras.\nImproveme
nts to Mapillary Tools\, command line scripts for working with and uploadi
ng geotagged imagery and video.\nMobile app updates including multi-taskin
g\, redesigns\, multi-language support\, and upload improvements.\nCamera
Grant programs in the US and Europe\, providing 360º cameras for people i
nterested to map pedestrian infrastructure.\nIntegrations with Rapid Edito
r\, an AI powered OpenStreetMap editor which we will demo in more detail a
t a workshop.\nUpdated Help Pages to make capturing\, uploading\, and usin
g street-level imagery far easier.\n\nAfter walking through the latest Map
illary improvements\, we will take a look at case studies of organizations
contributing and using imagery. We’ll zoom in on an NGO\, a government
agency\, and a commercial entity\, each of which are using Mapillary in di
fferent ways.\n\nWe’ll finish our talk with an exploration of upcoming M
apillary features and projects. We encourage questions and suggestions in
the Q&A and hope for a productive conversation at the end as we walk toget
her towards 2 billion images.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Mapillary: The path to 2 billion images - Christopher Beddow\, Edoa
rdo Neerhut
URL:http://talks.osgeo.org/foss4g-2023/talk/MVYVGR/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-7MMQCK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:Knowledge sharing is increasingly being recognized as necessary
to address societal\, economic\, environmental\, and public health challe
nges. This often requires collaboration between federal\, local and tribal
governments along with the private sector\, nonprofit organizations and i
nstitutions of higher education. In order to achieve this\, there needs to
be a move away from data-centric to knowledge sharing architectures\, suc
h as a Geographic Knowledge Infrastructure (GKI) to support spatial knowle
dge-based systems and artificial intelligence efforts. Location and time a
re dimensions that bind information together. Data from multiple organizat
ions need to be properly contextualized in both space and time to support
geographically based planning\, decision making\, cooperation and coordina
tion.\n\nThe explosive uptake of ChatGPT seems to indicate that people wil
l increasingly be getting information and generating content using chatbot
s. Examples of AI-driven chatbot technology providing misleading\, harmful
\, biased\, or inaccurate information due to a lack of access to informati
on highlight the importance of making authoritative knowledge accessible\,
interoperable\, and usable for machine-to-machine readable interfaces tho
ugh GKIs to support AI efforts.\n\nSpatial knowledge graphs (SKG) are a us
eful paradigm for facilitating knowledge sharing and collaboration in a ma
chine-readable way. Collaboration involves building graphs with nodes and
relationships from different entities that represent a source of truth\, t
rusted geospatial information\, and analytical resources to derive new and
meaningful insights through knowledge inferencing by location or a networ
k of related locations.\n\nHowever\, due to a lack of standardization for
representing the same location and for managing dependencies between graph
s\, interoperability between independently developed SKGs that reference t
he same geographies is not automated. This results in a duplication of eff
ort across a geospatial ecosystem to build custom transformations and pipe
lines to ensure references to geographic data from different sources are h
armonized within a graph for the correct version and time period and that
these references are properly maintained over time. \n\nWhat is needed is
a way to manage graph dependencies\, or linking\, between organizations in
a more automated manner. References to geographic features (i.e.\, geo-ob
jects) from graphs that are curated by external (and ideally authoritative
) entities should come from formally published versions with the time peri
od for which they are valid (i.e.\, the period of validity). As newer vers
ions of SKGs are published for different periods of validity\, updating de
pendencies between graphs should be controlled and automated. \n\nIt turns
out that an approach for a similar kind of dependency management has been
in mainstream use for decades in a related field. Software developers lon
g ago abandoned the practice of manually managing code artifacts on filesy
stems and manually merging changes to code. Rather\, they use a combinatio
n of namespacing for identity and reference management along with formally
managing versioned releases in a code repository. Although there are nua
nced differences between software code versioning and dependency managemen
t between SKGs\, there are enough similarities to indicate distinct advant
ages to treating geospatial data as code for the purpose of managing graph
dependencies to automate knowledge sharing. \n\nWe have been developing s
uch an approach since 2018 with the core principles implemented in an open
-source application called GeoPrism Registry (GPR)\, which utilizes spatia
l knowledge graphs to provide a single source of truth for managing geogra
phic data over time across multiple organizations and information systems.
It is used to host\, manage\, regularly update hierarchies and geospatial
data through time for geographic objects. GPR is being used by the minist
ry of health in the country of Laos to manage interlinked dependencies bet
ween healthcare related geo-objects and geopolitical entities. More recent
ly it has been installed in Mozambique for use by the national statistics
division (ADE) to meet their National Spatial Data Infrastructure (NSDI) o
bjectives to facilitate cross-sectoral information collaboration using com
mon geographies for the correct periods of time.\n\nCurrently\, GPR is bei
ng considered by the US Federal Geospatial Data Committee (FGDC) to help b
uild a GKI for GeoPlatform.gov\, which is mandated by the United States Ge
ospatial Data Act of 2018 (GDA) to improve data sharing and cooperation be
tween public and private entities to promote the public good in a number o
f sectors. US federal agencies are developing spatial knowledge graphs\, b
ut they are not interoperable using machine-to-machine readable interfaces
with those from other agencies. We led a requirements\, design\, and scop
ing effort that revealed a GKI architecture for GeoPlatform\, will at a mi
nimum\, require the following machine-readable characteristics to enable k
nowledge interoperability using SKGs at scale.\n\nAuthoritative:\nCopies o
f data always remain authoritative by preserving the identity of its sourc
e.\n\nTemporal:\nThe period of validity should be specified in metadata as
a moment in time (such as a date)\, a frequency (e.g.\, annually or quart
erly)\, or an interval (year 2000 to 2005) in which data have not changed
relative to when they were published.\n\nDistributed:\nUtilize the Data Me
sh architecture pattern by giving organizations the ability to publish loc
ally hosted graph assets. Other organizations can build fit-for-purpose gr
aphs by pulling and merging only what is needed from authoritative sources
. \n\nTransitive:\nChanges made to graphs should automatically propagate t
o the graphs that reference them\, even if the dependency occurs via multi
ple layers of indirection (i.e.\, a dependency of a dependency). \n\nVersi
oned:\nMetadata should capture the published version.\n\nInteroperable:\nT
he semantic identity of data types\, attributes\, and relationships should
be defined such that equivalency and identity can be established. This wo
uld include the use of namespaces\, controlled vocabularies\, taxonomies\,
ontologies\, geo-object types\, and graph edge types.\n\nIn this paper we
will present the approach for implementing these GKI requirements and Geo
Platform.gov interoperability use cases using open-source software. This w
ill include the Common Geo-Registry concept for managing the authoritative
and interoperable requirements\, the Data Mesh framework for making the s
olution distributed and transitive\, and the spatial knowledge graph repos
itory for managing temporal\, and versioned dependencies. We will also pre
sent the metamodel architecture used by GeoPrism Registry for managing gra
ph dependencies\, facilitating interoperability\, publishing\, and how it
currently is being used as a graph repository.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Enabling Knowledge Sharing By Managing Dependencies and Interoperab
ility Between Interlinked Spatial Knowledge Graphs - Nathan McEachen
URL:http://talks.osgeo.org/foss4g-2023/talk/7MMQCK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-BUZAGV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:This project was a pilot of a larger upcoming project\, where t
he aim is to produce a national interoperable data model for every valid z
oning and city plan in Finland. The project is part of the development of
the Finnish Environment Institute’s Built Environment Information System
and the harmonization of national land use planning information. \n\nThe
aim of this presentation is to present the overall workflow of the project
and the transition from proprietary data towards an open source national
database with common spatial and descriptive information. Currently the da
ta used in municipal decision making processes in Finland consists of prop
rietary data that is lacking spatial information or is outdated.\n\nThe tr
ansformation of the zoning and city plans from two different data provider
s created a lot of topological errors and unmatched geometries. QGIS was a
key tool for fixing these errors - the digitizing and geometry repair too
ls were used in solving these issues. \n\nThis pilot project was implement
ed in Southern Savonia\, Finland. In the region\, zoning has been execute
d for approximately 80 % of the whole land area. The focus of the project
was to investigate the compatibility of the base data and how to automate
the processes of merging\, fixing\, updating and comparing the data. The d
ata was in vector format and was provided by the National Land Survey of F
inland and municipalities of Southern Savonia. \n\nThe automation processe
s were built with a python script and the quality control was made with ma
nual digitization. The official documentation of the zoning and city plans
were included in the borderline vector data. The final product was upload
ed to a GitHub repository. The project also managed to produce a timeline
for the upcoming nationwide project and the distribution between automated
and manual workload in similar projects. \n\nThe methods and the results
of the project could be duplicated in other countries or lead the way towa
rds more open national or regional land use planning.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Land of 60000 zoning plans - QGIS to the rescue! - Ville Hamunen
URL:http://talks.osgeo.org/foss4g-2023/talk/BUZAGV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-WMTYLV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:FieldMaps.io is a personal initiative originally created to dev
elop offline interactive reference maps for humanitarian actors. However\,
in short time\, it transitioned to helping develop common operational dat
asets that form the foundation for humanitarian response planning. Over th
e past 2 years\, enormous effort has gone into releasing a high-resolution
composite dataset able to be updated daily from multiple sources. This ta
lk will cover 3 aspects of the project.\n\nAlgorithm\n\nEdge-matching reso
lves gaps and overlaps between hundreds of separate national data sources\
, requiring an algorithm that can perform at global scale. The resulting m
ethodology uses something akin to a euclidean allocation raster applied to
vector space\, free of the compromises other approaches like generalizati
on and snapping make. If you've ever been challenged by topology or data c
leaning\, you might find some insights into solving your own problems with
the ideas contained here.\n\nPipeline\n\nThe edge-matching algorithm invo
lves multiple complex and computationally intensive steps. Although Geopan
das and GDAL usually come to mind when building multi-step geoprocessing s
cripts\, PostGIS ended up being the fastest and best scaling tool for tran
sforming gigabytes of vector data. I'll challenge your assumptions of how
it can be used to create pipelines on both desktops and in the cloud\, and
make a case for why you should include it in your next project.\n\nSource
s\n\nA composite dataset is only as good as the foundations it builds upon
\, and great care was taken in selecting which sources were used in this p
roject. For international boundaries\, I'll go into detail about how I use
d only public domain sources to create an ISO 3166 compliant dataset. At t
he subnational level\, I'll highlight two projects that each curate update
d administrative boundaries: one by the United Nations\, another by an aca
demic institution.\n\nWhether you're a remote sensing specialist in search
of the best topologically valid boundaries to run zonal statistics with\,
a Python developer frustrated by your pipelines constantly running into m
emory limits\, or just want to run this tool on your own boundaries\, I ho
pe you come away from this talk with a valuable concept you can apply to y
our own work.\n\nData: https://fieldmaps.io/data\n\nTool: https://github.c
om/fieldmaps/edge-extender
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Creating Global Edge-Matched Subnational Boundaries - Maxym Malynow
sky
URL:http://talks.osgeo.org/foss4g-2023/talk/WMTYLV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RPVTPU@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:Access to high-quality data on existing bicycle infrastructure
is a requirement for evidence-based bicycle network planning\, which can s
upport a green transition of human mobility. However\, this requirement is
rarely met: Data from governmental agencies or crowdsourced projects like
OpenStreetMap often suffer from unknown\, heterogeneous\, or low quality.
Currently available tools for road network data quality assessment often
fail to account for network topology\, spatial heterogeneity\, and bicycle
-specific data characteristics. \n\nTo fill these gaps\, we introduce Bike
DNA\, an open-source tool for reproducible quality assessment tailored to
bicycle infrastructure data. BikeDNA performs either a standalone analysis
of one data set or a comparative analysis between OpenStreetMap and a ref
erence data set\, including feature matching. Data quality metrics are con
sidered both globally for the entire study area and locally on grid cell\,
thus exposing spatial variation in data quality with a focus on network s
tructure and connectivity. Interactive maps and HTML/PDF reports are gener
ated to facilitate the visual exploration and communication of results. \n
\nBikeDNA is based on open-source python libraries and Jupyter notebooks\,
requires minimal programming knowledge\, and supports data quality assess
ments for a wide range of applications - from urban planning to OpenStreet
Map data improvement or transportation network research. In this talk we w
ill introduce how to use BikeDNA to evaluate and improve local data sets o
n bicycle infrastructure\, examine what BikeDNA can teach us on the curren
t state of data for active mobility\, and discuss the importance of local
quality assessments to support increased uptake of open and crowd-sourced
data.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:BikeDNA: A tool for Bicycle Infrastructure Data & Network Assessmen
t - Anastassia Vybornova
URL:http://talks.osgeo.org/foss4g-2023/talk/RPVTPU/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KDBNVD@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:STAC Browser is a full-fledged web interface for browsing and s
earching static STAC catalogs and STAC APIs. It has been rewritten from sc
ratch with a lot of new functionality. This talk will introduce STAC Brows
er\, showcase new functionality and uncover some unexpected gems such as t
he broad range of customization possibilities. Lastly\, the presentation w
ill guide you through a set of best practices for your static STAC catalog
or STAC API so that you get the most out of STAC Browser with regards to
functionality and user experience.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Get most out of STAC Browser - Matthias Mohr
URL:http://talks.osgeo.org/foss4g-2023/talk/KDBNVD/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-WYXQ38@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:pgRouting is evolving rapidly\, many changes have been taking p
lace. Lets catch on.\n\nThe focus of this talk will be on the **topology**
functions that were created on 2013\, Its been 10 years\, and its their t
ime to go:\n* Why "I" don't want to use them any more\n* New specialized f
unctionality has been created that substitute the work that the topology f
unctions are doing in a very rustic way.\n* A quick guide on how not to us
e the "soon to be deprecated topology functions"
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:State of pgRouting - Vicky Vergara
URL:http://talks.osgeo.org/foss4g-2023/talk/WYXQ38/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-AHEZTR@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:An overview of the Core Models and Encodings for Styling and Sy
mbology - Part 1: Core ("SymCore") 2.0 draft candidate Standard.\n\nIn com
parison to the current OGC Symbology Conceptual Model: Core Part ("SymCore
") version 1.0\, the new draft candidate Standard aims to better reflect i
ts classification as an OGC Implementation Standard by including the requi
rements classes needed to enable the implementation of interoperable encod
ings\, renderers (e.g.\, OGC API - Maps / OGC API - Tiles) and systems par
sing and/or generating style definitions (e.g.\, OGC API - Styles\, visual
style editors\, style transcoders).\n\nIt does so by featuring:\n\n- A mo
dular logical and conceptual model for styling capabilities\,\n- A minimal
Core requirements class including clear extension mechanisms\, through th
e definition of abstract Selectors\, Symbolizers\, and Expressions\,\n- a
basic Vector Styling requirements class\,\n- a basic Coverage Styling requ
irements class\,\n- requirements classes providing additional styling func
tionality\,\n- a JSON encoding of the conceptual and logical model facilit
ating machine readability\,\n- a CSS-inspired encoding of the conceptual a
nd logical model facilating hand-editing.\n\nThe latest version of the dra
ft is available in HTML (https://opengeospatial.github.io/ogcna-auto-revie
w/18-067r4.html) or PDF (https://opengeospatial.github.io/ogcna-auto-revie
w/18-067r4.pdf).\n\nThe official GitHub repository is at: https://github.c
om/opengeospatial/styles-and-symbology
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Overview of draft OGC Styles & Symbology "SymCore" 2.0 models & enc
odings - Jerome St-Louis
URL:http://talks.osgeo.org/foss4g-2023/talk/AHEZTR/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MYP3PB@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:The Joint Research Centre (JRC) of the European Commission is c
ommitted to providing independent\, evidence-based science and knowledge t
hat supports EU policies. To facilitate this\, the JRC has developed the B
ig Data Analytics Platform (BDAP)\, a data platform that allows data scien
tists to easily access\, analyze\, view\, and reuse scientific data to gen
erate and communicate evidence-based insights and foresight. \n\nBDAP host
s spatiotemporal data at petabyte scale from various domains\, including e
levation\, meteorological\, administrative\, and satellite Earth Observati
on data. Its architecture leverages almost entirely on Free and Open Sourc
e software and tools. The platform offers a cluster environment with both
CPU and GPU machines\, allowing for large-scale data processing. Additiona
lly\, users can visualize and interactively analyze their data through Jup
yter Notebooks and Voilà dashboards. \n\nRecently\, BDAP implemented the
Spatio Temporal Asset Catalog (STAC) specification to describe its data. T
he catalog hosts different types of data\, which share the basic STAC fiel
ds. Thanks to the STAC modularity each data type can be described with its
own STAC extensions. \n\nBDAP reuses and benefits from various STAC Free
and Open Source software and tools. In particular\, from the STAC ecosyste
m it implements the STAC Browser for displaying and searching data\, it pr
ovides STAC compliant APIs through STAC FAST-API backed by an elasticsearc
h instance\, and uses PySTAC as a Python library for working with STAC met
adata. This implementation helps BDAP in its FAIRification process improvi
ng users' search\, access\, and reuse of data. \n\nIn this presentation\,
the design and implementation of the STAC compliant set of software tools
will be described. Some real use cases will be presented\, with an exampl
e on the creation of analysis ready data cubes from Sentinel-2 Earth Obser
vation satellite imagery.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Enhancing Researchers' Data FAIR Experience for producing Policy-Re
levant Insights through STAC Open Source Software and Specifications - Chi
ara Chiarelli
URL:http://talks.osgeo.org/foss4g-2023/talk/MYP3PB/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MHPAPK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T160000
DTEND;TZID=Europe/Tirane:20230628T163000
DESCRIPTION:In Cameroon\, the planning and monitoring of a measles vaccinat
ion campaign is implemented in an open source software called Iaso built o
n a Python based backend combining Django and Postgres/Postgis \; the fron
tend is React based. Iaso aims to provide a number of core functionalities
to support ongoing geospatial data management: a mobile application\, a w
eb dashboard\, a mapping function to merge various data sources\, a user-f
riendly API for data science and scripting\, and a seamless bi-directional
integration with DHIS2 (standard health information system in low- and mi
ddle-income countries).\n\nIaso is articulated around three essential comp
onents : a central georegistry interface\, a mobile data collection tool a
nd a micro planning interface. Those tools are integrated seamlessly with
each other to provide a powerful platform to manage\, update\, merge and v
alidate multiple data sources and structured information collected. Geospa
tial data from GPS collection to the management of multiple reference list
s of organization units (Health\, Administrative or School pyramid) are Ia
so's foundation. Those features allow interconnecting collected data to ex
isting hierarchical features coupled with planification and collection of
survey campaigns in the field through the mobile application and the web p
latform.\n\nIaso exposes a full API providing various endpoints allowing d
ata scientists to integrate data analysis pipeline through external analyt
ic platform. As a geospatial data management platform\, it provides versio
ning of every dataset and is designed to keep a full history of all the ch
anges on the data of interest from the forms to the geometry or metadata o
f the organization units. It also features seamless integration with QGIS
and other desktop applications through a templated Geopackage format.\n\nI
n this presentation\, the tool is explained and described from the plannin
g of the vaccination campaign in Cameroon to the near real-time monitoring
of the campaign (eg. stock and team planning management).\n\nSource : htt
ps://github.com/BLSQ/iaso
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Digitizing and improving GIS for Global Health: from data collectio
n to geospatial data management for a measles vaccination campaign in Came
roon - Céline Bassine
URL:http://talks.osgeo.org/foss4g-2023/talk/MHPAPK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-7S7HNU@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T163000
DTEND;TZID=Europe/Tirane:20230628T170000
DESCRIPTION:The Knowledge Laboratory\, in short k.LAB\, is a software stack
that embraces the FAIR principles: findable\, accessible\, interoperable
and reusable. Its objective is to support linked knowledge across the bord
ers of the domains of single modelers and scientists. k.LAB’s fascinatin
g novelty is the use of semantics to create a natural language to describe
the models and the qualities that want to be observed.\n\nModelers can de
velop their models and publish them to the network. Publishing makes them
findable and accessible within the network. Since everything in the networ
k is observable\, when running a model\, k.LAB looks for the best knowledg
e unit able to resolve the particular request. Interoperability is build a
nd reusability is a natural consequence.\n\nThe k.LAB software stack is fr
ee and open source and relies on various projects of the Osgeo community a
s Geoserver\, Openlayers and the Hortonmachine. It has been in development
for almost 2 two decades and got a particular visibility boost in 2021\,
when the Statistics Division of the UN Department of Economic and Social A
ffairs and the UN Environment Program\, in collaboration with the Artifici
al Intelligence for Environment & Sustainability at the Basque Centre for
Climate Change\, launched the Artificial Intelligence powered application
for rapid natural capital accounting: the ARIES for SEEA Explorer. \n\nLat
ely a python client that allows interaction with k.LAB has been released.
This opens up to new ways to observe the world from within common GIS tool
s as for example QGIS.\n\nAn overview of the state of the art of the proje
ct will be given.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Integrated modeling with k.LAB... and QGIS - Andrea Antonello
URL:http://talks.osgeo.org/foss4g-2023/talk/7S7HNU/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XMRSQB@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T163000
DTEND;TZID=Europe/Tirane:20230628T170000
DESCRIPTION:SOZip ([Seek-Optimized ZIP](https://sozip.org)) is a new open s
pecification on top of the ZIP archive format to compress one or several f
iles organized and annotated such that a SOZip-aware reader can perform ve
ry fast random access (seek) within a compressed file.\nSOZip makes it pos
sible to access large compressed files directly from a .zip file without p
rior decompression. It is not a new file format\, but a profile of the exi
sting ZIP format\, done in a fully backward compatible way. ZIP readers th
at are non-SOZip aware can read a SOZip-enabled file normally and ignore t
he extended features that support efficient seek capability.\nWe will pres
ent how SOZip works under the hood and discuss about SOZip implementations
\, in particular in [GDAL](https://gdal.org)\, which make it possible for
its downstream users\, in particular [QGIS](https://qgis.org)\, to read se
amlessly and efficiently large compressed files in [GeoPackage](http://www
.geopackage.org/)\, [FlatGeoBuf](https://flatgeobuf.org/)\, or shapefile f
ormats.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:SOZip: using directly (geospatial) large compressed files in a ZIP
archive! - Even Rouault
URL:http://talks.osgeo.org/foss4g-2023/talk/XMRSQB/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-YSYWUF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T163000
DTEND;TZID=Europe/Tirane:20230628T170000
DESCRIPTION:The amount of data we have to process and publish keeps growing
every day\, fortunately\, the infrastructure\, technologies\, and methodo
logies to handle such streams of data keep improving and maturing. GeoServ
er is an Open Source web service for publishing your geospatial data using
industry standards for vector\, raster\, and mapping. It powers a number
of open-source projects like GeoNode and geOrchestra and it is widely used
throughout the world by organizations to manage and disseminate data at s
cale. We integrated GeoServer with some well-known big data technologies l
ike Kafka and Databricks\, and deployed the systems in Azure cloud\, to ha
ndle use cases that required near-realtime displaying of the latest AIS re
ceived data on a map as well background batch processing of historical Mar
itime AIS data. \n\nThis presentation will describe the architecture put i
n place\, and the challenges that GeoSolutions had to overcome to publish
big data through GeoServer OGC services (WMS\, WFS\, and WPS)\, finding th
e correct balance that maximized ingestion performance and visualization p
erformance. We had to integrate with a streaming processing platform that
took care of most of the processing and storing of the data in an Azure da
ta lake that allows GeoServer to efficiently query for the latest availabl
e features\, respecting all the authorization policies that were put in pl
ace. A few custom GeoServer extensions were implemented to handle the aut
horization complexity\, the advanced styling needs\, and big data integrat
ion needs.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Processing and publishing Maritime AIS data with GeoServer and Data
bricks in Azure - Andrea Aime
URL:http://talks.osgeo.org/foss4g-2023/talk/YSYWUF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-8SQQB8@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T163000
DTEND;TZID=Europe/Tirane:20230628T170000
DESCRIPTION:In this presentation\, we showcase a unique approach to analyzi
ng Capital Bikeshare trips in Washington D.C. using Open-Source Geospatial
(FOSS4G) tools and technologies. Our project involved loading trip data i
nto a PostGIS database\, utilizing the Valhalla routing engine and OpenStr
eetMap data to find the optimal routes between each pair of stations\, and
then constructing a topogeometry table to represent these routes. Using t
his topogeometry table\, we are able to estimate the number of Capital Bik
eshare trips that occur on each road in Washington D.C.\n\nThe use of FOSS
4G tools and technologies allowed us to perform this analysis in a cost-ef
fective and efficient manner\, while also providing high-quality results.
The results of our analysis have important implications for urban planning
and mobility research\, as they can be used to understand the patterns an
d impacts of bike-share usage in cities.\n\nOur presentation will provide
an overview of the methodology used in our project\, as well as a discussi
on of the results and their implications. We will also share our experienc
es using FOSS4G tools and technologies and provide insights on how these t
ools can be used in similar projects. This presentation is of interest to
geospatial professionals\, urban planners\, and anyone interested in using
FOSS4G tools for data analysis and mobility research.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Pedaling towards Progress: An Analysis of Capital Bikeshare Trips i
n Washington D.C. using Open-Source Geospatial Tools - Max Lindsay
URL:http://talks.osgeo.org/foss4g-2023/talk/8SQQB8/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ESZJPV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T163000
DTEND;TZID=Europe/Tirane:20230628T170000
DESCRIPTION:In the submitted paper\, the topicality of the building stock i
n municipalities in Baden-Württemberg\, part of the Federal Republic of G
ermany\, is examined. Three municipalities were selected and included in t
he study according to the spatial type concept of the Federal Office for B
uilding and Regional Planning (BBSR 2023): rural town 2\,000-5\,000 inhabi
tants\, small town 5\,000-20\,000 inhabitants\, medium-sized town\, 20\,00
0-100\,000 inhabitants. The analysis concept is explained and the quantita
tive and qualitative results of the project\, which is currently in its fi
nal phase\, are presented. The aim is to use these results to derive and c
ommunicate recommendations for action for the municipalities\, but also fo
r the public surveying administration\, in order to contribute to timely a
nd effective action by municipal decision-makers and citizens through fast
er provision of geospatial data.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:An Investigation into Updating the Building Stock Data for Municipa
lities in Baden-Württemberg\, Germany - Franz-Josef Behr
URL:http://talks.osgeo.org/foss4g-2023/talk/ESZJPV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-3BWBFN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T163000
DTEND;TZID=Europe/Tirane:20230628T170000
DESCRIPTION:Every year\, there's a new Postgres major release that improves
on performance in certain areas and could provide new hooks for extension
s like PostGIS to take advantage from them. If not planned well\, upgradin
g your production databases can become a pain. Sooner than you think you'l
l be running on EOL (End-of-Life) versions because the upgrade has been po
stponed too many times. Don't!\n\nDid you know Postgres upgrades can be gr
eatly automatized these days with downtimes of only a few seconds? This ta
lk will show you how and will also present some essential features from re
cent Postgres and PostGIS versions to get you excited for the new upgrade.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Upgrade your Postgres and PostGIS will thank you - Felix Kunde
URL:http://talks.osgeo.org/foss4g-2023/talk/3BWBFN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XBHYF9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T163000
DTEND;TZID=Europe/Tirane:20230628T170000
DESCRIPTION:“Cloud-Native Geospatial” is a new paradigm for performing
efficient data access and compute the cloud in an interoperable way in ord
er to achieve scalable and repeatable analysis of geospatial data. The las
t few years have seen major developments in open standards and open softwa
re that make this possible\, supporting full end to end interoperable work
flows on remote sensing data\, starting from data discovery to publishing
of derived products.\n\nThis talk will provide an overview of what Cloud-N
ative geospatial is and why it is important for building scalable architec
tures. It will cover the current state of the Spatio Temporal Asset Catalo
g (STAC) specifications\, and the landscape of cloud-optimized file format
s\, for raster\, vector\, and point-cloud data formats (COG\, GeoZarr\, Ge
oParquet\, COPC).
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:An overview of Cloud-Native Geospatial - Matthew Hanson
URL:http://talks.osgeo.org/foss4g-2023/talk/XBHYF9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-D3ZRYY@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T163000
DTEND;TZID=Europe/Tirane:20230628T170000
DESCRIPTION:On February 6\, 2023 a sequence of major earthquakes with magni
tudes 7.8 and 7.5 have struck Southern Turkiye and Northern Syria\, causin
g massive damage and very high number of casualties in both countries. The
sequence of earthquakes were followed with hundreds of aftershocks within
the month following the earthquakes\, as well as triggering other major e
arthquakes\, such as the 6.4 magnitude earthquake that had struck Antakya
on February 20. Humanitarian OpenStreetMap Team (HOT)\, with Yer Çizenler
(YÇ)\, HOT’s local partner within the Turkish OSM community\, have act
ivated to map the missing road and building base data with the help of reg
ional and global OpenStreetMap communities. \n\nMore than 7 thousand con
tributors from these communities\, together\, have contributed to the addi
tion of more than 1.4 million buildings\, 70\,000 km of roads into OpenStr
eetMap for the use of field volunteers and organizations worldwide. \n\nIn
this talk\, the audience will be informed about the coordinated efforts w
ithin this mapping activation\, the impact of the data created with some e
xample use cases within the response activities. The audience will be info
rmed about various open data sources that were used to enhance the existin
g OSM data\, and their licensing and compatibility considerations during t
he mapping process. The presenters will also describe the validation\, dat
a quality assurance and monitoring methods\, approaches and tools utilized
for ensuring the OSM data is reliable\, current and is able to meet commu
nity standards within both short and long terms.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Community Activation for the Kahramanmaraş Earthquake Response via
OpenStreetMap - Can Unen
URL:http://talks.osgeo.org/foss4g-2023/talk/D3ZRYY/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-SR99W9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230628T170000
DTEND;TZID=Europe/Tirane:20230628T180000
DESCRIPTION:Geospatial analysis welcomes an audience to interact with compl
ex interactions and dynamic shifts in ecosystem balance. Location intellig
ence collected as data layers mirror a symphony or chapters in a book. We
will explore the potential risks of vulnerable cities by exploring the env
ironment\, economics\, built infrastructure\, and how they intersect. We b
uild the story or music over time while exploring the tensions we create.
Let’s examine the edges of eco-geomorphic frameworks and listen for a na
rrative.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Open-Source Solutions: Expanding our Humanity with Data Stories - B
onny P McClain
URL:http://talks.osgeo.org/foss4g-2023/talk/SR99W9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-E99GUQ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T090000
DTEND;TZID=Europe/Tirane:20230629T093000
DESCRIPTION:We will explore how Re:Earth as a digital public good could sup
port a "Peaceful Profitable Society" and create new employment opportuniti
es.\nRe:Earth is an open source platform built around a geographic informa
tion system that digitally represents geospace and enables analysis and vi
sualization of cities and regions. The use of such digital public goods of
fers opportunities to develop new ways of working and improve their own li
ves\, especially for the socially vulnerable.\n\nIn particular\, we will e
xplore the potential for vulnerable populations\, such as refugees and sin
gle mothers\, to use Re:Earth to pave the way for self-empowerment. We wil
l also delve into how digital public goods such as Re:Earth can impact soc
iety as a whole\, especially how they can be a tool for the vulnerable to
improve their own lives and contribute to the realization of a "society wh
ere peace is profitable".\n\nThis speech will provide insight into how suc
h digital public goods can impact individual lives and society as a whole\
, and how they can help shape a "society where peace is profitable".
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Creating a Peaceful and Profitable Society: FOSS4G and New Employme
nt Opportunities - Rei Kasai
URL:http://talks.osgeo.org/foss4g-2023/talk/E99GUQ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-JDLBQH@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T093000
DTEND;TZID=Europe/Tirane:20230629T100000
DESCRIPTION:Geochicas is a initiative born in State of the Map Sao Paolo an
d adopted by FOSS4G communities over the past years. We would like to shar
e with you what had happened in the last couple of years and what we fores
ee in the future of the initiative. How Geochicas is part of a larger ecos
ystem of siblings organizations working towards having a more balanced pre
sence of women and minority groups in the Geospatial communities.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Geochicas: From SOTM to FOSS4G\, a Geospatial journey - Miriam Gonz
alez
URL:http://talks.osgeo.org/foss4g-2023/talk/JDLBQH/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MBS8M9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:Gleo is a nascent javascript WebGL mapping library. It aims to
find a niche alongside Leaflet\, OpenLayers\, MapLibre and Deck.gl.\n\nThi
s library was presented at FOSS4G 2022\, with an emphasis on its architect
ural foundations: geometry/reprojection/antimeridian handling\, and object
-oriented abstractions for WebGL data structures.\n\nThis session provides
a tour of the features developed during the last year. These include\, am
ong others:\n- Work done as part of the OSGeo-OGC codesprints (OGC API cli
ents\, experimental symbols)\n- Animated symbols (render loop)\n- Symbol c
lass decorators (ability to add more functionality to a cartographic symbo
l class during runtime)\n- Flexibility of scalar field manipulation (symbo
ls that render as a magnitude instead of a colour\, then the field renders
as e.g. a heatmap)\n\nThese functionalities are a fresh approach to carto
graphic rendering and will provide a glimpse of the potential of Object-Or
iented WebGL manipulation for cartographic rendering.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Gleo Feature Frenzy - ivansanchez
URL:http://talks.osgeo.org/foss4g-2023/talk/MBS8M9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-3HUQS9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:The Long Island Zoning Atlas is an interactive web map that dis
plays zoning data\, public services\, and demographic data for municipalit
ies all across Long Island excluding New York City. The app focuses on sta
tistics that help affordable housing advocates plan housing projects. This
year we rebuilt the Long Island Zoning Atlas using our new FOSS stack. Th
e project presented a problem very common to GIS projects: transforming da
ta from many different sources\, in this cases towns. We were given the da
ta in many different formats and needed to transform it all into clean\, u
sable data which is organized to our needs and renders quickly and efficie
ntly on the web.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N115 - Second Floor
SUMMARY:Many Data Sources\, One Web Map: Data cleaning and optimization wit
h FOSS - Will Field\, Valerie Bauer
URL:http://talks.osgeo.org/foss4g-2023/talk/3HUQS9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GEBSMM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:Growing urbanization cause environmental problems such as vast
amount of carbon emissions and pollution all over the world.\nSmart Infras
tructure and Smart Environment are two significant components of the smart
city paradigm that can create opportunities for ensuring energy conservat
ion\, preventing ecological degradation\, and using renewable energy sourc
es. United Nations Sustainable Development Goals (SDGs) such as “Sustain
able Cities and Communities”\, “Accessible and Clean Energy”\, “In
dustry\, Innovation and Infrastructure”\, and “Climate Action” can b
e achieved by implementing the smart city concept efficiently. Since a gre
at portion of the data contains location information\, geospatial intellig
ence is a key technology for sustainable smart cities. We need a holistic
framework for the smart governance of cities by utilizing key technologica
l drivers such as big data\, Geographic Information Systems (GIS)\, cloud
computing\, Internet of Things (IoT). Geospatial Big Data applications off
er predictive data science tools such as grid computing and parallel compu
ting for efficient and fast processing to build a sustainable smart city e
cosystem.\n\nHandling geospatial big data for sustainable smart cities is
crucial since smart city services rely heavily on location-based data. Eff
ective management of big data in storage\, visualization\, analytics\, and
analysis stages can foster green building\, green energy\, and net zero t
argets of countries. Geospatial data science ecosystem has many powerful o
pen source software tools. According to the vision of PANGEO\, a community
of scientists and software developers working on big data software tools
and customized environments\, parallel computing systems have the ability
to scale up analysis on geospatial big data platforms which is key for oce
an\, atmosphere\, land\, and climate applications. Those systems allow use
rs to deploy clusters of compute nodes for big data processing. In the app
lication phase of this study\, Pandas\, GeoPandas\, Dask\, Dask-GeoPandas\
, and Apache Sedona libraries are used in Python Jupyter Notebook environm
ent. In this context\, we carried out a performance comparison of two clus
ter computing systems: Dask-GeoPandas and Apache Sedona. We also investiga
ted the performance of the novel geospatial data format GeoParquet togethe
r with other well-known formats.\n\nThere is a common vision\, policy reco
mmendations\, and industry-wide actions to achieve the 2050 net zero carbo
n emission scenario in the United Kingdom. The energy efficiency of the En
glish housing stock has continued to increase over the last decade. Howeve
r\, there is a need for systematic action plans in parcel scale to deliver
on targets. In the study\, open data sources are used such as Energy Perf
ormance Certificates (EPC) data of England and Wales\, Ordnance Survey (OS
) Open Unique Property Reference Number (UPRN)\, and OS Building (OS Open
Map) for analysing energy efficiency level of domestic buildings. Firstly\
, EPC data is downloaded from Department for Levelling Up\, Housing & Comm
unities data service in Comma Separated Value (CSV)\, UPRN data from OS Op
en Hub in GeoPackage (GPKG)\, and buildings data from OS in GPKG formats.
After saving each file in GeoParquet format\, EPC data and UPRN point vect
or data are joined based on the unique UPRN id. Then each UPRN data attrib
ute is appended to the relative building polygon by conducting spatial joi
n operation. Read\, write\, and spatial join operations are both conducted
on Dask-GeoPandas and Apache Sedona in order to compare the performances
of the two big spatial data frameworks.\n\nCluster computing system enable
s much faster data handling when compared with the traditional approaches.
Comparing performances of the frameworks\, local computing hardware (11th
Gen Intel Core i7-11800H 2.30 GHz CPU\, 64 GB 3200 MHz DDR4 RAM) is used.
According to the results\, Dask-GeoPandas and Apache Sedona prevailed Geo
Pandas in read\, write\, and spatial join operations. Apache Sedona perfor
med better during the performance tests. On the other hand\, GeoParquet fi
le format was much faster and smaller in size when compared with the GPKG
data format. After spatial join operation\, energy performance attributes
are included in building data. In order to reveal regional energy efficien
cy patterns\, SQL statements are used for filtering the data according to
the energy rates. The query result is visualized using Datashader which pr
ovides highly optimized rendering with distributed systems.\n\nThis study
answers the question “Can geospatial big data analytics tools foster sus
tainable smart cities?”. Volume\, value\, variety\, velocity\, and verac
ity of big data require different approaches than traditional data handlin
g procedures in order to reveal patterns\, trends\, and relationships. Usi
ng spatial cluster computing systems for large-scale data enables effectiv
e urban management in the context of smart cities. On the other hand\, ene
rgy policies and action plans such as decarbonization\, and net zero targe
ts can be achieved by sustainable smart cities supported by geospatial big
data instruments. The study aims to reveal the potential of big data anal
ytics in the establishment of smart infrastructure and smart buildings usi
ng large-scale geospatial datasets on state-of-the-art cluster computing s
ystems. In future studies\, larger spatial datasets like Planet OSM can be
used on cloud-native platforms to test the capabilities of the geospatial
big data tools.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:GEOSPATIAL BIG DATA ANALYTICS FOR SUSTAINABLE SMART CITIES - Muhamm
ed Oguzhan Mete
URL:http://talks.osgeo.org/foss4g-2023/talk/GEBSMM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TDMRZC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:deck.gl is a popular open source data visualization library tha
t uses the power of WebGL to render huge amounts of data performantly in t
he browser. A collection of versatile layers allows the user to create man
y different types of visualizations\, with excellent support for geospatia
l data in particular.\n\nThe core layers can be extended by the means of d
eck.gl extensions to create interactive experiences which are not possible
in other data visualization frameworks.\n\nThis [talk](https://docs.googl
e.com/presentation/d/1YMfMeB38mhhYXNJ5OH55r5OsieZrbugR91BcEouSm2E/edit?usp
=sharing) will give an overview of deck.gl\, including some of the core la
yers and will then focus on three of the latest extensions:\n\n - The Col
lisionFilterExtension avoids collisions between features on screen. This c
an be used to selectively show large cities in preference to small ones on
a map when they would otherwise overlap or laying out labels.\n - The Ma
skExtension implements realtime masking of data by an arbitrary spatial bo
undary. An example use case is clipping a set of roads and places of inter
est to the boundary of a city.\n - The TerrainExtension offsets the 3D co
mponent of features by referencing a separate 3D layer. For example\, a se
t of pins on a map can be placed at the correct height relative to a 3D te
rrain layer.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Supercharging deck.gl layers with extensions - Felix Palmer
URL:http://talks.osgeo.org/foss4g-2023/talk/TDMRZC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-VS8RYX@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:OpenLayers is a powerful web-mapping library\, and it has been
around for quite a while. Far from being stuck in a past state where it of
fered most features anyone could expect\, the community of contributors an
d maintainers are continuously pushing it forward\, rethinking orientation
s and taking in new trends. Be it cloud-native formats\, emerging standard
s or drastic performance improvements\, more and more innovations are beco
ming parts of OpenLayers feature set.\n\nThis talk will give you an overvi
ew of the past few years of development\, and show in how many incredibly
useful ways OpenLayers can be used nowadays. We will also discover the exc
iting developments that are shaping up for the future\, and how all this i
s being made possible.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:What's new and coming up in OpenLayers - Olivia Guyot
URL:http://talks.osgeo.org/foss4g-2023/talk/VS8RYX/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GWPKMG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:If you have ever had the experience of having to write code to
draw on web maps\, you'll know how painful the process can be - especially
when situations get more complex.\n\nTerra Draw is an open source JavaScr
ipt library that provides a new way to add drawing functionality to a host
of web mapping libraries\, including Leaflet\, OpenLayers\, Google Maps\,
MapboxGL JS and MapLibreGL JS.\n\nThe library provides a selection of bui
lt in modes that 'just work' across different mapping libraries. These fea
tures include elementary drawing tools like point\, line and polygon\, as
well as supporting more advanced concepts like snapping\, rotation and sca
ling. \n\nTerra Draw is also designed to be extendable so that you can wri
te your own custom modes and adapters (thin wrappers for each mapping libr
ary). The architecture of the library means that any mode work can work wi
th any adapter and vice versa creating a strong multiplier affect as new m
odes and adapters are written. This decoupling has the added benefit that
drawing libraries can be swapped out without breaking your app!\n\nThe tal
k will examine the history of the library\, how to get started\, and also
an opportunity to hear more about the future of Terra Draw.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Introducing Terra Draw: A JavaScript Library To Draw On Any Web Map
- James Milner
URL:http://talks.osgeo.org/foss4g-2023/talk/GWPKMG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-DWCZBQ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:Do you want to broaden your horizons by learning about geospati
al support for the United Nations operations? Or are you interested in dev
eloping highly efficient and portable geospatial apps which make use of PM
Tiles\, COPC\, COG\, Raspberry Pi\, and a cool Web3 technology named IPFS
(Inter-planetary File System)? We are doing both in the Domain Working Gro
up 7 (DWG 7) on Smart Maps of the UN Open GIS Initiative.\n\nIn this parti
cipatory and voluntary DWG established in Firenze in August 2023\, partici
pants bring in their objectives and combine efforts within the Partnership
for Technology in Peacekeeping to bring greater involvement to peacekeepi
ng through innovative approaches and technologies that have the potential
to empower UN global operations. In addition to our core objective to supp
ort the use of UN Vector Tile Toolkit in the UN Global Service Centre\, DW
G 7 is supporting domestic and campus-level service operations\, and suppo
rting 3D geospatial data such as point clouds and 3D city models. We are c
ombining efforts to define and implement the concept of Smart Maps.\n\nWe
are happy to share with you our new effort named Model UN Development and
Operations (MUNDO) that simulates geospatial support for the United Nation
s operations by making use of existing open geospatial data and our Smart
Maps technologies. MUNDO project is not only useful for demonstrating the
technology for the UN staff\, but also useful for learning about the situa
tion and the UN’s effort. We are also happy to share with you our new co
ncept of WebMaps3\, which introduces Web3 technology for web maps. By comb
ining IPFS and cloud optimized formats like PMTiles\, COPC\, and COG\, we
were successful in hosting a vector tiles service from a newly released na
tion-wide cadastre dataset on a Raspberry Pi\, within 10 days after the re
lease\, by producing a 14GB PMTiles file.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Smart Maps for the UN and All - keeping web maps open - Hidenori Fu
jimura\, Yui Matsumura
URL:http://talks.osgeo.org/foss4g-2023/talk/DWCZBQ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-HY7BDD@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:QGIS releases three new versions per year and each spring a new
long-term release (LTR) is designated. Each version comes with a long lis
t of new features. This rapid development pace can be difficult to keep up
with\, and many new features go unnoticed. This presentation will give a
visual overview of some of the most important new features released over t
he last calendar year. \n\nIn March of 2023 a new Long-term release was pu
blished (3.28)\, and shortly before FOSS4G\, the latest stable version of
QGIS (3.32) will be released. I will start by comparing the new LTR (3.28)
to the previous (3.22). Here I will also summarize by category the new fe
atures found in the latest LTR (GUI\, processing\, symbology\, data provid
ers etc.).\n\nI will then turn my attention to the important new features
found in the latest releases (3.30 & 3.32). Each highlighted feature will
not simply be described but will be demonstrated with real data. The versi
on number for each feature will also be provided. If you want to learn abo
ut the current capabilities of QGIS\, this talk is for you! \n\nPotential
topics include: Annotation layers * GUI enhancements * New Expressions *
Point cloud support * Print layout enhancements * New renderers and symbol
ogy improvements * Mesh support * 3D * Editing
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:QGIS Feature Frenzy - both for the Long-term release (3.28) and the
Latest release (3.32) - Kurt Menke
URL:http://talks.osgeo.org/foss4g-2023/talk/HY7BDD/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-BY7NHY@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:In our allocated 15 minutes\, we would like to take you on a tr
ip following the winding roads of building a community\, the Romanian geos
patial community: geo-spatial.org. We want to share our story\, beyond our
geodata and knowledge portal\, to the very core of the values and princip
les that have guided us through difficult times and made our overcame chal
lenges even brighter. \nIn our more than a decade of existence\, we’ve o
rganised over 25 national FOSS workshop\, a regional FOSS4G in 2013 and a
global FOSS4G in 2019\, we’ve initiated collaborative geo-related projec
ts and managed to infuse the geospatial component in various non-spatial o
rganisations\, such as the ones in education or investigative journalism.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Making of a community - beyond the recipe - Vasile Crăciunescu\, C
odrina Ilie
URL:http://talks.osgeo.org/foss4g-2023/talk/BY7NHY/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-YW97TB@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T103000
DTEND;TZID=Europe/Tirane:20230629T110000
DESCRIPTION:Published in 2020\, the European strategy for data sets the vis
ion for Europe to become a leader in a data-driven society by establishing
so-called common European data spaces in all strategic societal sectors.
Data spaces are envisioned as sovereign\, trustworthy and interoperable da
ta sharing environments where data can fairly flow within and across actor
s\, in full respect of European Union (EU) values to the benefit of Europe
an economy and society. The development of data spaces is accompanied by a
set of horizontal legislative measures\, including\, among others\, an Im
plementing Act on high-value datasets under the Open Data Directive that l
ays down a list of datasets (many of which being geospatial) that EU Membe
r States public sector organisations are required to make available for fr
ee\, under open access licenses\, in machine-readable formats and via Appl
ication Programming Interfaces (APIs). \nThe talk will describe the activi
ties around open source geospatial software and open geospatial data that
the European Commission’s Joint Research Centre (JRC) has performed to s
upport the development of the common European Green Deal data space\, focu
sed on environmental data sharing and instrumental to address climate chan
ges and environmental challenges in line with the top priority of Von der
Leyen’s Commission 2019-2024. \nA key enabler to bring public data into
this data space is the infrastructure setup for the EU INSPIRE Directive\,
which is technically coordinated\, maintained and operated by the JRC. Th
e INSPIRE Directive itself\, together with the Directive on public access
to environmental information\, are currently subject of an impact assessme
nt that might lead to a revision of the legal framework (GreenData4All ini
tiative). This is accompanied by an overall modernisation of the technical
infrastructure\, increasingly based on open source software both at the C
ommission side (GeoNetwork for the INSPIRE Geoportal\, ETF for the INSPIRE
Reference Validator and Re3gistry for the INSPIRE Registry) and at the Me
mber States side\, where FOSS4G tools are the primary choice for both serv
ing and consuming data. Thanks to a number of INSPIRE Good Practices promo
ted by the community\, new standards and approaches for data encoding and
sharing (e.g. based on OGC APIs) are bringing additional value to the INSP
IRE stack. The same set of approaches ensures the full alignment and compl
ementarity between INSPIRE and the Implementing Act on high-value datasets
\, thus positioning open source geospatial software as a true enabler for
the Green Deal data space.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Open source geospatial software in support of the common European G
reen Deal data space - Marco Minghini
URL:http://talks.osgeo.org/foss4g-2023/talk/YW97TB/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QCRSWC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:We developed a free graph-based geo-intelligence engine that se
rves fast\, scalable\, and reliable data analysis. The engine's value lies
in its flexibility and applicability to any relational dataset\, as well
as its integration of open-source technologies and libraries. We chose to
build our geo-intelligence engine on a graph infrastructure to enable fast
er\, index-free queries and better support for interconnected data.\n\nTo
showcase the capabilities of our engine\, we have developed a geo-financia
l software that provides users with a powerful tool for analyzing financia
l scores of companies based on geo-location. Businesses can quickly and ea
sily analyze data to gain valuable insights into competitors\, potential p
artnerships\, and market trends. Our software presents the results of the
analysis in a user-friendly and visually appealing format\, making it acce
ssible even to non-technical users.\n\nOur geo-financial analysis software
is based on user-specified location and range. The user interacts with an
Angular frontend\, which incorporates the Leaflet library for map interac
tion and an OpenStreetMap basemap. The backend is based on Golang\, which
handles authentication and message queueing interaction with a Python anal
ysis tool. The data retrieved for Python processing comes from a Neo4j gra
ph database\, which is accessed through Cypher queries and networking algo
rithms. All of the software components are located in separate containers\
, promoting flexible and independent scalability achieved with Docker Comp
ose and orchestrated by Kubernetes.\n\nIn this presentation\, we will disc
uss our graph-based geo-intelligence engine\, which is the backbone of our
application. We will showcase the geo-financial analysis application itse
lf\, providing a demo and demonstrating how it can be used for business ge
o-intelligence analysis. Throughout the presentation\, we will continuousl
y discuss the open-source technologies that are at the core of our work an
d focus on the value that each of them has brought to our achievements.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Graph-based geo-intelligence - Francesca Drăguț
URL:http://talks.osgeo.org/foss4g-2023/talk/QCRSWC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-SQ3MLL@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:[Slides](https://docs.google.com/presentation/d/1RgI-t9U5dlTmmo
2Yq--m8vICxFSUn_YIdxUrudBXNZ4/edit?usp=sharing)\n\n[vis.gl](https://vis.gl
) is a suite of composable\, interoperable open source geospatial visualiz
ation frameworks (GPU powered) centered around deck.gl. During the last 4
years vis.gl has played an essential role in the development of geospatial
applications during the last 4 years. \n \nWith close to 100K daily downl
oads from npm\, it’s widely used today in many areas and industries: fro
m academics teams\, to enterprise companies like Uber\, Foursquare\, CARTO
\, Google or Amazon.\n\nThe open governance of vis.gl has guaranteed the e
volution and maintenance of the framework\, the project [joined](https://o
penjsf.org/blog/2022/06/07/openjs-world-2022-openjs-foundation-welcomes-ur
ban-computing-foundation-vis-gl-and-kepler-gl/) the OpenJS foundation in 2
022 with the main goal of re-enforcing the open evolution of the project.\
n\nDuring this talk we’ll do a quick and high level introduction of the
most important [frameworks](https://vis.gl/frameworks) that belong to this
suite (deck.gl\, kepler.gl\, loaders.gl\, etc.)\, we’ll do an update of
the most important features and milestones achieved in the last year\, an
d we’ll share the strategy and direction for the next year.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:vis.gl\, the powerful framework suite behind deck.gl and kepler.gl
- Alberto Asuero Arroyo\, Ib Green
URL:http://talks.osgeo.org/foss4g-2023/talk/SQ3MLL/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-BPQNBC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:Kosovo is one of the most environmentally degraded countries in
Europe. It is also one of the poorest. The country lacks the capacity to
conduct environmental assessments to gauge the scale of its environmental
problems. It has even less capacity to understand its vulnerability to cli
mate change and its prognosis for sustainable development. This paper desc
ribes the use of available (open) resources by the technically trained to
understand environmental changes and provide a framework for developmental
research that provides practical understandings of climate impacts. There
tends to be a lack of awareness of the tools and scant knowledge of their
use towards sustainable development. \nAn environmental assessment of Kos
ovo using large and open remote-sensing data from Google Earth Engine is e
xplained through an embedded multi-case design. Our approach used publicly
available models and code walkthroughs from the book Cloud-based Remote S
ensing with Google Earth Engine. The models were coded for Kosovo and the
greater western Balkans region in JavaScript using Google Earth Engine ope
n datasets to analyze environmental conditions in this region. This work d
emonstrates the value of free and open tool development and analysis for d
evelopment of environmental sustainability. The use of open data requires
careful analytical designs and the application of correct tools for specif
ic regions and particular uses. Complex environmental conditions can muddl
e the data and analyses generated from open datasets. The “un-muddled”
analysis performed here adds to the knowledge base of the environmental c
onditions within Kosovo and provides insight into regional assessment of c
hanging climates. \nModels for air pollution and population exposure\, gro
undwater monitoring with GRACE\, urban environments\, and deforestation vi
ewed from multiple sensors were compiled into an environmental assessment
of the scopes and scales of several environmental issues that plague Kosov
o. The air pollution and population exposure model assesses the human toll
of air pollution in Kosovo. Groundwater monitoring with Gravity Recovery
and Climate Experiment (GRACE) appraises the health of aquifers and the se
curity of water resources. Urban-environment analysis evaluates the change
s that are occurring in urban locations in Kosovo. And the deforestation m
odel is used to determine and evaluate the changes to several environments
in Kosovo. The project will also include discussions of scalability to un
derstand how the interconnected environmental conditions of the Balkans re
gion can be further studies. The models\, analytical frameworks\, and over
arching goals provide a robust strategy towards practical leveraging of re
mote sensed data to provide intrinsic value into developmental countries.
\nThe methods are interchangeable and replicable for climate-change analys
is\, sustainability decision making\, and monitoring of environmental chan
ge. The urban expansion in Kosovo from 2010 till 2020 is studied with Land
sat and MODIS mission data to understand the consequences of land use chan
ge. The air pollution and population exposure model employs Sentinel-5 TRO
POMI and population density data to help discern air pollution levels and
the human toll of environmental degradation. The groundwater monitoring ap
plication uses Gravity Recovery and Climate Experiment strives to clarify
water storage capacities and trends within Kosovo’s aquifers. The forest
degradation and deforestation model uses Landsat mission data to understa
nd the changes occurring within the forests of Kosovo. The combination of
these models creates a comprehensive case study of the environmental condi
tions within Kosovo and provides a baseline for understanding the effects
of changing climates in the region. This information is crucial in develop
ing effective strategies to address the challenges posed by climate change
and to ensure a sustainable future for the region. \nThis paper clarifies
the methods used for modeling of big data sets in Google Earth Engine to
generate products that can be used to assess both climate change and envir
onmental change. We explore the frameworks for cloud computing of open-dat
a environmental analyses by evaluating data selection and analytical techn
iques to provide an analytical framework for future development. Further b
uilding the cross-sectional understanding of the leverage utility of Googl
e Earth Engine with analytical frameworks that provide utility with develo
ping academic frameworks for resilience building and products that can tra
verse into government institutional knowledge building\, private sector su
stainable developmental gaps\, public sector environmental and climate dev
elopmental strategies. \nThe emergence of new technologies has provided op
portunities for new approaches to broadly understand the impacts of global
climate change and free-to-use frameworks places the capacity to understa
nd attainable for developing countries. The use of this technology enables
development of a regional understanding of climate change\, its impacts\,
and the approaches for enhancing resilience through analysis of petabytes
of open satellite data. This paper delivers a framework with which remote
ly sensed data can be assessed to understand how human-environment interac
tions in developing nations will be influenced by changing climates. These
models which are all functionally different have environmental links that
through development provides the future of open big data for building cli
mate change resilience through a remote sensed top to bottom understanding
of what the data means and how it can be applied.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Google Earth Engine and the Use of Open Big Data for Environmental
and Climate-change Assessments: A Kosovo Case Study - Dustin Sanchez
URL:http://talks.osgeo.org/foss4g-2023/talk/BPQNBC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-NHXAWW@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:This talk is exactly what it says on the tin: I want to extract
restaurants or shops or train stations from OpenStreetMap. Or every POI t
here is. How do I do that and why extraction is so damn hard? This talk is
not exactly a one-two-click instruction: we will see how data gets into O
SM and why it is not easy to get it out.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:How to get points of interest from OSM - Ilya Zverev
URL:http://talks.osgeo.org/foss4g-2023/talk/NHXAWW/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MTVQLU@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:Since we have introduced QGIS 3D in 2017\, it has gone through
major improvements. In addition to new features\, several new data formats
have been also integrated to QGIS.\n\nThis presentation will cover the la
test improvements made as result of the recent crowdfunding efforts to int
roduce point cloud processing\, enhance 3D maps for elevation data.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:QGIS 3D\, point cloud and elevation data - Saber Razmjooei
URL:http://talks.osgeo.org/foss4g-2023/talk/MTVQLU/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ENUCGK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:The European Ground Motion Service (EGMS) is part of the Copern
icus Land Monitoring Service (CLMS) lead by the EEA (European Environment
Agency). EGMS is based on the full resolution InSAR processing (20x5m) of
the European Space Agency (ESA) Sentinel-1 (S1). This massive geospatial t
imeseries dataset is composed by ~10.000 million timeseries distributed ov
er 31 European countries. The baseline covers 2015-2020 and updates are be
ing published on a yearly basis. It is publicly accessible at https://egms
.land.copernicus.eu/ with a 3D viewer and download service. \n\nThis open
dataset consists of three product levels (Basic\, Calibrated and Ortho). T
he Basic and Calibrated are offered at full resolution 20x5m (Line of Sigh
t) whereas the Ortho product offers horizontal (East-West) and vertical (U
p-Down) anchored to the reference geodetic model resampled at 100x100m.\n\
nSixense is coordinating a consortium responsible for the independent vali
dation of this continental scale geospatial dataset. The validation goal i
s to assess that the EGMS products are consistent with user requirements a
nd product specifications\, covering the expected range of applications. T
o evaluate the fitness of the EGMS ground motion data service seven reprod
ucible validation activities (VA) have been developed gathering validation
data from different sources across 12 European countries:\n\n• VA1 –
Point density check performed by Sixense. \n\n• VA2 – Comparison with
other ground motion services carried out by NGI (Norwegian Geotechnical In
stitute). \n\n• VA3 – Comparison with inventories of phenomena/events
performed by BRGM (French Geological Survey). \n\n• VA4 – Consistency
check with ancillary geo-information carried out by NGI. \n\n• VA5 – C
omparison with GNSS data performed by TNO (Dutch Geological Survey). \n\n
• VA6 – Comparison with insitu monitoring data performed by GBA (Austr
ian Geological Survey). \n\n• VA7 – Evaluation XYZ and displacements w
ith Corner Reflectors performed by TNO. \n\nThe validation environment dev
eloped and maintained by Terrasigna includes all the necessary elements to
perform all the validation tasks from data collection and description to
execution of the different methodologies. The objective of this portable K
ubernetes/Terraform cloud-based system is to guarantee reproducibility of
all the validation activities:\n\n• A MinIO web-based validation data up
load tool where scientists can upload their validation data and EGMS subse
ts.\n\n• A validation data catalogue based on GeoNode (based on OGC CSW)
where all validation sites data is properly described and georeferenced t
o ensure reproducibility.\n\n• JupyterHub notebook environment where sci
entists can develop their validation scripts (Python/R). These notebooks p
roduce graphs and figures to be included in the yearly validation reports.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:EGMS: Validating 10.000 million open geospatial ground motion times
eries at EU scale - Joan Sala Calero
URL:http://talks.osgeo.org/foss4g-2023/talk/ENUCGK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TLTSLK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:#30DayMapChallenge is a daily map making challenge which is hel
d since 2019 every year in november on social network. This challenge has
become year after year popular for the mapmakers community\, and more than
8000 maps have been posted in 2022 session.\nLast year was my first parti
cipation\, it was a great opportunity to try to make unusual maps\, comple
te sleeping projects\, and be updated with geospatial technologies. \nIn t
his talk will be presented how this challenge has been completed and espec
ially which open tools has been used to make the 30 maps.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:#30DayMapChallenge with Open tools - Raymond Lay
URL:http://talks.osgeo.org/foss4g-2023/talk/TLTSLK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-B9DDED@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:UNVT Portable is a package for RaspberryPi that allows users to
access a map hosting server via a web browser within a local network\, pr
imarily for offline use during disasters. It is designed to aid disaster r
esponse by combining aerial drone imagery with OpenStreetMap and open data
tile datasets.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Offline web map server "UNVT Portable" - ShogoHirasawa\, Hidenori F
ujimura\, Taichi Furuhashi
URL:http://talks.osgeo.org/foss4g-2023/talk/B9DDED/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-Y77TU8@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:[OL-Cesium](https://github.com/openlayers/ol-cesium/) is a popu
lar Open source Javascript library that you can leverage to add 3D to a ne
w or existing OpenLayers application. You code the logics in a single plac
e and it gets applied to both OpenLayers 2D map and Cesium 3D globe. The l
ibrary handles the synchronization of the view\, layers\, styling\, for yo
u. This behaviour is customizable.\n\nSince its creation\, 9 years ago\, t
he library has attracted a large community of users. It has evolved to fol
low OpenLayers\, Cesium and the global javascript ecosystem.\nThis talk is
about the strengths of the library\, its state and the plans for the futu
re.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:State of the OL-Cesium library - Guillaume Beraudo
URL:http://talks.osgeo.org/foss4g-2023/talk/Y77TU8/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-HMGBYV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T110000
DTEND;TZID=Europe/Tirane:20230629T113000
DESCRIPTION:Using generic or standard content management system (CMS) like
Wordpress or Strapi for managing geospatial data isn't an optimal solution
. Since object geometry isn't just one of many data fields\, it requires s
pecial handling for setting the data (e.g.\, on the map)\, storing data\,
transforming data for various needs (geometry output format\, CRS etc.) an
d using them for spatial analysis.\n\nWhen talking about a geospatial CMS\
, one would think that using GeoServer should be a must. How else would yo
u vizualize a non-trivial amount of data on the map\, right? Although Geos
erver might be a good answer\, that's not the only one. We\, at our compan
y\, have developed our custom geospatial CMS using the OpenLayers mapping
library on the frontend and PostgreSQL (with PostGIS\, of course) on the b
ackend\, using PHP Laravel and GeoJSON as middle man between the data stor
e and the frontend.\n\nCMS platforms frequently have one specific feature.
Different objects may have various attributes. Using the EAV (entity-attr
ibute-value) model is one of the methods that is frequently utilized\, alt
hough this choice usually comes with a number of issues\, such as querying
and storing the data. We used the possibility to swap out the EAV model f
or a straightforward json field in our CMS.\n\nThis talk will present what
choices we had to make to build solution in such way and what some of our
challenges were.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N115 - Second Floor
SUMMARY:Look\, how we build geospatial CMS without using GeoServer and EAV!
- Edgars Košovojs
URL:http://talks.osgeo.org/foss4g-2023/talk/HMGBYV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MZCRNJ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:Road Surface Inspector is a system developed by IT34 with the p
urpose of speeding up the process of road damage registration by using dee
p learning. The time consuming process of inspection and registration of r
oad damage is reduced significantly by using our Road Scanner Inspector ap
p that can be placed in the windshield of any vehicle. The app records a v
ideo and gps coordinates\, which are later processed in order to find diff
erent types of damage - potholes\, cracks\, damaged markings using deep le
arning.\n\nThe system can also detect other types of assets such as traffi
c signs\, traffic lights\, manholes and others that can be used in fx digi
talization tasks.\n\nThe results of the image analysis are presented on a
webgis portal as heatmaps presenting the condition of the road in the area
s that were inspected using the app. The heatmaps are further used by the
decision makers in order to prioritize the road maintenance work. \n\nWhil
e using the app\, Gps logs are built in realtime based on the positions se
nt by the phone while driving. These are further used for street inspectio
n documentation.\n\nOpen source components.\nPostgres + Postgis for storin
g the data and for geometry based analysis\nPyTorch and Yolo7 for deep lea
rning\nOpenLayers for visualizing the images/detection results as rasters
in webgis\nGeoserver for publishing data as WMS/WFS\nQGis as an external v
isualization tool for the data
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Road condition assessment and inspection using deep learning - Bogd
an Negrea
URL:http://talks.osgeo.org/foss4g-2023/talk/MZCRNJ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-7SB9GL@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:Traffic signs are a key feature for navigating and managing tra
ffic safely\, affecting all of us on a daily basis. However\, traffic sign
datasets are lacking on open government data portals as well as OpenStre
etMap (OSM).\n\nMapillary’s computer vision capabilities can extract mor
e than 1\,500 classes of traffic signs globally from street-level imagery
. Generated traffic signs are available on iD Editor\, Rapid and JOSM Mapi
llary plugin to enrich OpenStreetMap data. \n\nOur team wanted to know how
the accuracy of traffic signs detected by Mapillary compared with the rea
lity on the ground (the ground truth). To answer this question we collecte
d more than thousands ground truth data in San Francisco and used this inf
ormation to produce the recall\, precision\, and positional accuracy of ou
r machined generated traffic sign data. This provided some interesting ins
ights in OpenStreetMap and the level of completeness and gaps of that data
set. \n\nIn this talk\, we will cover Mapillary’s traffic sign extractio
n capabilities\, Mapillary generated traffic sign data against ground trut
h data and OSM’s traffic sign coverage in San Francisco’s downtown. We
will be also addressing how data quality can be improved using various da
ta collection techniques and the role of post-processing with Structure f
rom Motion and control points annotations.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:A review of Mapillary Traffic Sign Data Quality and OpenStreetMap C
overage - Yunzhi Lin\, Said Turksever
URL:http://talks.osgeo.org/foss4g-2023/talk/7SB9GL/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-X9VD8J@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:The christmas bird count\, started by ornithologist frank chapm
an in 1900\, is one of the earliest and longest-running citizen science pr
ojects in the world. Today\, it involves thousands of birdwatchers who cou
nt birds over a 24-hour period in mid-december. The data collected during
the christmas bird count provides scientists with valuable information abo
ut bird populations\, migration patterns\, and other important ecological
trends. This project set the stage for the growth of citizen science initi
atives\, where people participate in scientific research.\nRecently\, ther
e has been an increase in the number of citizen (cyber-)science projects\,
which leverage the power of the internet and digital technology to involv
e people in scientific research. These projects have had a significant imp
act on society\, contributing to advancements in fields such as astronomy\
, ecology\, and health. While these projects can be a lot of fun\, sometim
es the tasks for participants can be really monotonous\, and they can lose
motivation to continue being a part of the project. Therefore\, project o
rganizers need to keep participants engaged. This is where gamification co
mes into play. Applying game elements to anything that isn't a game is kno
wn as gamification. Adding elements of competition and rewards can help pe
ople stay engaged in the project and continue making contributions (Haklay
\, 2012). This can be especially helpful for long-term projects that requi
re continual effort from participants. The openSenseMap(1) is an open-sour
ce(2) citizen cyber-science platform that facilitates environmental monito
ring by allowing individuals to measure and publish sensor data. The platf
orm is designed to create a community-driven network of sensors to monitor
various environmental factors\, such as air\, water quality\, and much mo
re. A significant advantage of the platform is that it operates on open da
ta principles\, whereby all sensor data\nis accessible to the public(3). T
his openness encourages collaboration and facilitates innovation\, which h
as led to numerous applications in environmental monitoring. Despite its s
uccess\, the platform still faces challenges regarding user engagement and
motivation\, necessitating the incorporation of gamification strategies t
o enhance participation.\nDigital badges can be earned in a variety of set
tings and are a recognized symbol of skill or accomplishment. Although bad
ges are a common gamification component\, they are typically only usable i
n closed environments. The possibility of awarding badges for voluntarily
participating in scientific research can increase participant motivation.
The ability to display\, share\, and verify badges alongside skills and cr
edentials from other environments has changed the game of digital credenti
als. This technology is called Open Badges.\nThis paper focuses on the mot
ivational impact Open Badges can have on citizen science in the context of
the openSenseMap platform. Users of the openSenseMap platform were survey
ed for this study. Based on the results\, a prototype was implemented\, co
mbining an open badge platform with the existing openSenseMap platform. Th
e prototype added an open badge component to the platform\, allowing users
to earn badges for various achievements\, such as contributing a certain
number of measurements or completing a specific task.\nThe badges were des
igned to be displayed on the users profiles and could be shared on social
media or other online platforms. This feature enabled participants to show
case their contributions and achievements\, increasing their motivation to
continue participating in the project. The survey results indicated that
participants found the open badge component to make the citizen science pl
atform more interesting\, which may suggest that open badges have the pote
ntial to increase motivation and engagement in citizen science projects.\n
Furthermore\, its important to note that the open badge platform (called m
ybadges(4) ) used in this project is open source(5)\, aligning with the sp
irit of collaboration and transparency in citizen science. By leveraging t
he power of open badges and open-source technology\, this project has the
potential to drive significant positive change in the field of cyber-scien
ce and promote reproducibility in scientific research.\nIn addition to its
potential impact on citizen cyber-science\, open badges can also be adapt
ed to the open (geo)education context. Open Badges can provide learners wi
th an opportunity to showcase their knowledge and skills in a tangible and
transferable way (Halavais\, 2012). A genealogy of badges: inherited mean
ing and monstrous moral hybrids). By earning badges for completing educati
onal tasks\, learners can build a portfolio of evidence that can be used t
o demonstrate their achievements and credentials. This can be particularly
valuable in fields such as geospatial science\, where there is a growing
demand for individuals with specific technical skills and knowledge. The u
se of\nOpen Badges in open (geo)education can enhance the learning experie
nce and increase learner motivation\, leading to improved educational outc
omes and better-equipped professionals in the field.\nThis paper explores
the use of Open Badges\, a gamification component\, to enhance engagement
and motivation in citizen cyber-science projects. The proposed approach us
es an open-source citizen cyber-science platform\, the openSenseMap\, to c
ollect and publish sensor data\, making it accessible to the public. The i
ncorporation of Open Badges can incentivize participants to contribute to
the project continually. The results of our survey indicated that particip
ants found the open badge component to be an engaging and motivating featu
re\, which suggests that Open Badges have the potential to increase engage
ment in citizen science projects. This papers contribution aligns with the
foss4g academic track audiences interest in exploring innovative approach
es to open-source technologys use to address environmental and social chal
lenges. Therefore\, this papers findings and implementation approach could
be of significant interest to the foss4g academic community.\n\n\n1 - htt
ps://opensensemap.org\n2 - https://github.com/sensebox/openSenseMap-API\n3
- https://docs.opensensemap.org\n4 - https://mybadges.org/public/start\n5
- https://github.com/myBadges-org/badgr-server
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Motivating environmental citizen scientists and open data acquisiti
on on openSenseMap with Open Badges - Frederick Bruch\, Mario Pesch
URL:http://talks.osgeo.org/foss4g-2023/talk/X9VD8J/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-S9XRPP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:Privacy aware Content Managment System (CMS) operators don't le
t their viewers accept cookies from an external map provider. But creating
a map used to require specialized GIS knowledge and hosting a map server
is not everyone's cup of tea.\n\nThis talk explains how non-experts can se
rve a map based on OpenStreetMap vector tiles from a CMS. A MapLibre GL JS
based Wordpress plugin displaying a self-hosted PMTiles dataset is shown
as an example.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N115 - Second Floor
SUMMARY:Self-hosted CMS maps for everyone - Pirmin Kalberer
URL:http://talks.osgeo.org/foss4g-2023/talk/S9XRPP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-8RZJ8C@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:MapServer\, a founding OSGeo projects\, has been powering mappi
ng systems since the mid 1990s. This talk gives an overview of the many fe
atures of MapServer that have been developed over the past 25 years\, with
a focus on advanced functionality that is not well-known as they deserve.
\n\nFeatures will be shown using sample Mapfiles - the configuration file
s used by MapServer. Examples will include advanced symbology\, special la
yer types such as graticules\, charts\, and contours\, displaying data fro
m S3 buckets\, and more!
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:MapServer Features by Example - Seth Girvin
URL:http://talks.osgeo.org/foss4g-2023/talk/8RZJ8C/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-CLG8X9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:**Mergin Maps** has become a popular open-source GIS platform f
or collecting\, managing and sharing geospatial data. In the past year\, w
e have introduced several new features and improvements to the platform. O
ur goal is to provide a flexible and powerful GIS solution that is accessi
ble to users of all levels\, from seasoned professionals to those just get
ting started. In this talk\, we will highlight the latest developments and
demonstrate how they can benefit users in various fields.\n\nOne of the s
ignificant updates is the **introduction of workspaces**\, which allows us
ers to organize their projects\, data\, and users in a hierarchical struct
ure. This new feature streamlines the management of multiple projects and
simplifies the process of adding and removing users.\n\nAnother update is
the implementation of **tracking**\, which enables users to collect and vi
sualize location data. This feature is particularly useful for tracking ve
hicles\, equipment\, and personnel in the field\, and can be customized to
include various attributes.\n\nFinally\, we will discuss the Mergin Maps
roadmap for the future\, including plans for new features\, enhanced integ
rations and community-driven development. We believe these changes will ma
ke Mergin Maps more accessible and user-friendly for everyone\, regardless
of their level of experience. \n\n**Whether you are a seasoned GIS profes
sional or new to the world of geospatial data\, this talk will provide val
uable insights into the latest developments in Mergin Maps and its potenti
al for your work.**
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Mergin Maps: A Year of Progress - Tomas Mizera
URL:http://talks.osgeo.org/foss4g-2023/talk/CLG8X9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-8TFHPG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:United Nations Development Programme (UNDP) is a United Nations
agency tasked with helping countries eliminate poverty and achieve sustai
nable economic growth and human development. \n\nRecent advances in techno
logy and information management have resulted in large quantities of data
being available to support improved data driven decision making across the
organization. In this context\, UNDP has developed a corporate data strat
egy to accelerate its transformation into a data-driven organisation. Geo-
spatial data is included in this strategy and plays an important role in t
he organization. However\, the large scale adoption and integration of geo
-spatial data was obstructed in the past by issues related to data accessi
bility (silos located in various country offices)\, interoperability as we
ll as sub-optimal hard and soft infrastructure or know-how.\nAll this iss
ues have been addressed recently\, when UNDP SGD integration started devel
oping a geospatial hub - GeoHub - to provide geospatial data visualisatio
n and analytical tools to UNDP staff and policymakers.\n\n[UNDP GeoHub](ht
tps://geohub.data.undp.org/) is a repository of a wide array of data sets
of the most recent time span available at your fingertips! It is a central
ized ecosystem of geospatial data and services to support development poli
cymakers. It allows users to search and visualise datasets\, compute dynam
ic statistics and download the data. In addition\, GeoHub provides a featu
re to share their maps with the community easily. With our repository\, yo
u can also upload to share your valuable data to share with the community!
It connects geospatial knowledge and know-how across the organization to
enhance evidence-based decision-making with relevant data-led insights.\n\
nGeohub ecosystem consists of [sveltekit](https://kit.svelte.dev/) & [mapl
ibre](https://maplibre.org/) based frontend web applications and various F
OSS4G software in the backend side. [PostgreSQL/PostGIS](https://postgis.n
et/)\, [titiler](https://developmentseed.org/titiler/)\, [pg_tileserv](htt
ps://github.com/CrunchyData/pg_tileserv) and [martin](https://martin.mapli
bre.org/) are deployed in Azure Kubernetes (AKS) to provide advanced visua
lisation and analysis for users. All source code is published in [Github](
https://github.com/UNDP-Data/geohub) with an open-source license.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:UNDP's one stop shop for cloud based geospatial data visualisation
and analytical tool - Jin Igarashi\, Joseph Thuha\, Samara Dilakshani Polw
atta Polwatta Lekamlage\, Ioan Ferencik
URL:http://talks.osgeo.org/foss4g-2023/talk/8TFHPG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-C9CVBF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:In this talk we introduce a European initiative with global eff
ects that aims to support the uptake of Earth Observation (EO) data produc
ts and services by increasing European capability to generate timely\, acc
urate\, disaggregated\, people-centred\, accessible and user-friendly envi
ronmental information based on EO data. The initiative - Open Earth Monito
r Cyberinfrastructure - is following a well defined workflow:\n(1) Identif
y gaps and needs analysis : finding out what are the bottlenecks of data p
latforms together with stakeholders\;\n(2) Use open source EO computing en
gine : integrating EO with in-situ data to obtain improved geospatial data
services and products\; \n(3) Build better data portals: harmonise\, brid
ge and improve existing open source platforms\;\nMake data platforms FAIR:
improve accessibility of data with open source licences and capacity buil
ding\; \n(4) Serve concrete goals: all Open Earth Monitor activities are c
entred around pre-defined use cases with various stakeholders. \n\nWe do n
ot plan to reinvent the wheel\, therefore all our efforts will focus on im
proving existing open source solutions and other initiatives\, such as: Op
enEO.org\, Geopedia.world\, GlobalEarthMonitor.eu\, EarthSystemDataLab.net
\, OpenLandMap.org\, EcoDataCube.eu.\, LifeWatch.eu\, XCUB and EuroDataCub
e.com. Our developments will materialise in a series of monitoring tools a
t European as well as global level in various fields: forestry\, natural h
azards\, biodiversity\, crop monitoring etc. \n\nIn the context of Open Ea
rth Monitor\, Cyberinfrastructure is defined as the coordinated aggregate
of software\, hardware\, human expertise and other technologies required t
o support current and future discoveries in science and engineering\, enab
ling relevant integration of often disparate resources to provide an usefu
l and usable framework for research\, discovery and decision-making charac
terised by broad access and "end-to-end" coordination. \n\nOpen Earth Moni
tor Cyberinfrastructure has received funding from the European Union's Hor
izon Europe research and innovation programme under grant agreement No. 10
1059548. (HORIZON-CL6-2021-GOVERNANCE-01).
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Increasing the uptake of Earth Observation services and products th
rough European efforts - Codrina Ilie
URL:http://talks.osgeo.org/foss4g-2023/talk/C9CVBF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GEMGWR@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:Are you interested in open geospatial tech for humanitarian pur
poses? Have you ever wondered who the people behind the geospatial techno
logies are? The collective brains? In this talk\, we will tap into the pow
er of the tech collective at Humanitarian OpenStreetMap Team\, share our e
xperience\, excite you about joining the collective and get some hands-on
input from YOU!\n\n\nMeet two members of the Humanitarian OpenStreetMap Te
am (HOT) - Petya & Synne. We are a global team that operates with four reg
ional Open Mapping Hubs: https://www.hotosm.org/hubs/. In developing and i
mproving open geospatial tech for humanitarian purposes\, our vision is to
creatively meet the needs of the communities through collective\, communi
ty-centered efforts. Our mission? To amplify community-led innovation for
impact through diversity\, creativity & passion!\n\n\nSome of the stories
we will share will be about our experiences and lessons learnt on collect
ive projects and products (https://github.com/hotosm/) ranging from the HO
T Tasking Manager collective \, collaborating with Kathmandu Living Labs (
KLL) in Nepal\, to development of a Field Mapping Tasking Manager (FMTM).
We will also share some of the boldest regional activities\, including Ope
nStreetMap (OSM) Hackfest in Asia Pacific and the Ideas Lab in Eastern and
Southern Africa.\n\n\nYou will also find out how YOU can get involved by
contributing to open geospatial tech. Expect a short participatory exercis
e [the collective brains/ power of collective intelligence] during this s
ession!
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:The power of collective intelligence: HOT’s approach to open tech
and innovation - Petya Kangalova\, Synne Marion Olsen
URL:http://talks.osgeo.org/foss4g-2023/talk/GEMGWR/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-AQMEEK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T113000
DTEND;TZID=Europe/Tirane:20230629T120000
DESCRIPTION:Gisquick (https://gisquick.org/) is an open-source platform for
publishing GIS projects on the web. A GIS project is defined by a QGIS pr
oject file including data sources (files\, databases\, even virtual layers
) and symbology defined in the QGIS desktop application using the styling
tool.\n\nWith the help of the Gisquick plugin for QGIS\, it is possible to
upload the data to the Gisquick server and host the map. \n\nGisquick is
a fully featured hosting platform\, where the project administrator can fi
ne-tune web publishing attributes\, set predefined scales\, bounds\, or vi
sibility. Also group permissions on the project level as well as layer lev
el (query\, edit\, export) may be defined. Vector data - geometry and attr
ibutes - can be edited directly on the web. \n\nInterface between the fron
tend and backend is based on open standards (OGC WMS and WFS). The mapping
application has standard components from the GIS point of view: decent la
yer switcher\, attribute table\, zoomable map\, printing tool (based on QG
IS templates)\, and customizable feature-detail form.\n\nAll this can be t
ested on our demo platform https://demo.gisquick.org/ - but you can also m
ake your own deployment via Docker images. Gisquick is open-source softwar
e published under the GNU GPL.\n\nIn the presentation\, we are going to pr
esent various features of Gisquick and show practical examples and discuss
technologies used for its development.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Gisquick: Let’s share (Q)GIS much quicker - Martin Landa\, Jáchy
m Čepický
URL:http://talks.osgeo.org/foss4g-2023/talk/AQMEEK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-SPFAKC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T120000
DTEND;TZID=Europe/Tirane:20230629T123000
DESCRIPTION:One of the primary motivations for the Open Mapping Hub Asia-Pa
cific to increase the quantity and quality of OpenStreetMap (OSM) data in
the region is the region's high exposure to multiple types of hazards.\n\n
Apart from assisting response efforts following a disaster event by provid
ing access to critical geospatial information\, the hub aims to ensure tha
t OSM data is already available in high-risk areas\, even before a disaste
r occurs\, to be used in critical anticipatory action such as developing e
arly warning systems and mitigation plans. It is critical to have a system
atic method for determining the OSM mapping requirements in these disaster
hotspots.\n\nAlthough some tools separately assess the Completeness of OS
M Data and the Disaster Risk Level of a location\, a new tool that combine
s these assessments is required to highlight the areas that should be prio
ritized for mapping in OSM.\n\nThe Open Mapping Hub Asia-Pacific created a
data-driven method for determining which areas in OSM disaster mapping sh
ould be prioritized. The resulting method is deployed as a QGIS plug-in an
d distributed to OSM communities for offline assessments to identify disas
ter-prone areas that have not yet been mapped in OSM.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Disaster Mapping Prioritization in OSM - Harry Mahardhika Machmud\,
Honey Fombuena
URL:http://talks.osgeo.org/foss4g-2023/talk/SPFAKC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RCX989@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T120000
DTEND;TZID=Europe/Tirane:20230629T123000
DESCRIPTION:Welcome to the Open Source Geospatial Foundation\, proud hosts
of FOSS4G\, and advocate for free and open source geospatial software ever
ywhere. This is a call out to open source software developers\; please joi
n OSGeo and help us help you!\n\nJoin OSGeo today:\n\n* Even just listing
your project on the osgeo.org website is a great first step. Help us promo
te your technology so users can discover and enjoy your software.\n* The O
SGeo “community program” gives project teams a chance to join the foun
dation with an emphasis on supporting innovation and new projects. The fou
ndation provides some direct support\, assistance along with endorsement a
nd recognition from our board.\n* For established projects please join our
“incubation program” to be recognized for excellence and as a full OS
Geo committee.\n\nUnlike other foundations OSGeo does not require that you
give up or transfer any Intellectual Property\; we simply ask that you be
spatial\, open-source\, and open to participation.\n\nThis presentation g
ives clear instructions on how to join OSGeo\, and representatives from re
cent successful projects will be on hand to answer your questions.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:How to join OSGeo (for projects) - Tom Kralidis\, Jody Garnett
URL:http://talks.osgeo.org/foss4g-2023/talk/RCX989/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-L7PEFD@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T120000
DTEND;TZID=Europe/Tirane:20230629T123000
DESCRIPTION:As cities expose people to increasing threats\, urban planning
perspectives on safety remain on the periphery of urban design and policy.
Public spaces cause different emotions in individuals\, and the feeling o
f safety is the primary emotion that affects their well-being and behavior
(Pánek\, Pászto\, & Marek\, 2017). For this reason\, an urban planning
strategy should pay special attention to providing a safe environment\, es
pecially in public spaces.\n\nNegotiating with the use of public spaces po
ses a more significant challenge for marginalized groups\, especially for
women in every social group for whom sexual harassment and other forms of
gender-based violence in public areas are a daily occurrence in every city
worldwide (UN Women\, 2021). Nonetheless\, there is a very limited amount
of data that showcases the level of safety of site-specific public spaces
\, especially for cities in developing countries like Kosovo.\n\nIn this r
egard\, aiming to contribute to the effort for developing a methodology fo
r assessing site-specific safety in public space\, we have developed SafoM
eter. SafoMeter is a methodological framework for assessing safety in publ
ic spaces and their spatial distribution. SafoMeter's approach adheres to
a human-centered approach that analyzes public spaces by looking closely a
t people's everyday experiences. Its framework is built by mediating indi
cators that assess both objective safety and subjective perceptions of saf
ety.\n\nThe objective indicators for measuring safety fall into two broad
categories: urban fabric and accessibility. Research on the relationship b
etween the built environment and perceived safety highlights several physi
cal components attributed to feelings of safety (UN-Habitat\, 2020). In ad
dition\, spatial criteria/features used in previous research include urban
structure and accessibility as two broad categories of spatial elements t
hat positively or negatively affect people's sense of safety (Wojnarowska\
, 2016). \n\nThe subjective indicators for measuring emotional safety fall
into the categories of threats and comfort. Contrary to conventional meth
ods\, the framework highlights the necessity for collecting data from the
individual evaluation of perceived safety. Subjective evaluations of the u
sers of public spaces are considered very important due to the low correla
tion between objective safety and subjective assessment of one's well-bein
g\, as shown in previous research (Von Wirth\, Grêt-Regamey & Stauffacher
\, 2014).\n\nThe pilot location used for applying SafoMeter’s methodolog
y to measure safety in public spaces was the urban area of Prishtina. The
official population of the Municipality of Prishtina is about 200\,000 inh
abitants\, of which almost 150\,000 live in the city area. Being the capit
al city of Kosovo\, the Municipality of Prishtina is the central city of s
ignificant political\, economic\, and social developments in the country.
\n\nThe data for each indicator of the SafoMeter methodology were collecte
d for a period of three months (July\, August\, and September 2022) at dif
ferent hours during the day. Mergin Maps application was used via mobile
phone to collect the field data recording both objective and subjective in
dicators. The data collection project was developed in QGIS\, version 3.2
2.12 LTR\, including 8 layers\, one for each indicator. A hexagonal grid o
f 0.86 ha was used to aggregate data into a Safety Index. Furthermore\, th
e results of the Safety Index were calculated and visualized via QGIS. A p
articular focus was drawn to visualizing unsafe hotspots in the city and s
howcasing their spatial distribution to inform citizens and decision-maker
s about spaces that need more urgent intervention.\n\nFor the Safety index
with a scale from 0 (least safe) to 10 (most safe)\, all spaces evaluated
in the study area result below half or with a maximum value of 5.57. Ther
efore\, it can be concluded that the indicators measured in Prishtina poin
t to an urgency for intervention\, both in physical infrastructure and in
terms of improving safety that comes as a threat from the human factor. Ad
ditionally\, besides being very few\, the areas considered safer within th
e city are not connected to each other\, not allowing users to move safely
from one place to another. Parks or green spaces\, which are scarce space
s in Pristina\, turn out to be amongst the main hotspots with the lowest s
core.\n\nApplying the SafoMeter methodology generated valuable insights fo
r assessing safety in the public spaces of Prishtina. The results of the p
ilot study reveal an urgent need for intervention. These findings suggest
that policymakers and urban planners should prioritize the creation of saf
er public spaces in Prishtina and other cities facing similar challenges.\
n\nAt the same time\, a systematic safety assessment requires systematic y
ear-round data collection processes to design effective area-based interve
ntions and policies. Therefore\, a more detailed\, further data collection
process should be established. In addition\, this process should aim at i
ncreasing the number of participating citizens in evaluating the safety in
dicators. All the data collected via the SafoMeter framework will be publi
shed via a web-based platform where different user groups can use them. Fi
nally\, via SafoMeter\, we aimed to provide a tool that can be replicated
for further studies by other users shared according to the principles of o
pen-source knowledge.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:SafoMeter - Assessing Safety in Public Spaces: The urban area of Pr
ishtina - Gresa Neziri
URL:http://talks.osgeo.org/foss4g-2023/talk/L7PEFD/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-7GNPH9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T120000
DTEND;TZID=Europe/Tirane:20230629T123000
DESCRIPTION:The mobile application QField is based on QGIS and allows field
work to be carried out efficiently based on QGIS projects\, offline or onl
ine. Developments in recent months have added additional functions to the
application that are useful for fieldwork. Examples are used to present th
e most important new features. Discover the most recent features like 3D-l
ayers handling\, printing of reports and atlases\, elevation profiling of
terrain and layers\, multi-column support in feature form\, azimuth values
in the measuring tool\, locked screen mode\, the QR-code reader\, stakeou
t functionalities\, the official release of the iOS version and many more.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:QField news - stakeout\, measurements\, printing and many more - Ma
rco Bernasocchi
URL:http://talks.osgeo.org/foss4g-2023/talk/7GNPH9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UFN9KV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T120000
DTEND;TZID=Europe/Tirane:20230629T123000
DESCRIPTION:When it comes to styling of geodata many tools have their own s
olution: SLD\, QGIS-Styles\, OpenLayers-Styles\, Leaflet\, …\n\nBut what
to do if you need to share the same style across different formats?\nGeoS
tyler brings the solution. With its standalone parsers\, nearly any (layer
based) style can be converted from one format to another - from SLD to Op
enLayers\, QGIS\, Mapfile\, and vice versa.\n\nOn top of this\, GeoStyler
offers a library of React UI elements to easily create styles in your own
WebGIS.\n\nThis talk will give an overview of possible use cases for GeoSt
yler\, its latest developments such as the new layout and the support for
expressions\, as well as past and upcoming community events.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:GeoStyler - One Tool for all Styles - Daniel Koch\, Jan Suleiman
URL:http://talks.osgeo.org/foss4g-2023/talk/UFN9KV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KLH8FN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T120000
DTEND;TZID=Europe/Tirane:20230629T123000
DESCRIPTION:G3W-SUITE is a modular\, client-server application (based on QG
IS-Server) for managing and publishing interactive QGIS cartographic proje
cts of various kinds in a totally independent\, simple and fast way.\n\nAc
cessing administration\, consultation of projects\, editing functions and
use of different modules are based on a hierarchic system of user profilin
g\, open to editing and modulation.\n\nThe suite is made up of two main co
mponents: G3W-ADMIN (based on Django and Python) as the web administration
interface and G3W-CLIENT (based on OpenLayer and Vue) as the cartographic
client that communicate through a series of API REST.\n\nThe application\
, released on GitHub with Mozilla Public Licence 2.0\, is compatible with
QGIS LTR versions and it is based on strong integration with the QGIS API.
\n\nThis presentation will provide a brief history of the application and
insights into key project developments over the past year\, including:\n *
new editing functions and greater integration with QGIS tools and widgets
in order to simplify the preparation of web cartographic management syste
ms\n * QGIS embedded project management\n * WMS-T and MESH data management
and integration of TimeSeries functions\n * on/off management for the ind
ividual symbology categories as in QGIS\n * integration of the QGIS Proces
sing API to allow the integration of QGIS analysis modules and perform onl
ine geographic analysis\n * structured management for log consultation on
three levels: G3W-SUITE\, QGIS-SERVER and DJANGO\n\nThe talk\, accompanied
by examples of application of the features\, is dedicated to both develop
ers and users of various levels who want to manage their cartographic infr
astructure based on QGIS
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:G3W-SUITE and QGIS integration: state of the art\, latest developme
nts and future prospects - Walter Lorenzetti
URL:http://talks.osgeo.org/foss4g-2023/talk/KLH8FN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-3FGPHE@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T120000
DTEND;TZID=Europe/Tirane:20230629T123000
DESCRIPTION:Europe is a world leader in Earth Observation (EO) and climate
change studies. An outstanding example is Copernicus\, the most ambitious
EO programme worldwide\, which in addition to being an independent system
is also a strong component of the Group on Earth Observation (GEO)\, an in
tergovernmental partnership aiming to improve the availability\, access an
d use of open EO to support policy and decision making in a wide range of
sectors.\nSince 2005\, the Global Earth Observation System of System (GEOS
S) has been a key initiative by GEO to integrate platforms and connect exi
sting infrastructures using common standards for sharing and using digital
resources. Europe is delivering a regional contribution to GEO\, named Eu
roGEO\, by covering the last mile of the EO value chain. However\, this re
gional node lacks the effective interoperability needed to implement a Eur
opean ecosystem to fully support the policy cycle. \nTo fill this gap\, th
e development of a sustainable EuroGEOSS ecosystem connecting many Europea
n assets including data\, sensor networks\, analytical methods and models\
, computing infrastructures\, products and services that support European
objectives (i.e. a EuroGEOSS ecosystem)\, is of a vital importance in the
evolution of the initiative. \nThe purpose of this talk is to present the
rationale and the development status of a EuroGEOSS prototype\, that the E
uropean Commission’s Joint Research Centre is conceptualizing.\nStarting
with the analysis of use cases with the highest European policy priority\
, five of them were identified as the prominent ones to be replicated. Alo
ng with the replication of use cases\, a monitoring framework of issues an
d gaps identified in the life cycle will be populated meanwhile. \nThe Eur
oGEOSS prototype architecture will implement the following patterns: a) Po
rtal and Single Sign On\; b) Meta catalogue of the services (data\, models
\, infrastructures\, etc.)\; c) High flexibility and modularity level\; d)
Adoption of the Machine Learning operation (MLOps) methodology. \nThe Eur
oGEOSS ecosystem is not conceived as another platform. It will rather be a
virtual platform leveraging on: a) open sources and open interoperability
standards (normative and de facto)\; b) interconnection of novel technolo
gies\; c) inclusion of relevant European communities such as those around
EuroGEO and INSPIRE\; d) Scalable interoperable infrastructures: CREODIAS\
, OpenEO\, etc.\nThe development of a EuroGEOSS prototype will last until
the end of 2024\, documenting the status of gaps\, challenges in the avail
able data and infrastructure\, as well as assisting a future scenario and
business model and a possible operationalization.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:EuroGEOSS Prototype Development - Albana KONA
URL:http://talks.osgeo.org/foss4g-2023/talk/3FGPHE/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-78MVUZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T133000
DTEND;TZID=Europe/Tirane:20230629T140000
DESCRIPTION:How do you create a near-real-time source of 3D geospatial data
from around the world?\n\nThe French Institute of Cartography and start-u
p Extra are collaborating to develop a decentralized protocol for this pur
pose. The Circum protocol will merge LiDAR datasets from various providers
\, sell this data source to consumers\, and redistribute the value back to
the original providers.\n\nCircum uses blockchain technology and 3D surfa
ce reconstruction algorithms to carry out its mission. Learn about the pro
tocol’s key mechanisms with the team at this conference.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Introduction to decentralized geospatial digital twins: merging all
LiDAR datasets in the world - Charlie Durand\, Bertrand Juglas
URL:http://talks.osgeo.org/foss4g-2023/talk/78MVUZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PCSCVS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T133000
DTEND;TZID=Europe/Tirane:20230629T140000
DESCRIPTION:The Hydro Network-Linked Data Index (NLDI) is a system that can
index data to a hydrographic network and offers a RESTful web service to
discover indexed information upstream and downstream of arbitrary points
along the stream network. This allows users to search for and retrieve geo
spatial representations of stream flowlines\, catchments\, and relevant wa
ter monitoring locations contributed by the water data community - without
downloading the national dataset or establishing links themselves.\n\nThi
s is done by data providers publishing open information about the location
s of their data within the context of the U.S. stream network. Data linked
to the NLDI includes various federal\, state and local water infrastructu
re features and water quantity and quality monitoring locations. The NLDI
is being developed as an open source project and welcomes contributions to
both its code and indexed data\, with the main implementation currently b
eing maintained by the U.S. Geological Survey. \n\nThe community of practi
ce surrounding the NLDI extends to R and python developers working on clie
nts that allow scientists to quickly retrieve data relevant for specific h
ydrologic analyses. As the NLDI community grows\, a similar concept could
be applied at a global scale\, facilitating the development of downstream
tools and applications. \n\nWhile the NLDI is limited to the US\, global w
ork would be possible by leveraging global stream network datasets such as
MERIT-Hydro. A proof-of-concept global River Runner allowing discovery of
the flowpath downstream of arbitrary points anywhere on Earth has already
been implemented using MERIT-Hydro and OGC-API Processes in pygeoapi. Thi
s session includes demonstrations of the NLDI and the global River Runner.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N115 - Second Floor
SUMMARY:River Runner: navigating and indexing hydrologic data with open sta
ndards and data - Benjamin Webb
URL:http://talks.osgeo.org/foss4g-2023/talk/PCSCVS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-88HDVN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T133000
DTEND;TZID=Europe/Tirane:20230629T140000
DESCRIPTION:PostGIS supports geometries with a Z dimension and geometries w
ith M (measure) values\, but there are not a lot of examples of *both* of
these being used together. One use case is the analysis of airplane tracks
which requires both - that is to say every vertex has an altitude and a t
imestamp. \n\nThis talk will show how live positional data transmitted fro
m aircraft can be accessed in a PostGIS database. I will then show how a s
equence of these positions can be represented effectively as LINESTRINGZM
geometries which can be analyzed as trajectories using native PostGIS func
tions.\n\nWith spatial SQL\, we can do things such as determine anomalous
changes in an aircraft's velocity or altitude and find the exact point in
time at which two aircraft came closest to one another. The focus on the t
alk will be showing how future work on large datasets of ADS-B data can be
done using PostGIS and other open-source geospatial tools.\n\nI will cove
r how to use Python and PostgreSQL's PL/Python language extension to impor
t the data and QGIS to render the data\, but the analysis will be be done
in SQL.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Aircraft trajectory analysis using PostGIS - Benjamin Trigona-Haran
y
URL:http://talks.osgeo.org/foss4g-2023/talk/88HDVN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-JWKDAF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T133000
DTEND;TZID=Europe/Tirane:20230629T140000
DESCRIPTION:3geonames.org is a free api for fast reverse geocoding\, using
a new technique of locality-preserving hashing of 2d/3d spatial points to
1d integers via a combination of Hilbert curve and bit interlacing. This t
alk expands on the use-case and the performance/accuracy advantages of thi
s technique. (The talk slides will be available at: https://3geonames.org/
prizren.html )
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Locality-Sensitive Hashing with the Hilbert Curve for fast reverse
geocoding - Ervin Ruci
URL:http://talks.osgeo.org/foss4g-2023/talk/JWKDAF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TARBCB@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T133000
DTEND;TZID=Europe/Tirane:20230629T140000
DESCRIPTION:Since April 2022 I've been manipulating projected digital maps
in collaboration with improvising musicians\, dancers\, and spoken word ar
tists across Europe and North America. Constraining my project to use only
web mapping technologies\, "A Synesthete's Atlas" is a curious mutation o
f expanded cinema\, applying strategies from experimental film & animation
\, color theory\, the Light and Space movement\, and concrete poetry to ge
ography.\n\nI'll present Carto-OSC\, an assemblage of open source librarie
s\, data\, and protocols\, plus 1000+ lines of JavaScript that integrates
it all into a touch-surface interface. I'll discuss my motivations and use
of the OSC protocol to control the manipulations\, offer aesthetic observ
ations\, and present video excerpts of previous performances.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:A Synesthete's Atlas: Performing Cartography in Real Time - Eric Th
eise
URL:http://talks.osgeo.org/foss4g-2023/talk/TARBCB/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-YKYL9N@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:This paper aims to clarify the state of development of highly a
ccurate and open 3D city model data and its usage methods\, which started
in Japan in 2020\, from two aspects: quantitative geospatial analysis usin
g publicly available data\, and qualitative evaluation analysis of 40 use
cases using the data.\n\nAs a background to this study\, digital twins\, w
hich are virtual replicas of the physical urban built environment (Shahat
et al.\, 2021)\, are gaining global attention with the development of geos
patial information technology to understand current conditions and plan fu
ture scenarios in cities (Lei et al.\, 2022). This trend can be applied in
areas related to a wide range of urban issues\, such as urban development
\, disaster prevention\, and environmental and energy simulation\, and has
the potential to be used for urban planning through an intuitive approach
via various GIS tools. On the other hand\, the geospatial information req
uired by the digital twin also needs to be accompanied by three-dimensiona
l shape information and many attribute information of building units. Data
development and related research using CityGML (Kolbe et al.\, 2021)\, a
representative standard specification\, has mostly been carried out in Eur
opean and US cities\, and there have been few efforts in Asia (https://git
hub.com/OloOcki/awesome-citygml).\n\nIn Japan\, urban planning has mainly
been carried out using analogue methods such as paper maps and window serv
ices. However\, as citizens' lifestyles and socio-economic systems are dra
stically changing due to the high interest in smart cities and the spread
of COVID-19 infection\, urban policies such as disaster prevention and urb
an development using digital technology are becoming increasingly importan
t. The digital transformation of urban policies such as disaster preventio
n and urban development using digital technology has become an urgent issu
e. “Project PLATEAU (https://www.mlit.go.jp/plateau/)” is a project in
itiated in 2020 under the leadership of the Ministry of Land\, Infrastruct
ure\, Transport and Tourism (MLIT) to develop a high-precision 1:2500-leve
l 3D city model CityGML format in a unified manner and convert it into ope
n data format via CKAN's data portal (CityGML\, 3D Tiles\, GeoJSON\, MVT\,
ESRI Shapefile)\, to develop an open-source data viewer and to explore us
e cases.\n\nThis study details the history of the "Project PLATEAU" initia
tive and discusses the relationship between openness and urban data common
s. Many of the data specifications\, converters and online viewers are clo
sely related to FOSS4G. Next\, data for 126 cities in Japan (about 19\,000
square kilometers) developed as open data over a three-year period are re
gionally aggregated and then quantitatively compared with OSM building dat
a in Japan. Trends such as coverage rates between cities and micro-regiona
l analysis within Tokyo are then attempted. To analyze a large amount of d
ata\, this part was carried out using data converted to FlatGeobuf format.
\n\nSome of the results of the data preparation analysis are as follows: T
he basic analysis of the cities covered by PLATEAU showed that the total n
umber of buildings in LOD1 was about 15.7 million\, with a population cove
rage of about 38.4%. These cities have shown an increasing trend in popula
tion over the last five years (an average of about +10\,000 for the 126 ci
ties). By comparison\, the total number of OSM buildings in the country is
about 12.7 million\, generally widely distributed across the country's 19
03 administrative districts (about 38\,000 square kilometers). Therefore\,
only the cities maintained by PLATEAU provide data with a higher level of
detail than OSM. However\, the detailed LOD2 building data with roof shap
e is limited to about 480\,000 buildings (about 300 square kilometers in 9
7 cities nationwide)\, which are high-rise buildings and landmarks in larg
e cities.\n\nTo identify more micro trends\, we compared the accuracy of t
he building data for central Tokyo\, which has the largest number of units
in both datasets\, in 2020\, the year the PLATEAU data was created. The n
umber of units in each building dataset is OSM (726\,685 units) and PLATEA
U (1\,768\,868 units). When PLATEAU is used as the base data\, the coverag
e of OSM is about 40%. On the other hand\, of the 3190 city blocks in cent
ral Tokyo\, 502 (about 15.7%) were identified as having more OSM buildings
than PLATEAU. As a factor contributing to this discrepancy\, a historical
analysis of the timestamps and versions of the building data (about 80\,0
00 units) that exist only in OSM revealed that most of them were created m
ore than two years before the PLATEAU data and have never been updated. Th
erefore\, the PLATEAU data should be updated to keep the data fresh\, even
in areas where OSM data are already widely distributed\, if only data old
er than 2020 are maintained.\n\nFor example\, open 3D urban model data for
cities of various sizes have been released in Japan\, and they are highly
accurate and complementary to OSM data. In addition\, these data have beg
un to be used in administrative practice\, and a total of 44 applications
in new areas such as citizen participation and entertainment (especially s
ervices using XR) have been identified. The evaluation of the exploitation
methods is explained in the paper\, but the cases related to smart cities
and disaster prevention are particularly striking. The issues to be addre
ssed in these efforts are the nationalization of the scope of maintenance\
, the organic merging with open data as represented by OSM\, and the furth
er GIS education in the field of urban planning. Finally\, as data contrib
uting to the reproducibility of this study\, the data sources used in the
analysis are themselves open data and thus readily available. Therefore\,
we plan to provide a download list of each data source and GIS data summar
izing the tabulation results as open data on Github.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:The Role of 3D City Model Data as an Open Digital Commons: A Case S
tudy of Openness in Japan's Digital Twin "Project PLATEAU” - Toshikazu S
eto
URL:http://talks.osgeo.org/foss4g-2023/talk/YKYL9N/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-VDJEEH@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:Climate change’s impact on public transportation tends to foc
us on improving transit infrastructure to reduce stoppages. While this is
important\, it does not take into account the effect it has on communities
\, often already underserved\, that rely on the transit system. As part of
The Opportunity Project’s Building Climate Change Resilience Through Pu
blic Transit sprint\, our team at Data Clinic set out to develop an open s
ource\, user-friendly\, and scalable tool to communicate intersectional ri
sks faced by transit infrastructure and community access at the local leve
l. This solution was inspired by both the event\, and user research with k
ey stakeholders in transit agencies\, academia\, and community organizatio
ns.\nIn this presentation\, we will demonstrate TREC: Transit Resiliency f
or Essential Commuting\, and expose key decisions that resulted in a geosp
atial solution designed for wide audiences\, and geographic and data scala
bility. TREC’s transit stop-level insights can become crucial tools for
transit planners and community organizations to prioritize and advocate fo
r infrastructure improvements that take community effects into account.\nF
ocused initially on two locations- one small (Hampton Roads\, Virginia) an
d one large (New York City) transit system\, each station is treated as a
destination providing access to essential services during localized climat
e change events. In this MVP\, we employ flooding as our climate scenario\
, the event most cited as recurring and disruptive by our stakeholders. \n
Using OpenStreetMap to calculate walksheds around each station obtained fr
om GTFS data\, we categorize importance in accessing essential services su
ch as hospitals and jobs around a transit stop. Layered onto this\, we bin
current flood risk for each station using the prevalence of buildings wit
h moderate- to extreme high-risk of flooding according to open data\, and
provide polygons representing projected flood risk in 2050.\nWhile we buil
t the TREC UI to maximize accessibility of this contextualized data to mul
tiple stakeholders\, we also seek to optimize usability of the repo to all
ow tech-mature transit planners to adopt the tool internally and incorpora
te their proprietary fine-grained data. Further\, we are committed to expa
nding the functionality of TREC according to user feedback. \nThe threat o
f climate change disrupting daily life on a recurring basis\, beyond large
-scale disasters\, continues to grow. With the help of this tool\, we hope
to democratize relevant data\, inspire the open publication of localized
geospatial data related to climate change\, and enable human-centered deci
sionmaking through a multidimensional lens.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N115 - Second Floor
SUMMARY:Transit Access to Essential Services in the face of Climate Change
- Kaushik Mohan\, Erin Stein
URL:http://talks.osgeo.org/foss4g-2023/talk/VDJEEH/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-Z8MBEZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:PDAL is Point Data Abstraction Library. It is a C/C++ open sour
ce library and applications for translating and processing point cloud dat
a. It is not limited to LiDAR data\, although the focus and impetus for ma
ny of the tools in the library have their origins in LiDAR. PDAL allows yo
u to compose operations on point clouds into pipelines of stages. These pi
pelines can be written in a declarative JSON syntax or constructed using t
he available API. This talk will focus on the current state of the PDAL Po
intcloud processing library and related projects such as COPC and Entwine\
, for pointcloud processing. Coverage of the most common filters\, readers
and writers along with some general introduction on the library\, coverag
e of processing models\, language bindings and command line based batch pr
ocessing. First part will be covering new features for current users. Some
discussion of installation method including Docker\, binaries from packag
e repositories\, and Conda packaging. For more info see https://pdal.io
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:State of PDAL - Michael Smith
URL:http://talks.osgeo.org/foss4g-2023/talk/Z8MBEZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QZGN3K@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:GeoServer deployments in the cloud and kubernetes are becoming
the norm\, while the amount of data published is also growing\, both in te
rms of layers and size of data. As a result\, the need for scaling up is b
ecoming more and more common.\n\nThis presentation covers GeoServer cluste
ring approaches\, comparing the available options and their suitability to
different environments. We will cover:\n* Managing the GeoServer configur
ation\, stable configuration with planned upgrades versus dynamic runtime
changes.\n* Deployment options (monolithic\, separate tiling\, microservic
e oriented)\n* Dynamic configuration clustering with JMS\, external databa
se storage\, and distributed memory.\n\nAttend this presentation to get an
update on GeoServer cloud and clustering options\, and pick the option th
at is the best match for your specific use case.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Scaling GeoServer in the cloud: clustering state of the art - Andre
a Aime
URL:http://talks.osgeo.org/foss4g-2023/talk/QZGN3K/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZPQPMQ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:Talk for the HOTOSM Tasking Manager.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Modernising Tasking Manager Infrastructure - Yogesh Girikumar
URL:http://talks.osgeo.org/foss4g-2023/talk/ZPQPMQ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XEN89T@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:GTFS is stands for General Transit Feed Specification\, which i
s developed by Google and used for describing schedules of public transpot
ation. A bunch of dataset is distributed in the world and GTFS includes ge
ospatial information - stops and routes. To utilize such intresting data\,
we have developed GTFS-GO - QGIS plugin to process GTFS. You can translat
e GTFS to GIS data and visualize them by GTFS-GO. The plugin can be used f
or analyzing public transportaion by aggregating traffic frequencies on ea
ch stop or route. In this talk\, you can see how GTFS is visualized or ana
lyzed by using GTFS-GO on QGIS.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Traffic Analysis with QGIS and GTFS: GTFS-GO - IGUCHI Kanahiro
URL:http://talks.osgeo.org/foss4g-2023/talk/XEN89T/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-8GZUDQ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:In a context of digital transition and the increasing availabil
ity of urban data\, Rennes Métropole wishes to better equip its decisions
and public policies on the basis of data and cooperation.\n\nUltimately\,
the goal is to :\n- Promote cooperation and the contribution of the actor
s of the territory\, in particular the citizens\n- "Enlighten" public deci
sions and policies\, in particular the democratic\, ecological and energy
transition projects carried out by Rennes Métropole.\n\nIssues of transpa
rency\, public service efficiency and cost control are also sought.\n\nThe
metropolitan cooperation platform that is currently developed will consis
t of one or more tools based on the digital twin intended to equip public
decisions and policies on the basis of data and cooperation.\n\nThe platfo
rm is developed partly on VC Map which is an Open-Source JavaScript framew
ork and API for building dynamic and interactive maps on the web. It can d
isplay 2D data\, oblique imagery and massive 3D data including terrain dat
a\, vector data\, mesh models\, and point clouds making it easy for users
to explore and interact with the data in an integrated and high-performanc
e map application. VC Map is built upon open\, proven\, and reliable GIS
and web technologies such as OpenLayers and Cesium for the visualization o
f 2D and 3D geo-data.\n\nA particular effort was made on the design in ord
er to offer users\, mainly citizens of Rennes Metropole\, a pleasant user
experience that allows an exploration of the development projects of the m
etropole in 2D and 3D.\n\nWe will present the cooperation platform through
three use cases of interest for Rennes Metropole : \n\nSolar Cadaster : S
imulation of the photovoltaic production potential of the roofs and compar
ison with the energy consumption of the residents\, the costs and the capa
city of the network.\n\nLinear transport systems : Mediation (including vi
sualization) and consultation with citizens and communities for the implem
entation of a linear transport infrastructure\n\nExposure to electromagnet
ic waves : Visualization of exposure levels to electromagnetic waves (simu
lations and real and real measured values) as well as objects (radioelectr
ic relays and sensors) on the territory of the City of Rennes.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:CesiumJS and OpenLayers for a metropolitan cooperation web platform
based on the digital twin of Rennes Métropole. - Frederic Jacon\, Ben Ku
ster
URL:http://talks.osgeo.org/foss4g-2023/talk/8GZUDQ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FSFARL@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:GIS instructors at an American technical college have created a
five-course certificate in GeoAI. The first cohort of undergraduate stud
ents has completed the degree requirements two years later. This presentat
ion will discuss the formation for the degree\, the courses\, and the resu
lting graduates. The presentation will discuss the learning outcomes for
the degree and individual AI and machine learning GIS courses.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Introducing GeoAI Technology to Undergraduates in Public Two-Year C
ommunity Colleges - Phillip Davis
URL:http://talks.osgeo.org/foss4g-2023/talk/FSFARL/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TSVXVG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:In this talk\, I'll share some practical tips and tricks for ma
naging an enterprise GIS workflow with QGIS and PostGIS. I'll showcase som
e real-world examples to highlight the benefits of using a centralized spa
tial database to manage GIS data\, and I'll walk through the steps to set
up a QGIS project for creating\, updating\, and deleting data directly fro
m QGIS. \n\nMy goal is to help organizations that are planning to set up a
PostGIS-powered QGIS workflow and are looking for innovative ways to maxi
mise the benefits of the joint powerhouse of QGIS and PostGIS.\n\nAs we di
ve deeper\, I'll explore some of the key technical aspects of using QGIS a
nd PostGIS for enterprise GIS. I'll share some tips for configuring and in
tegrating the tools\, and showcase how to set up an easily accessible end-
user workflow for creating and editing data in QGIS using QGIS forms.\n\nT
hroughout the talk\, I'll also share some stories from different projects
to illustrate how these tips and tricks have been successfully applied in
practice. I will do my best to ensure that you’ll leave the talk with an
understanding of the benefits of using QGIS and PostGIS as part of their
Enterprise GIS workflows.\n\nWhether you're a GIS professional\, team lead
er / project manager or anyone seeking to optimize their GIS data manageme
nt\, this talk will provide valuable insights and practical advice for opt
imizing your GIS data management. Join me as we explore the power of open
source tools for enterprise GIS!
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Lessons from Successful Enterprise GIS Implementations with QGIS an
d PostGIS - Santtu Pyykkönen
URL:http://talks.osgeo.org/foss4g-2023/talk/TSVXVG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FNMERN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:Use case for the implementation of a platform that supports dat
a that contributes to the publication and management of Digital Twins\, ba
sed on the use of MapLibre as a web viewer and at the same time consuming
information from different geospatial sources\, including Mesh\, Raster\,
DEM\; and near real time data sources such as OneBusWay or OpenTripPlanner
based on GTFS formats\, for the comparison and analysis of information.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Implementing Digital Twin City in MapLibre with the integration of
different information sources - Ariel Anthieni\, Sebastian Lopez
URL:http://talks.osgeo.org/foss4g-2023/talk/FNMERN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UYZFZT@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:Our talk presents an initiative that works to develop an open\,
interactive\, user intuitive platform for a constantly updated\, comprehe
nsive and detailed overview of the dynamic environment of the open source
digital infrastructure for geospatial data storage\, processing and visual
isation systems. OSS4gEO is designed as a repository that functions as an
extended metadata catalogue\, curated by the community and a tool for metr
ics computation\, visualisation\, ecosystem statistical analysis and repor
ting.\n\nThe initial development of the Open Source for Geospatial Softwar
e Resources platform builds on previous extensive work started in 2016 tha
t has materialised into a pioneering overview of open source solutions for
geospatial\, voluntarily updated by the team. Starting in 2023\, OSS4gEO
has become a part of a wider ESA EO Open Innovation initiative to actively
support and contribute to the EO and geospatial open source community and
it is intended as a seed action to better understand\, represent and harv
est the geospatial open source ecosystem. \n\nThere are 3 main objectives
that OSS4gEO aims to achieves: \n(1) It aims to offer an informed and as c
omplete as possible overview of the open source for geospatial and EO ecos
ystem\, together with various capabilities of filtering and visualisations
\, within the platform as well as technical solutions to programmatically
access and extract data from the database (APIs) to use in any purpose\, i
ncluding commercial\;\n(2) It aims to provide guidance through the complex
ity of the geospatial ecosystem so that one can choose the best solutions\
, while understanding their sustainability\, technical and legal interoper
ability and all the dependencies levels\;\n(3) It aims to serve as a commu
nity building\, a promoting and maintaining platform for new and innovativ
e open source solutions for EO and geospatial\, developed within various p
rojects\, research centres\, small or large companies\, universities or th
rough individual initiatives. \n\nOur talk will outline the OSS4gEO initia
tive as a community-led\, bottom-up initiative\, highlight current and fut
ure developments and co-development activities and introduce the wider ESA
EO Open Innovation context.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Open Source for Geospatial Software Resources Platform for Geospati
al Data Exploitation – OSS4gEO: community led Open Innovation at ESA and
beyond - Stefanie Lumnitz\, Codrina Ilie
URL:http://talks.osgeo.org/foss4g-2023/talk/UYZFZT/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GDFREX@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T140000
DTEND;TZID=Europe/Tirane:20230629T143000
DESCRIPTION:The Model of Living Landscape (MLL) is a set of empirical based
tools for land management and landscape planning. It recognizes the compl
exity of the interactions between humans and the natural environment\, and
it aims to create a sustainable and resilient landscape that supports the
well-being of both people and nature. One of the core MLL components is a
process-based model for rainfall-runoff and erosion computation called SM
ODERP. The model operates on the principle of cell-by-cell mass balance\,
calculated at each time step. SMODERP (https://github.com/storm-fsv-cvut/s
moderp2d) is open-source software implemented in Python language to ensure
compatibility with most GIS software solutions. The current implementatio
n supports Esri ArcGIS\, GRASS GIS and QGIS. In this contribution\, a new
QGIS SMODERP plugin linking the hydrologic model outputs to MLL will be pr
esented. The plugin performs the input data preparation on the background
using GRASS GIS data provider\, computation is done by SMODERP Python pack
age\, and results visualised with predefined map symbology in QGIS map can
vas. \n\nThis contribution was supported by grant RAGO - Living landscape
(SFZP 085320/2022) and Using remote sensing to assess negative impacts of
rainstorms (TAČR - SS01020366).
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Connecting SMODERP with Living Landscape - QGIS Plugin - Martin Lan
da\, Ondřej Pešek\, Petr Kavka
URL:http://talks.osgeo.org/foss4g-2023/talk/GDFREX/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-9PWWJX@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:Pointview is a product developed by IT34 for working with Lidar
and Photogrammetry data. It gives the user the possibility to upload\, p
rocess\, visualize and work with data. \n\nLidar data formats such as LAS\
, LAZ\, E57 can be uploaded\, processed and visualized in the browser.\n\n
Photogrammetry: Images from drones or video from phones can be uploaded\,
processed into a 3d point cloud and visualized in a browser. \n\nIn additi
on\, data can be captured using our SmartSurvey app that captures video wh
ich is used for building a 3d pointcloud\, together with an ortophoto and
dem. The data is later available for visualization in Pointview or in QGIS
though a WFS service.\n\n\nMoreover\, the system offers a complete manage
ment system where the user can create projects for organizing the data\, c
an share the data with other users and manage the access.\n\nThe system us
es various data processing workflows for data processing based on open sou
rce components such as:\nPostgresSql + Postgis for storing the data and fo
r geometry based analysis.\nOpenLayers for visualizing the images and grou
nd control points results as rasters\nGeoserver for publishing data as WMS
/WFS\, \nQGis for visualizing data\,\nPDAL for lidar data processing\, \nG
DAL for raster data processing\, \nCloudCompare for lidar data processing\
, \nPotree for Data Visualization
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Lidar data processing\, management and visualisation in a browser u
sing Pointview - Bogdan Negrea
URL:http://talks.osgeo.org/foss4g-2023/talk/9PWWJX/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-SJNCBD@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:At the National Land Survey of Finland (NLS) we are developing
multiple QGIS plugins\, and we needed a way to share the common code and b
reak the components to smaller independent plugins while still providing a
good developer experience. \n\n \n\nOne of the main issues when sharing l
ibrary code between different QGIS plugins is the runtime environment unce
rtainty. Since Python import machinery is not easily configurable to suppo
rt multiple versions of dependencies (like nested node_modules in nodejs-w
orld)\, the runtime is limited by default to a single version of a library
\, and later access to the same module is cached. This limits the version
available to all plugins in a single QGIS session to the code that is firs
t run\, which makes sharing code difficult\, especially when breaking API
changes are necessary to the dependency library code. \n\n \n\nAt NLS we d
eveloped tooling to work around these limitations\, which improves the dev
eloper experience and allows sharing of common QGIS plugin code easily via
standard Python libraries. Tool provides a streamlined developer workflow
and necessities like typing and IDE helpers\, and a way to package a plug
in that depends on other standard Python libraries. \n\n \n\nDevelopment e
nvironment for a QGIS plugin can be initialized simply by using a virtual
environment\, installing the dependencies and launching QGIS with the plug
in and its dependencies fully setup. This works with bootstrap code passed
on the command line\, which will provide QGIS access to the virtual envir
onment\, setups the plugin from the environment with access to any library
dependencies. Tool also provides a debugger session and could also provid
e for example hot reload signals for the plugin when code is changed. This
provides a quicker and easier feedback cycle for the developer and simpli
fies the workflows when developing QGIS plugins. \n\n \n\nRuntime dependen
cies are reorganized at build-time to be imported for a sub-package of the
plugin\, so only the exact packaged version of a dependency is used at ru
ntime. This works by rewriting external library dependency import statemen
ts in the source code. Tool also generates the metadata.txt file in a way
that is compatible with standard Python packaging tools\, for example setu
ptools. This allows easily sharing the same code both as Python library an
d as a QGIS plugin.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Improving QGIS plugin developer experience - Antero Komi
URL:http://talks.osgeo.org/foss4g-2023/talk/SJNCBD/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-EZNJ8U@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:The LH Urban Digital Twin Platform is a comprehensive solution
for new town planning and development that utilizes open source digital tw
in technology. The platform combines real-world data with spatial informat
ion context to offer a three-dimensional sharing/collaboration integration
support system. \n\nDevelopers will appreciate the platform's flexibilit
y and scalability\, which are based on a microservice architecture that co
nnects multiple modules independently and loosely. The platform utilizes o
pen standards WMS\, WFS\, WCS\, WPS OGC Web Service standard features thro
ugh GeoServer and GeoWebCache\, a tile cache server that accelerates map d
elivery built into GeoServer. Additionally\, the platform supports visuali
zation of data in various formats using mago3D\, F4DConverter\, and Smart
Tiling. \n\nThe platform offers a range of services\, including automatic
apartment building placement\, construction site safety management\, 3D u
rban landscape simulation\, environmental planning simulation\, and underg
round facility visualization simulation. The platform also features real-t
ime monitoring and visualization of IoT-based data\, which is of particula
r interest to developers interested in smart city development. \n\nFirstl
y\, the presentation will show how open source based digital twin visualiz
e the complex 3D city models in a web browser. Secondly it will showcase t
he platform's features and data\, including actual system's functions and
service UI/UX through a video. Attendees will gain insights into how the p
latform can be used to support rational decision making during complex urb
an planning\, design\, development\, and operation stages. \n\nThis prese
ntation is of interest to developers working in the field of urban plannin
g\, design\, and development\, as well as those interested in open source
digital twin technology. \n\nLH Corp is one of the largest public compani
es in Korea providing land and housing for public purpose. They are owned
and controlled by the Korean government. They’ve played a large role in
new town development and housing welfare.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Open Source Basded 3D City Model Visualization - A LH Urban Digital
Twin Case - Cheun-gill Park\, Hansang Kim
URL:http://talks.osgeo.org/foss4g-2023/talk/EZNJ8U/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PYLQHC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:### Background \n\nCities are home to 72% of the population in
Europe and account for 70% of the energy consumption. Being particularly v
ulnerable to climate change impacts\, urban areas play a key role in carbo
n mitigation and energy transition. It is\, therefore\, of particular impo
rtance to increase renewable energy production for urban areas and cities.
\n\nCities urgently require information about their potential for renewab
le energy production to target ultra-sustainable policies. Luxembourg has
set very ambitious goals with its Plan National Intégré Énergie Clim
at (PNEC). It describes policies and measures to achieve ambitious nationa
l targets for reducing greenhouse gas emissions (-55%) as well as pushing
renewable energy production (+25%) and energy efficiency (+40-44%) by 2030
. \n\nPublic authorities often lack the expertise in integrated assessment
and relevant simulation tools to support scientific evidence-based decisi
ons about energy strategies\, enhance interaction with stakeholders and ac
celerate energy transition. The main outputs of this study are related to
the demonstration of the role of interoperable geographical digital twins
based on Free and Open-Source software and geospatial software technologie
s in the simulation\, monitoring and management of the current and near fu
ture renewable-based energy systems. \n\n \n\n### Approach and Concept \n\
nThe scope of the presented work is to demonstrate the role of a 3D geogra
phical urban digital twin in the context of a high penetration and optimis
ed installation of PV and the impact of its power generation on the grid.
Free and Open-Source software technologies build the basis of a web platfo
rm which implements a geographical digital twin based on open data\, open
OGC standards to build a fully interoperable Digital Twin. This allows the
integration of open 3D CityGML data with simulation algorithms of renewab
le potentials and the energy grid system all into one technical interopera
ble architecture. \n\nThe objective of this study is to simulate the poten
tial for building integrated and building attached solar photovoltaic (PV)
electricity generation in use case cities\, and later to scale up the res
ults to a nationwide level. The approach taken involves several key steps:
\n\n1. Estimation of electricity consumption of the building stock at loc
al level\, in order to understand the demand for electricity and the poten
tial for PV generation. \n\n2. Simulation of the electricity generation po
tential of building-integrated and building-attached PV systems\, consider
ing factors such as rooftop and facade orientation and shading effects. \n
\n3. Development and analysis of scenarios for different PV technologies\,
including consideration of techno-economic parameters such as feed-in-tar
iffs\, lifetime of installation\, efficiency\, and power consumption. \n\n
4. Selection of optimal locations for PV placement across the city\, based
on a combination of rooftop and facade suitability\, electricity demand\,
and electricity grid nodes. \n\n5. Implement all steps into an interopera
ble web-based decision support platform providing advanced simulation and
assessment tools using high resolution open building information. \n\n \n\
n### Results \n\nGeospatial software technologies and 3D and 4D algorithms
are building the core of the platform (based on iGuess®) to enable the p
lanning of PV electricity generation from the local to the national scale.
Global solar irradiation is simulated for each roof-top and façade at a
very high resolution\, taking into account 3D shading effects of the surro
undings in the urban environment. Scenarios for different PV technologies\
, feed-in tariffs and cost efficiencies and amounts of PV installations ar
e computed to show impacts of spatio-temporal differing PV generation. Thi
s simulates the large increase of PV installations required to accelerate
the development of sustainable energy and climate action plans (SECAPs) fo
r all municipalities in Luxembourg and the entire nation. \n\nThe develop
ed platform serves multiple beneficiaries\, e.g.\, Municipalities\, urban
planners etc. to support 3D based realistic urban energy planning. Citizen
s and energy communities can help shape their city and get access to high
resolution information. This platform provides a tool for estimating long-
as well as short- and mid-term PV power generation at high resolution acr
oss entire neighbourhoods and districts generating time-series data. \n\nF
urthermore\, we have implemented tools for the identification of cost-effi
cient PV placement/integration in buildings on roof-tops and facades to te
st the different scenarios and allow for interactive selection for optimal
PV placement identification across the study area. \n\n \n\n### Conclusio
ns \n\nThis paper presents the importance of geographical digital twins pr
oviding the core platform for the current energy transition from fossil fu
els to renewables. The advantage of an interoperable geographical urban di
gital twin\, as proposed here\, provides the flexibility necessary to simu
late and test scenarios for rapid\, integrated urban planning under climat
e change. Based on open-source\, open standards and open APIs\, open data\
, simulation and assessment methods and tools can be seamlessly integrated
to provide a 3D real world environment to assess and develop energy trans
ition approaches. Different stakeholders\, such as citizens\, municipaliti
es and businesses can act and be stimulated to enable a faster transition
to renewable energy and harvest the full potential of improved urban plann
ing based on geographical Digital Twin technologies.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:An interoperable Digital Twin to simulate spatio-temporal photovolt
aic power output and grid congestion at neighbourhood and city levels in L
uxembourg - Ulrich Leopold
URL:http://talks.osgeo.org/foss4g-2023/talk/PYLQHC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-K3SNQM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:In Norway we now get more up-to-date maps for land resource map
(AR5)\, because the domain experts on agriculture in the municipalities i
n Norway have got access to a easy to use client. This system includes a s
imple web browser client and a database built on Postgis Topology. \n\nIn
this talk we will focus on\, what is it with Postgis Topology that makes i
t easier to build user friendly and secure tools for updating of land reso
urce maps like AR5. We will also say a couple of words about advantages re
lated to traceability and data security\, when using Postgis Topology.\n\n
In another project\, where we do a lot ST_Intersection and ST_Diff on many
big Simple Feature layers that covers all of Norway\, we have been strugg
ling with Topology exceptions\, wrong results and performance for years.
Last two years we also tested JTS OverlayNG\, but we still had problems. T
his year we are switching to Postgis Topology and tests so far are very pr
omising. We also take a glance on this project here in this talk. \n\nA Po
stgis Topology database modell has normalised the data related to borders
and surfaces as opposed to Simple Feature where this is not the case. Simp
le Feature database modell may be compared to not using foreign keys betwe
en students and classes in a database model\, but just using a standard sp
readsheet model where each student name are duplicated in each class they
attend.\n\nURL’s that relate this talk\n\nhttps://gitlab.com/nibioopenso
urce/pgtopo_update_gui\nhttps://gitlab.com/nibioopensource/pgtopo_update_r
est\nhttps://gitlab.com/nibioopensource/pgtopo_update_sql\nhttps://gitlab.
com/nibioopensource/resolve-overlap-and-gap
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:More correct maps/data with Postgis Topology rather then Simple Fea
ture ? - Lars Opsahl
URL:http://talks.osgeo.org/foss4g-2023/talk/K3SNQM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZQLFGH@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:QFieldCloud enables the synchronisation and consolidation of fi
eld data collected by teams using QField. From small individual projects t
o large data collection campaigns\, the platform allows you to manage the
collaboration of multiple people on the same project\, assign different ro
les and rights to different users\, work online and offline\, and keep tra
ck of changes made. In 2022\, QFieldCloud was testable as a beta version.
Already during the beta phase\, over 40\,000 registered users synchronised
their projects via the platform. Beginning of 2023\, the official version
was released. A brief overview of how QFieldCloud works and how the platf
orm is built is given.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:QFieldCloud - seamless fieldwork for QGIS - Marco Bernasocchi
URL:http://talks.osgeo.org/foss4g-2023/talk/ZQLFGH/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-K8NGSH@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:MobiDataLab is the EU-funded lab for prototyping new mobility d
ata sharing solutions.\nOur aim is to foster data sharing in the transport
sector\, providing mobility organising\nauthorities with recommendations
on how to improve the value of their data\,\ncontributing to the developme
nt of open tools in the cloud\, and organising hackathons\naiming to find
innovative solutions to concrete mobility problems.\n\nStarted in 2021\, t
he project investigated mobility data and services and did grown an\nopen
knowledge base about mobility data as one of the four main pillars of the
project.\nWith the realization of tools and the combination of data and se
rvices in the Transport Cloud\,\nwhich is the second pillar of the project
\, a representative set of technical\n"mobility data sharing enablers" has
been grown.\n\nIn the second half of the project\, these assets are being
provided to the public.\nThe Virtual and Living Labs will host environme
nts for mobility data stakeholders\nto explore the state of the art for da
ta\, services and their interaction to solve\nmobility data challenges. Al
l aligned with the FAIR statement - making data and services\nfindable\, a
ccessible\, interoperable and reusable.\n\nThe challenges are mainly based
on a broad set of use-cases\, defined by the core project group\,\nthe re
ference group and external stakeholders. These challenges are the core of
the Livind and\nVirtual Labs\, where participants building solutions for t
he given challenges and exploring new\nopportunities with the shared mobil
ity data and services.\n\nWith the feedback of the labs\, our partners\, t
he reference group and external stakeholders\n- mobility data providers fr
om public and private sector\, municipalities\,\ngovernmental institutions
\, start-up communities and stakeholders from research and industry\,\nthe
project will make challenges transparent and remove barriers for data sha
ring.\n\nSince the project started in February 2021\, we will present our
achievements \nprovide an outlook on the last mile of the project\, where
we are bringing the\ntools on the road.\n\nFurther information on the proj
ect is available via https://mobidatalab.eu and https://github.com/mobidat
alab .\n\n\nMobiDataLab is funded by the EU under the H2020 Research and I
nnovation Programme (grant agreement No 101006879).
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:MobiDataLab - Building Bridges on the way for FAIR mobility data sh
aring - Johannes Lauer\, Thierry Chevallier
URL:http://talks.osgeo.org/foss4g-2023/talk/K8NGSH/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-DDRB3Z@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:Apache Superset is one of the most used no-code platforms for b
usiness intelligence. It allows for the exploration and visualization of d
ata\, from simple line charts to highly detailed geospatial charts\, witho
ut the need for programming skills. These charts can be published on inter
active dashboards to provide users with meaningful and up-to-date informat
ion. Currently\, a plug-in for visualizing cartodiagrams is in development
which is based on the OSGeo projects OpenLayers and GeoStyler. This plug-
in gives users the ability to use any visualization of Superset within a g
eospatial context\, so that e.g. simple pie charts or even complex locatio
n based timeseries can be displayed on a map. Thereby\, Superset becomes a
powerful tool for visualizing geospatial data.\n\nThis talk gives a brief
overview of Superset and possible use cases while focussing on geospatial
data.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Visualizing Geospatial Data with Apache Superset - Jan Suleiman
URL:http://talks.osgeo.org/foss4g-2023/talk/DDRB3Z/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-LMNBLS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:The Web has an increasing number of web applications being deve
loped to freely provide their information and is a hub for open data publi
shing. For this to happen as a self-sustained ecosystem\, data must be fin
dable\, accessible\, interoperable\, and reusable to both humans and machi
nes across the wider web. This session delves into Web Best Practices for
publishing data using open source and standards-based solutions.\n\nThe ge
oconnex.us project is about providing technical infrastructure and guidanc
e to create an open\, community-contribution model for a knowledge graph l
inking hydrologic features in the United States as an implementation of In
ternet of Water principles. This knowledge graph can be leveraged to creat
e a wide array of information products to answer innumerable water-related
questions. \n\nImplementation has two parts: persistently identified real
world objects and organizational monitoring locations that collect data a
bout them. Both must be published to the Web using persistent URIs and com
municated with common linked data semantics in order for a knowledge graph
to be constructed. \n\nThe Internet of Water Coalition supports the first
part with a Permanent Identifier Service and reference hydrologic referen
ce features (e.g. watersheds\, monitoring locations\, dams\, bridges\, etc
.) within the US.\n\nIn support of the second part\, geoconnex.us takes ad
vantage of pygeoapi using the OGC API - Features standard to publish struc
tured metadata resources about individual hydrologic objects and the data
about them. pygeoapi supports extending this standard by incorporating dom
ain-specific structured data into the HTML format at the feature level\, a
nd allowing for external HTTP URI identification. In addition\, pygeoapi
’s flexible plugin architecture enables for custom integration and proce
sses. This means that individual features from various sources can have st
ructured\, standardized metadata harvested by search engines and assembled
into a useful knowledge graph.\n\nThis spatial feature-based linked data
architecture enables data interoperability between independent organizati
ons who hold information about the same real world thing without centraliz
ing data infrastructure - answering important questions like\, “Who is c
ollecting water data about my local stream and its tributaries?” or “W
hat data do we have about water upstream and downstream of East Palestine\
, Pennsylvania?”
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Geoconnex.us: a standards based framework to discover water data -
Tom Kralidis\, Benjamin Webb
URL:http://talks.osgeo.org/foss4g-2023/talk/LMNBLS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-BNJXL7@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:pgRouting\, a PostGIS extension containing algorithms and tools
for working with graph data\, has become a highly flexible member of the
FOSS routing engine family. In this talk\, I want to demonstrate just how
flexible it can be by showing how routable networks (called 'topologies' i
n pgRouting) can be made editable.\n\nI will take the audience from theore
tical conception of editable topologies (how can edits\, insertions and de
letions be handled in PostGIS?) through its implementation. Finally\, I wi
ll end with a demonstration of a fully editable topology in a web mapping
application based on a real world example using OpenStreetMap data.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N115 - Second Floor
SUMMARY:Editable topologies in pgRouting - Christian Beiwinkel
URL:http://talks.osgeo.org/foss4g-2023/talk/BNJXL7/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FSJ7PK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:The goal of this presentation is to give an overview of the dif
ferent options available for deploying a GeoServer configuration to differ
ent environments. In addition to the common data_dir folder deployment opt
ion\, we will explore the possibilities offered by existing extensions and
by the REST API\, including different client libraries around it. We will
also discuss the advantages that can be brought by Terraform for this use
case.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Comparison of GeoServer configuration deployment options - Alexandr
e Gacon
URL:http://talks.osgeo.org/foss4g-2023/talk/FSJ7PK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QP73BR@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T143000
DTEND;TZID=Europe/Tirane:20230629T150000
DESCRIPTION:The use of free open source software is catching on and (at lea
st) in Finland governmental institutions are making the big switch to open
source software from other solutions. This opens up the need and possibil
ity for training. \n\nTraining needs may differ from no previous training
or knowledge to advanced GIS professionals so customising the training and
exercises are important. Some might need to start with basic GIS and spat
ial information in general and continue to hands-on learning and multiple
different exercises to help them learn the use of different tools and work
flows in QGIS. \nFor more advanced users\, training and helping with diffe
rent programs for example GeoServer and QField or deepening the knowledge
of different workflows such as visualisation or Python in QGIS are more in
order.\n\nFOSS4G has also been catching on and spreading in schools and u
niversities. These new professionals that have used FOSS4G from the very b
eginning of their studies can be more efficient and skillful using these d
ifferent programs. They may also demand more from the software and think o
f new ways to modify and perfect their workflows and produce new innovatio
ns. They can be a new and very important resource for developing different
areas of FOSS4G.\n\nTraining new and more experienced professionals in FO
SS4G is a very important step for implementing new tools and workflows int
o different industries and businesses. Training also works both ways\, thr
ough discussion and hands-on exercises some new and interesting needs may
emerge and those could be possible to develop further into new tools or pl
ugins. \n\nThe more institutions\, businesses and other users are interest
ed in switching to FOSS4G\, the more new opportunities and needs for diffe
rent tools and working methods arise. This in turn helps to develop the so
ftware further.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Training the future with FOSS4G - Elisa Hanhirova
URL:http://talks.osgeo.org/foss4g-2023/talk/QP73BR/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZRYY83@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T153000
DESCRIPTION:Use cases should drive product development\, not the other way
around. Maps and the products we use to consume them have the biggest impa
ct on the world when these principles are adhered to. How many government
portals have you visited where a carefully curated map is presented that h
ardly anyone sees let alone uses? Presenting the data to the user in an in
tuitive way that helps them make a decision or take action is essential.\n
\nLarge paper maps of the 1700s were well suited to a captain’s desk as
their ships traversed the oceans. Road atlases of the 20th century helped
to spur family adventures and weekend getaways as highway networks were co
nstructed around the world. The small computers in our pockets today allow
us to see when the next train will arrive and which one will get us home
sooner. These examples took the technology of the day and used it to make
products with significant impact on society. The mobile internet in partic
ular changed mapping in one of the most notable ways since humans started
abstracting 3D space on 2D surfaces.\n\nWe’re on the cusp of another gre
at shift in the way maps are used with many exciting use cases awaiting di
scovery. The technology powering this potential is Augmented Reality (AR).
This talk will explore some of the use cases that AR is supporting and wh
ere it might be useful in future. We’ll look at how AR can be accessed a
nd how the medium of access affects its utility. With these use cases in m
ind\, we’ll assess how open tools and map data enable AR. Some of the da
ta and tools we’ll look at include:\nGeometries of pedestrian ways\nAsso
ciated attributes: Incline\, safety\, lighting\, access\, surface type\, a
ccessibility features\nBuilding entrances\n3D building data\nVPS for local
isation\nRouting algorithms\n\nThe talk will conclude with a summary of Me
ta’s approach to map building and how open source geospatial technology
powers the maps we build for today and the years ahead.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:AR: Why open map data is critical to the future of computing - Edoa
rdo Neerhut
URL:http://talks.osgeo.org/foss4g-2023/talk/ZRYY83/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-LPYMXZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T153000
DESCRIPTION:The Uber H3 library is a powerful geospatial indexing system th
at offers a versatile and efficient way to index and query geospatial data
. It provides a hierarchical indexing scheme that allows for fast and accu
rate calculations of geospatial distances\, as well as easy partitioning o
f data into regions. In this proposal\, we suggest using the Uber H3 index
ing library in Postgres for geospatial data processing.\n\nPostgres is an
open-source relational database management system that provides robust sup
port for geospatial data processing through the PostGIS extension. PostGIS
enables the storage\, indexing\, and querying of geospatial data in Postg
res\, and it offers a range of geospatial functions to manipulate and anal
yze geospatial data.\n\nHowever\, the performance of PostGIS can be limite
d when dealing with large datasets or complex queries. This is where the U
ber H3 library can be of great use. By integrating Uber H3 indexing with P
ostgres\, we can improve the performance of PostGIS\, especially for opera
tions that involve partitioning of data and distance calculations.\n\nWe p
ropose to demonstrate the use of Uber H3 indexing library in Postgres for
geospatial data processing through a series of examples and benchmarks. Th
e proposed presentation will showcase the benefits of using Uber H3 indexi
ng for geospatial data processing in Postgres\, such as improved query per
formance and better partitioning of data. We will also discuss the potenti
al use cases and applications of this integration\, such as location-based
services\, transportation\, and urban planning.\n\nThe proposed presentat
ion will be of interest to developers\, data scientists\, and geospatial a
nalysts who work with geospatial data in Postgres. It will provide a pract
ical guide to integrating Uber H3 indexing with Postgres\, and offer insig
hts into the performance gains and applications of this integration.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Leveraging the Power of Uber H3 Indexing Library in Postgres for Ge
ospatial Data Processing - Jashanpreet Singh
URL:http://talks.osgeo.org/foss4g-2023/talk/LPYMXZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PC3WRH@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T153000
DESCRIPTION:Introducing Felt\, a new map sharing and collaboration product.
\n\nWe connect closely with the current ecosystem of open source mapping t
ools and make it easier to work together with colleagues inside and outsid
e mapping. In this talk\, we will show:\n\n- How current users of programs
like QGIS bring Felt into their workflows\n- Where Felt lets them expand
into new areas like community feedback\n- How we’ve used and expanded co
re OSS libraries like MapLibre\, GDAL\, Pelias\, and Tippecanoe\n- Why we
’re pushing forward emerging formats and standards like PMTiles\n\nSessi
on attendees will gain an important new tool for their stack\, a product m
ade for extending the reach of existing open source mapping tools and impr
oving collaborative map-making beyond analysis.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Felt Maps for Sharing and Collaboration - Michal Migurski
URL:http://talks.osgeo.org/foss4g-2023/talk/PC3WRH/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-3UCFFC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T150500
DESCRIPTION:Today\, there is a growing use of airborne sensors in archaeolo
gy\, especially to investigate the surface of vast territories quickly and
accurately. Airborne laser scanning technologies from small remotely pilo
ted aircraft are rapidly turning towards more and more performing solution
s for the investigation of archaeological traces hidden by vegetation or s
oil deposits substantial. The proposed contribution aims to fit into this
field of archaeological research by presenting "UAVIMALS" (Unmanned Aerial
Vehicle Integrated with Micro Airborne Laser Scanner)\, a new system of a
erial remote sensing of "shadow marks” (Masini – Lasaponara 2017\; p.
32) designed for surface archaeological investigations\, the result of an
Early Carrer Grant funded by the National Geographic Society. The system\,
consisting of a custom drone based on an open architecture and software f
or vehicle control and data processing\, integrates a solid-state laser se
nsor\, commonly designed to avoid obstacles\, but here exploited to proces
s a DTM (Digital Terrain Model) accurate of small surfaces with a signific
ant reduction in acquisition time and cost. The ambition of the UAVIMALS p
roject was not to create an airborne LIDAR at low cost and less performing
than those already on the market\, but rather to create an instrument of
easy transportability\, less expensive and equally precise. We believe the
solution represents a breakthrough in research into airborne laser scanne
r technologies.\nThe acquisition of three-dimensional images at very high
morphometric resolution\, has proved to be a fundamental practice for the
study of various contexts of our planet\, but in the archaeological field\
, in particular\, drone remote sensing is an extremely important practice
for the investigation of ancient structures\, sometimes still unexplored\,
not otherwise searchable by other means\, such as excavation and reconnai
ssance activities\, due to uncomfortable geomorphological conditions\, pla
ces of difficult access and traces invisible to the human eye at short dis
tances and in particular climatic conditions (Štular- Eichert- Lozić 202
1). Nevertheless\, most of the instruments currently on the market still h
ave prohibitive costs for archaeological research\, as well as unfavourabl
e dimensions to meet transport needs in inaccessible places in the absence
of transport. The realization of the system presented has tried to overco
me these critical issues by working on the hardware solution best suited t
o the needs of an investigation of aerial archaeology\, by using a type of
lidar sensor never used for remote sensing by drone. The instrument\, wit
h its low cost and dimensions\, was born as a system for autonomous drivin
g on road vehicles (https://leddarsensor.com/solutions/m16-multi-segment-s
ensor-module/) and was customized on a self-built drone to obtain a protot
ype of the 'very light' class. Following the experimentation in two differ
ent archaeological contexts\, the work continued with the resolution of th
e second criticality\, that is the creation of a software useful for the c
ontrol of the medium in phase of flight but also able to monitor the acqui
red data finalizing a first graphical elaboration. Currently\, in fact\, i
t is possible to work the clouds of lidar data points only through dedicat
ed software (Cloude Compare\; 3D Zephyr\; QGIS etc.) that not being connec
ted with the drone\, do not allow a real-time visualization of what is see
n by the sensor and prevent a preliminary first monitoring of any archaeol
ogical presence hidden in the overflight area. The DEM\, meshes and clouds
of points obtained from the sensor can then be loaded into geospatial sof
tware such as QGIS\, allowing spatial\, territorial\, and geomorphological
analysis of the data acquired using specific tools. If for other contexts
of application such activity may be superfluous\, in the archaeological f
ield\, a system like the one thought can represent a concrete possibility
of widening of the archaeological investigations that in such a way would
be speeded up by a tool of observation as well as facilitated by a cost wi
dely accessible to the funds given to the research university. The system\
, moreover\, would allow to speed up also the preliminary archaeological o
perations preliminary to the realization of any public work\, through an i
mmediate verification of the possible archaeological presence in the areas
affected by the operations\, thus avoiding costly design changes in the p
rocess. The proposed contribution\, therefore\, would present not only the
hardware and software solution developed\, but also the preliminary resul
ts obtained from its application in the archaeological context of Leopoli
- Cencelle\, a medieval city\, about 60 km north of Rome\, where critical
issues such as the extent of the site\, the presence of large elevation ch
anges and dense vegetation have always complicated the excavation activiti
es on the hill\, still leaving much of the unexplored city. In this contex
t\, in fact\, remote sensing by drone\, has proved to be an effective meth
od for the investigation of ancient structures with a different degree of
archaeological visibility in which the evidence is not yet completely abov
e ground and are obliterated by high and medium stem vegetation. The exam
ination\, although the result of an experimental activity\, not only made
it possible to identify anomalies relating to structures not yet intercept
ed by the excavation operations but also encouraged the planning of future
investigation campaigns\, allowing a more conscious planning of the areas
of interest.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:UAVIMALS: the "open" remote sensing system for surface archaeologic
al investigations. - Federica Vacatello
URL:http://talks.osgeo.org/foss4g-2023/talk/3UCFFC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QMTXW9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T153000
DESCRIPTION:Radiant Earth is building a new data sharing utility called Sou
rce Cooperative that aims to make it trivially easy for data providers to
publish data on the Internet. Source Cooperative is the next generation of
Radiant MLHub which Radiant Earth built to share Earth observation traini
ng datasets. In this talk\, we will share lessons learned about sharing da
ta from working with NASA\, Planet\, Sinergise\, AWS\, Microsoft\, and oth
ers. We will also share how we’re applying those lessons to create Sourc
e Cooperative.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Expanding Geospatial Data Access: Lessons from Radiant MLHub and th
e Shift to Source Cooperative - Michelle Roby
URL:http://talks.osgeo.org/foss4g-2023/talk/QMTXW9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XHU8UU@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T153000
DESCRIPTION:Deprecation of a used framework is a common risk for software p
rojects. Migrations are very time-consuming and costly\, without showcasin
g any new functional features. This can make them an unpopular task\, that
tends to be postponed until there is no other choice\, be it for a custom
er or the community of an open source project.\n\nDuring the last decade f
or instance\, AngularJS has been one of the most popular web frameworks ar
ound. This was not any different in FOSS4G projects\, where it had been ad
opted in geoportals and other frontend components. With the end of the dec
ade\, active development of AngularJS came to an end and since summer 2021
no more security updates are provided. This has become a major challenge
for many web ecosystems - including FOSS4G ones - where AngularJS is still
very present\, but will have to be replaced in the long run.\n\nThis talk
will present various open source projects and how they differently approa
ch this challenge. It will reflect on lessons learned so far and aspires t
o provide inspiration for other projects in a similar situation.\n\nGeomap
fish is a WebGIS framework that allows to build geoportals. It is a commun
ity driven project. Its frontend is based on the ngeo javascript library\,
which has been built on top of AngularJS and OpenLayers. Due to its wide
functionality\, the project’s goal is to prevent a one shot migration. I
t has been decided for a continuous migration based on (Lit Element) web c
omponents\, that allow to integrate migrated functionalities step by step.
\n\nGeoportal.lu is the national geoportal of Luxembourg. It is based on t
he Geomapfish framework\, but has a very customized frontend. The requirem
ent here is similar. Instead of migrating all at once\, the different part
s should be continuously integrated. After following the Geomapfish migrat
ion strategy based on web components at first\, the project is finally mig
rated to another javascript framework (vue)\, without giving up on the con
tinuous migration.\n\nGeonetwork is a well-known FOSS4G catalog applicatio
n. On top of its powerful backend\, sits a frontend that is also based on
AngularJS. Once again\, its functionality is so vast\, that a complete rew
rite would be enormous. Thus came up the idea of geonetwork-ui: A new proj
ect that could live alongside Geonetwork without the goal to become isofun
ctional\, but to complement it. A project providing libraries specialized
in proposing user interfaces by leveraging Geonetwork’s backend capabili
ties.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Migration strategies: Or how to get rid of a deprecated framework -
Tobias Kohr
URL:http://talks.osgeo.org/foss4g-2023/talk/XHU8UU/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-YZYVZA@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T153000
DESCRIPTION:The National Land Survey (NLS) of Finland decided in the fall o
f 2020 to develop a national topographic data production system based on o
pen source technologies and especially on QGIS client. Since then\, many s
ignificant steps have been taken to implement the MVP of the application f
or the operators of the NLS at the start of 2025. \n\nThe latest significa
nt expansion of our product has been the development of a comprehensive an
d user-friendly way to handle data quality management for the operators. O
ur aim was to develop it in a way that changes for the quality rules could
be easily made and maintained and that would be as informative as possibl
e. The basic idea behind quality management is clear: our customers want h
igh-quality data\, and we want the operators to have clear and easy-to-und
erstand checks for their workflow that do not limit their productivity. Fo
r this\, we have developed a tool\, simply named Quality management tool.
\n\nThe reason we couldn't use the basic QGIS tools was that they were not
easily modifiable or extensive enough for our use cases and quality deman
ds for our data. We have been able to use some of them\, such as geometry
checks\, but for the most part\, the quality tools had to be manually sele
cted and configured\, which would take the operator's time. \n\nThe key co
ncept of quality management is that the operator gets real time feedback a
bout the quality\, so the errors can be fixed as part of the basic workflo
w and there is no need for separate phases for quality control. Additional
ly\, we would not limit the user from saving their work to their local dat
abase\, regardless of the errors they may have\, so that the workflow woul
d not be interrupted. \n\nAt this moment we have published the graphical u
ser interface for visualizing the quality check results (can be found here
: https://github.com/nlsfi/quality-result-gui) but on this talk I would sh
ow how it can work on a larger scale. For this purpose\, I would present t
he tool with use case videos. I would also like to talk about the architec
ture of the tool and how we are going to develop the tool even further. I
hope that some listeners can apply this tool for their workflows and benef
it from this example.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Developing a real-time quality checker for the operators on QGIS -
Olli Rantanen
URL:http://talks.osgeo.org/foss4g-2023/talk/YZYVZA/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QGYS7D@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T153000
DESCRIPTION:The Lazio Region Authority (Italy) has been using for several y
ears a system based on the G3W-SUITE and QGIS application which has allowe
d it\, not only to publish public web services\, but to prepare web cartog
raphic management systems dedicated to internal staff for the management o
f territorial aspects of own competence:\n * management of damages caused
by wildlife and related reimbursement procedures\n * environmental impact
assessment practices\n * wolf genetics\n * signaling the presence of wild
boar in urban areas\n * nests and strandings of sea turtles\n * road accid
ents with wildlife\n\nThe close integration between the suite and QGIS has
allowed to create web cartographic management systems characterized by:\n
* numerous geometry editing features\n * customization of the structure o
f the editing and attribute consultation forms\n * simplification of attri
butes compilation thanks to the ability to inherit from QGIS: editing widg
ets\, \n * mandatory and uniqueness constraints\, default values\, conditi
onal forms and drill down cascade based on expressions\n * possibility of
defining geographical constraints in visualization and editing in order to
divide the \nterritory based on areas of competence associated with indiv
idual users\n * possibility to differentiate the information content acces
sible on the basis of different users and roles\n * descriptive analysis o
f the data through integration with the graphs created with the DataPlotly
plugin\n\nThanks to the contribution and funding from the Lazio Region de
dicated to the development and integration with the QGIS functions related
to data editing\, G3W-SUITE is configured as a valid tool for the prepara
tion of advanced geographic data management systems on the web.\n\nAs an e
xample\, we report a series of use cases:\n * Environmental Protection Age
ncy of the Piemonte Region: post-event damage and usability census\, manag
ement and cartographic representation of post-earthquake inspection reques
ts\n * Gran Paradiso National Park: park route signage management\n * Piem
onte Region: preparation of Civil Protection Plans\n * Environmental Prote
ction Agency of the Lombardy Region: Hydrological Information System
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:G3W-SUITE as a tool for the preparation of web cartographic managem
ent systems - Walter Lorenzetti
URL:http://talks.osgeo.org/foss4g-2023/talk/QGYS7D/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-EGF9AA@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T153000
DESCRIPTION:The Copernicus Ground Motion Service (EGMS) is a European Union
(EU) initiative under the Copernicus program\, which aims to provide near
-real-time information about ground deformation caused by natural or man-m
ade hazards. The service uses a variety of data sources\, including satell
ite radar imagery\, to monitor and analyze ground motion in areas prone to
landslides\, sinkholes\, earthquakes\, and other hazards. Given the sensi
tive nature of the service\, EGMS product validation is a key activity in
assuring the user community (especially the decision makers) of the qualit
y of the ground motion and deformation information provided.\n\n\nThe main
goals of the EGMS validation system are as follows: to provide a reproduc
ible environment on top of modern cloud infrastructures (with a particular
focus on the European geo clouds)\, to enable the development of scientif
ic tools that validate EGMS characteristics\, to facilitate the reproducib
ility of the validation tasks\, and to account for key performance indicat
ors (which will allow shareholders to monitor the quality of the primary E
GMS product).\n\nTo achieve the first goal of providing a reproducible env
ironment\, we have focused on providing Terraform modules that facilitate
the deployment of our software stack on any supported cloud platform. The
software stack is built on top of the Kubernetes container orchestration s
ystem\, which runs on top of a managed cloud environment. Kubernetes provi
des uniform services regardless of the underlying cloud platform.\n\nFor t
he goals of developing the validation tools and the execution of those too
ls we decided on using an unified approach based on the JupyterHub solutio
n. JupyterHub is used for providing an unified development environment bas
ed on R and Python EO software tools (based on modified Pangeo Docker imag
es). Also Jupyter is used for executing the validation tools outside of Ju
pyterHub by leveraging an internal python service that uses papermill to e
xecute the notebook and then “nbconvert” to generate a html webpage co
ntaining the required visualizations and documentation in human readable f
orm.\n\nThe validation system is complemented by an bespoke web dashboard
aimed for providing reports and information related to the status of the v
arious key performance indicators.\n\nOverall the whole validation system
was developed by solely using FOSS4G components: GeoPandas\, RasterIO\, Ge
oNode\, GeoServer and JupyterHub.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Runtime environment for the validation of the Copernicus Ground Mot
ion Service - Vasile Crăciunescu\, Marian Neagul
URL:http://talks.osgeo.org/foss4g-2023/talk/EGF9AA/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RFCAYS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150000
DTEND;TZID=Europe/Tirane:20230629T153000
DESCRIPTION:The **Massive Open Online Course - Earth Observation Open Data
Science (MOOC EOODS)** teaches the concepts of data cubes\, cloud platform
s\, and open science in the context of Earth Observation (EO). \n\nIt aims
at Earth Science students\, researchers\, and Data Scientists who want to
increase their technical capabilities onto the newest standards in EO clo
ud computing. The course is designed as a MOOC that explains the concepts
of cloud native EO and open science by applying them to a typical EO workf
low from data discovery\, data processing up to sharing the results in an
open and FAIR way. \n\nThe [EO College platform](https://eo-college.org/we
lcome) hosts the course and hands-on exercises are carried out directly on
European EO cloud platforms\, such as [Euro Data Cube](https://eurodatacu
be.com/) or [openEO Platform](https://openeo.cloud/)\, using open science
tools like the [Open Science Data Catalogue](https://opensciencedata.esa.i
nt/) and [STAC](https://stacspec.org/en) to embed the relevance of the lea
rned concepts into real-world applications. The MOOC is an open learning e
xperience relying on a mixture of animated lecture content and hands-on ex
ercises created together with community renowned experts. \n\nAfter finish
ing the course\, the participants will understand the concepts of cloud na
tive EO\, be capable of independently using cloud platforms to approach EO
related research questions and be confident in how to share research by a
dhering to the concepts of open science.\n\nThe MOOC is valuable for the E
O community and open science as there is currently no learning resource av
ailable where the concepts of cloud native computing and open science in E
O are taught jointly to bridge the gap towards the recent cloud native adv
ancements in EO. The course is open to everybody\, thus serving as teachin
g material for a wide range of purposes including universities and industr
y\, maximizing the outreach to potential participants. \n\nOur talk will g
ive an overview of the MOOC at the current status. Furthermore\, we encour
age review\, feedback on its content and discussion.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:MOOC EOODS - Massive Open Online Course for earth observation and o
pen data science: a course to educate the next generation of EO researcher
s in data cubes\, cloud platforms and open science - Peter James Zellner
URL:http://talks.osgeo.org/foss4g-2023/talk/RFCAYS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UNGKZM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T150500
DTEND;TZID=Europe/Tirane:20230629T151000
DESCRIPTION:This project conducts a statistical model using the Mann-Kendel
l and a Sens Slope on the completed MODIS LST mission data for analysis of
climate change thermal shifts across the Republic of Kosovo. This project
leverages Google Earth Engine open data to build the statistical models t
hat are extracted and analyzed in Q-GIS. This approach uses non-parametric
statistical timeseries analysis for completed MODIS LST mission data to a
nalyze and understand day and night land surface temperature shifts over d
ifferent temporal periods to gather an understanding of the current and pr
oject the future expected impacts of climate change on various developing
tourist economies in the Republic of Kosovo. \nWater balance is utilized a
s a function of understanding the impacts of climate change on wine grape
capacity and the attempt to functionally understand the future disruptions
of climate change through linear geographic regressions. These regression
s will guide the understanding of the climate changes that are occurring w
ith the country and provide a basis for analysis to develop resilience met
hods. This model will be broken down into viticultural regionality to unde
rstand the dynamism of the impacts across the country. The two data sets u
sed will be MODIS land surface temperature and Tropical Rainfall Measuring
Mission which will create an understanding of surface temperature shifts
within Kosovo and water balance shifts that are occurring due to climate c
hange in Kosovo. The datasets also be correlated between each other using
a Pearson’s correlation coefficient to understand if a relationship exis
ts between land surface temperature and water balance within wine region o
f Kosovo. \nThe findings of this project will reveal geographic dispersion
of anomalous rain patterns and long-term temperature shifts occurring tha
t can have disruptive impacts on agricultural production of grapes. The re
sults will provide insights based on known geographic extent of wine grape
region to determine the significant temperature changes occurring over th
e past 20 years and the trends for both Day and Night LST within the Repub
lic of Kosovo. Further\, the analysis will seek to develop an understandin
g on the immediate to long-term impacts based on the satellite data trends
. Water balance data analysis will provide precipitation shifts that are
occurring on a monthly basis and can be assessed with Land Surface Tempera
ture as a means of understanding areas that are susceptible to flood-based
natural hazards and amplification through increased temperatures and loss
of water balance. The connection between the two can be assessed to under
stand systemic vulnerabilities occurring within regions that require envir
onmental quality for success. \nAdditionally\, the project is a novel fram
ework for timeseries analysis of bigdata to provide insights into climate
change impacts on the economies of the developing world. The analysis will
focus on the geographic dispersion of touristic economy assets that are b
eing built and improve the use of big data approaches to derive an underst
anding of temperature changes in data poor environments. The results of th
is paper will leverage open datasets\, an analysis of the impacts of tempe
rature changes on the developing tourist economy in the Republic of Kosovo
\, and the knowledge of capacity for leveraging large geographic datasets
for open climate change research. \nThe use of big data and open modeling
provides a considerable resource for governments\, municipalities\, and NG
Os to develop an understanding of how climate change will impact their com
munities. The paper discusses the statistical concepts used on the MODIS c
omplete dataset and interpretations of the results. The major concepts app
roached are the use of Google Earth Engine utilization for modeling remote
sensed data to understand the environmental conditions being caused by cl
imate change. The underlying data analysis and implications draw connectio
ns within local conditions and how human environmental conditions are impa
cted for wine tourism development. This paper does not assess the loss of
economic value but rather interpret the data to understand the positionali
ty of the underlying environmental commodity conditions such as snowpack a
nd grape vine stock. We discuss an analysis utilization within a novel fra
mework for open-source climate intelligence building for those regions wit
hout the resources for pay-to-use products and data. This paper will build
an understanding of methodological analysis approaches with multiple mode
ls to develop and deliver products capable of informing national and regio
nal climate adaptation strategies in both the long and short-term. \nThe R
epublic of Kosovo is working towards developing many touristic economic se
ctors that are heavily reliant on climate including the wine region of Rah
ovec and Prizren\, both of which face tremendous uncertainty in the face o
f climate change. Development of tools and technics to display the capabil
ities of open big data analysis and provide vital analysis into the impact
s of climate change. We seek to explore the capability for utilization of
open-source learning tools\, to build open-data models capable of providin
g vital insights into the impacts of climate change in countries that have
the least resources and the most risk.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Agro-tourism impact analysis of climate change using Google Earth E
ngine in the Rahovec wine region of Kosovo. - Dustin Sanchez
URL:http://talks.osgeo.org/foss4g-2023/talk/UNGKZM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-SDHKTG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T151000
DTEND;TZID=Europe/Tirane:20230629T151500
DESCRIPTION:This work is based on the design and development of a system ai
med at monitoring the urban transformations of the area used for the Expo
2015 exhibition in Milano\, exploiting the potential offered by the storag
e and management of geographic data in a GIS environment (Burrough\, 1986)
. The system is designed to collect and analyze data showing the changes o
f the urban landscape going through pre-Expo\, to Expo and post-Expo trans
formations (Gaeta & Di Vita\, 2021).\n\nOne of the reasons behind this wor
k is the fact that a complete digital database documenting the urban trans
formations in the Expo 2015 area is not yet available. In fact\, all the d
ata which were needed to implement the GIS were originally represented by
maps (in paper or in digital non georeferenced format) of development proj
ects and by cartographic work attached to city plans. After checking the c
ompatibility of the process with the original licenses\, the maps had been
made openly accessible to the public after being scanned\, so they had to
be geo-referenced and vectorized in order to be able to insert the data i
n the GIS database.\n\nThe implementation and use of GIS technology implie
d (i) the definition of the database conceptual and logical model\; (ii) t
he acquisition of a large number of geographic data layers\, which were st
ructured according to the design of a relational database. Layers which we
re acquired included data on: cadastral parcels\; buildings\; players invo
lved in the urban transformations\; land regulations\; open spaces\; land
cover\; functional lots\; public transport stops\; roads and underground u
tility lines.\n\nThe structure of the DB has been designed based on a rela
tional model (Codd\, 1970) by following the standard methodology defined i
n 1975 by the ANSI - SPARC Committee\, going through successive phases and
originating the external\, conceptual and logical models. Following this
strategy\, the external model was defined on what were assumed to be the f
uture users’ needs in terms of data storage\, consultation and queries o
n the data. Aiming at documenting also the timeline of the urban transform
ations of the area\, the Entity Relationship Diagram (ERD) was designed in
tegrating in a unique conceptual scheme the temporal dimension of the tran
sformations\, going from the pre-Expo\, to the Expo which took place in Mi
lano from May to October 2015 and finally the post-Expo layout of the area
. Subsequently\, the logical model of the database was also designed.\n\nT
he data acquisition required to research a large number of sources\, which
were mainly represented by images of maps available online on the website
s of the different stakeholders\, ranging from public administration chann
els and OpenStreetMap crowdsourced geodata to official Expo 2015 communica
tion platforms. They were then geo-referenced in order to acquire spatial
elements in vector format which were afterwards stored in the spatial data
base of the GIS\, becoming easily manageable and upgradeable in an interac
tive way. Notably\, the topological models of the streets and of the under
ground network of the district heating were implemented\, in the latter ca
se also connecting each building with the corresponding segment of the net
work (Cazzaniga et al.\, 2013). Finally\, the topological consistency and
coherence of such network and its components was validated.\n\nThe applica
tion of GIS technologies to monitor the transformations of the entire site
allowed to understand and analyze the different phases of the evolution o
f the urban territory\, identifying critical issues and strengths of the d
evelopment projects. Indeed\, in the GIS environment it is now possible to
perform reproducible elaborations and analysis useful to understand how t
he area changed in time\, especially from an urban planning point of view.
This approach can provide insights on the surface covered by buildings in
the different periods and on the change of destination or decommissioning
of exhibition pavilions in the post-EXPO environment. Moreover\, the data
base model allows users to query the data in order to identify underground
services as well as buildings that may be affected by future works on roa
ds or structures located in the area of interest. Such functionalities and
retrieved information could be crucial especially considering the recent
construction of a critical structure like the new Galeazzi hospital\, whic
h has been operative since 2022. Finally\, the possibility to present the
project\, the data and its related metadata and to communicate them also t
o a wider audience of non-technical users was envisaged through the public
ation of a WebGIS-on the Internet\, which was tested with a demo. In futur
e\, by implementing further improvements\, this prototype could lead to a
decision support system\, to be used as a tool to understand the area for
the benefit of all actors involved with different expertise and background
in the urban transformations. In particular\, the choice of the web platf
orm was driven by the possibility to make the project as accessible as pos
sible also through expandable tools in support of geo-narratives and story
telling as well as easy-to-understand dashboards for visualizing quantitat
ive analysis results.\n\nThe whole project has been developed by using fre
e and open-source technologies\, namely MySQL Workbench for the developmen
t of the database model\, QGIS for the implementation of the system and Ge
oNode for the testing of the publication of the System on the Internet. Th
e choice to use free and open-source technologies is both an economical an
d ethical solution aimed at knowledge sharing and at making the DB flexibl
e and easily expandable\, facilitating the integration of new data\, their
updating and the implementation of future functionalities\, paying attent
ion also to the technical accessibility even by non-expert users.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:A free and open-access GIS for the documentation and monitoring of
urban transformations in the area of the Expo 2015 exhibition in Milan - F
ederica Gaspari
URL:http://talks.osgeo.org/foss4g-2023/talk/SDHKTG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-JTNMVW@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T151500
DTEND;TZID=Europe/Tirane:20230629T152000
DESCRIPTION:Currently\, a reliable harmonized and comprehensive pan-EU map
of the building stock provided in vector format is not publicly available\
, not even for a level-of-detail LOD0 (according to the CityGML standard)\
, where the buildings’ footprints can be identified.\nEuropean countries
offer vector maps of their building stock through a variety of levels of
detail\, formats\, and tools\; data across countries is often heterogeneou
s in terms of attributes\, accuracy and temporal coverage\, available thro
ugh different user interfaces\, or hardly accessible due to language barri
ers. Bottom-up solutions from local cadastral data in the framework of the
INSPIRE initiative and top-down standard-setting regulations like the EU
Regulation 2023/138 laying down a list of specific high-value datasets and
the arrangements for their publication and re-use [1]\, are increasing an
d improving the homogeneity in the data availability.\nHowever\, crowd-sou
rced providers of building footprint vectors like OpenStreetMap (www.opens
treetmap.org) are covering an increasing fraction of territory within the
European Union. Simultaneously\, improvements in remote sensing increased
the resolution of satellite imagery and allowed for building footprints se
gmentation on very high-resolution images based on deep learning: major st
akeholders in the field of information technology were able to disseminate
large vector datasets with extensive territorial coverage publicly (like
Microsoft and Google). Other research institutions released grid-based map
s of built-up\, covering the world at the resolution of 10 metres (like th
e Built-Up Surface of the Global Human Settlement Layer) or Europe at the
resolution of 2 metres (like the European Settlement Map). Another project
called EUBUCCO [2] has compiled a vector database of individual building
footprints for 200+ million buildings across the 27 European Union countri
es and Switzerland\, by merging 50 open government datasets and OpenStreet
Map\, which have been collected\, harmonized and partly validated.\nThe me
thodology presented here provides a replicable workflow for generating sea
mless building datasets for each of the EU-27 countries\, by combining the
best available public datasets.\nAfter reviewing existing literature and
assessing publicly available buildings data sources\, the following were i
dentified as core input datasets:\n• OpenStreetMap (OSM): a free and ope
n-source global dataset of geographic features\, including building footpr
ints and attributes\; \n• Microsoft Buildings (MSB): a freely available
dataset of building footprints developed by Microsoft using machine learni
ng algorithm on very high-resolution satellite imagery [3]\; \n• Europea
n Settlement Map (ESM): raster dataset of built-up areas classified using
Convolutional Neural Networks from 2-meter spatial resolution from very hi
gh-resolution imagery available through Copernicus [4]. \nBuilding footpri
nts are available in OpenStreetMap across all 27 countries\, but with diff
erent levels of completeness and coverage. Human contributors trace data i
n OSM manually\, thus the available building footprints are considered of
higher geometric quality compared to those extracted by machine learning a
lgorithms of the MSB and ESM datasets. Microsoft provides high resolution
building footprints for all 27 countries\, but their coverage within the c
ountry areas varies considerably. The ESM dataset was derived from a seaml
ess mosaic covering the entire EU-27 area\, so it is considered being the
most complete in terms of coverage\, although the lower resolution and qua
lity does not allow for extracting detailed building footprints as availab
le with OSM and MSB.\nThe combination of the above-listed dataset is carri
ed out with a stepwise approach. First\, the MSB dataset is compared to OS
M\, and buildings are selected for any area where they don’t overlap or
intersect. MSB buildings below 40 m2 of surface are filtered out as outlie
rs. Then\, the ESM data is compared to the combined OSM and MSB buildings
and vectorised\, to fill in any gap that is not covered by the latter. Bui
lding footprints issued from ESM are further refined with various geo-spat
ial post-processing operations (e.g.\, buffer\, holes filling\, …)\, the
n filtered to retain only features above 100 m2 of surface\, thus discardi
ng outliers.\nTo implement and automate the described logical workflow\, a
n interactive model has been developed to work in the popular QGIS desktop
software. The QGIS model builder allows for building logical processing w
orkflows by linking input data forms\, variables and all the analysis func
tions available in the software.\nThe conflation process is conducted at t
he country level since OSM and MSB sources are already conveniently provid
ed in country extent packages. Depending on the geographic size of each co
untry and the amount of data included\, some countries are further split i
nto tiles for processing. The resulting building footprints from each inpu
t dataset are kept in separate files for easier handling\, but can be comb
ined visually in GIS software or physically merged in a single file.\nTher
e are several known limitations to the data and the processing workflow:\n
• Many MSB building footprints present irregular geometries that are cau
sed by faulty image interpretation. These can be filtered by calculating t
he vertex angle values of each polygon and removing specific outlier value
s. A methodology was developed at small scale\, but it was not possible to
implement it at country scale yet.\n• The ESM geometries do not accurat
ely describe the actual building footprints but only the rough block outli
ne. While ESM has seamless coverage\, its best application would be for gu
iding additional feature extraction from VHR imagery in areas where OSM an
d MSB have poor coverage.\n• The default overlap settings could be tweak
ed and dynamically adjusted\, based on the built-up pattern (e.g.\, less i
n urban areas\, more in rural areas).\n• Filters of minimum feature size
of 40 m2 for MSB and 100 m2 for ESM can be optimised to find the most rob
ust balance between including non-building features and actual smaller bui
ldings.\nThe resulting buildings dataset is compared with the European Com
mission’s GHSL Built-up surface layer [5] to get an understanding of the
respective coverage at pan European level. A more focused look into the c
omparison with available cadastral data for a particular city\, provides a
preliminary understanding of the accuracy of the new layer along with its
limitations.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:TOWARDS A PAN-EU BUILDING FOOTPRINT MAP BASED ON THE HIERARCHICAL C
ONFLATION OF OPEN DATASETS: THE DIGITAL BUILDING STOCK MODEL - DBSM - Piet
ro Florio
URL:http://talks.osgeo.org/foss4g-2023/talk/JTNMVW/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-VVYSQC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T152000
DTEND;TZID=Europe/Tirane:20230629T152500
DESCRIPTION:The European Ground Motion Service (EGMS) constitutes the first
application of high-resolution monitoring of ground deformation for the C
opernicus Participating States. It provides valuable information on geohaz
ards and human-induced deformation thanks to the interferometric analysis
of Sentinel-1 radar images. This challenging initiative constitutes the fi
rst ground motion public dataset\, open and available for various applicat
ions and studies.\n\n\nThe subject of this abstract is to validate the EGM
S product in terms of spatial coverage and density of measurement points.
A total of twelve sites have been selected for this activity\, covering va
rious areas of Europe\, as well as representing equally the EGMS data proc
essing entities. To measure the quality of the point density we employ ope
n land cover data to evaluate the density per class. Furthermore\, we prop
ose statistical parameters associated with the data processing and timeser
ies estimation to ensure they are consistent across the different selected
sites. \n\n\nThe usability criteria to be evaluated concern the completen
ess of the product\, its consistency\, and the pointwise quality measures.
Ensuring the completeness and consistency of the EGMS product is essentia
l to its effective use. To achieve completeness\, it is important to ensur
e that the data gaps and density measurements are consistent with the land
cover classes that are prone to landscape variation. Consistency is also
vital for point density across the same land cover class for different reg
ions. For instance\, urban classes will have higher density than farming g
rounds\, and this density should be consistent between the ascending and d
escending products. Pointwise quality measures are critical in assessing t
he quality of the EGMS PSI results. For example\, the temporal coherence i
s expected to be higher in urban classes\, and the root-mean-square error
should be lower. Overall\, these measures and standards are crucial in ens
uring the usefulness and reliability of the EGMS product for a wide range
of applications\, including environmental management\, urban planning\, an
d disaster response.\n\n\nFor the validation of point density\, a dataset
of 12 selected sites across Europe is used\, representing the four process
ing entities (TRE Altamira\, GAF\, e-GEOSS\, NORCE). The aim of the point
density validation activity is to ensure consistency across the EU territo
ries by comparing the point density at three sites for each algorithm\, on
e of which is in a rural mountainous area and the other two are urban. The
dataset is obtained directly from the Copernicus Land – Urban Atlas 201
8 and contains validated Urban Atlas data with the different land cover cl
asses polygons\, along with metadata and quality information. We have exte
nsive Urban Atlas (version 2018) verified datasets on the cities of Barcel
ona/Bucharest (covered by TRE Altamira)\, Bologna/Sofia (covered by e-GEOS
S)\, Stockholm/Warsaw (covered by NORCE) and Brussels/Bratislava (covered
by GAF). In parallel we select four different rural and mountainous areas
to analyse more challenging scenarios as well for the four processing chai
ns of the providers.\n\n\nThere are 27 different land cover classes define
d in Urban Atlas. To facilitate the analysis and the interpretation of the
results\, we aggregate and present our findings for each of the main CLC
groups: Artificial Surfaces\, Forest and seminatural areas\, Agricultural
areas\, Wetlands and Water bodies.\n\n\nFor the validation measures\, key
performance indices (KPI) are calculated\, with values between 0 and 1. We
normalise the estimated density values for each service provider with res
pect to the highest value for Artificial surfaces\, Agricultural areas and
Forest and seminatural areas. Users expect consistent and good densities
in these classes\, specifically in the Artificial surfaces. And the lowest
value for Wetlands and Water bodies. This will enable outlier detection s
ince the applied algorithms should barely produce any measurement points o
n these surfaces.\n\n\nRegarding the pre-processing of the data from EGMS\
, one of the challenges was the overlapping of bursts from different Senti
nel-1 satellite tracks. If all bursts were included in the analysis\, area
s with more track overlaps would result in a higher point density\, creati
ng a bias in the data. To address this issue\, a custom algorithm was desi
gned to identify and extract the unique\, non-overlapping polygon for each
burst. This iterative algorithm was specifically designed to ensure a fai
r comparison among different areas\, and to eliminate any biases that coul
d impact the results of the analysis.\n\n\nIn conclusion\, as an open and
freely available dataset\, the EGMS will provide valuable resources for a
wide range of applications and studies\, including those that leverage fre
e and open-source software for geospatial analysis. The validation results
presented here will help to ensure the accuracy and reliability of the EG
MS product\, thereby enabling further research and applications in areas s
uch as geohazards\, environmental monitoring\, and infrastructure manageme
nt.\n\n# References\nCostantini\, M.\, Minati\, F.\, Trillo\, F.\, Ferrett
i\, A.\, Novali\, F.\, Passera\, E.\, Dehls\, J.\, Larsen\, Y.\, Marinkovi
c\, P.\, Eineder\, M. and Brcic\, R.\, 2021\, July. European ground motion
service (EGMS). In 2021 IEEE International Geoscience and Remote Sensing
Symposium IGARSS (pp. 3293-3296). IEEE.\n\nAtlas\, U.\, 2018. Copernicus L
and Monitoring Service. European Environment Agency: Copenhagen\, Denmark.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Validating the European Ground Motion Service: An Assessment of Mea
surement Point Density - Joan Sala Calero\, Amalia Vradi
URL:http://talks.osgeo.org/foss4g-2023/talk/VVYSQC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-HS3KRC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:This talk is about the current state of MilMap and its ongoing
development. MilMap is a military geo-portal system widely and successfull
y used in every sectors of Korean military. The system is now undergoing m
ajor change from geo-portal to military digital twin system. \n\nMilMap is
developed on top of numerous open source projects such as PostGIS\, GeoSe
rver\, GeoWebCache\, Cesium\, OpenLayers\, mago3D\, OpenGXT. The system pr
ovides several functionalities like POI search\, geospatial data search\,
layer control\, satellite image search and download\, spatial terrain anal
ysis\, coordinates reading\, and map notes\, to the military officers thro
ugh the intranet. Although the system provides geospatial analytics functi
ons through OGC WPS(Web Processing Service)\, the current system is basica
lly a web based 3D GIS for data viewing and printing. Thanks to MilMap\, m
ilitary officers can now access the huge amount of geospatial data(maps\,
imagery\, 3D\, POI\, and others) in their browser without installing addit
ional software. \n\nMilMap is now undergoing major development to be a mor
e customized\, automated\, and analytical system. The future MilMap will s
upport user data uploading for intelligence sharing\, more bespoke battle
field analysis and others. In the long run\, MilMap is expected to be a cl
oud based military digital twin system for geospatial intelligence sharing
and battle field analysis & simulation.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Let's defense my country using FOSS4G! - Sanghee Shin
URL:http://talks.osgeo.org/foss4g-2023/talk/HS3KRC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RSNPM3@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:In recent years\, 3D city models have gained popularity for sup
porting urban planning\, citizen engagement\, and research. As technology
and infrastructure have improved\, many cities and countries now use 3D mo
dels to address urban issues\, encourage participation\, and inform decisi
on-making.\n\nThe Japanese government\, including the Ministry of Land\, I
nfrastructure\, Transport and Tourism's Project PLATEAU\, have promoted op
en 3D city models and 3D point cloud data. Over 100 cities are currently d
eveloping and releasing open digital twin data in CityGML format as of Feb
ruary 2023. Binyu et al. published the results of these efforts\, which ar
e also highlighted in the 3D City Index benchmarking report. The report sh
ows that seven out of 40 cities (18%) compared were Japanese cities.\n\nTh
is report discusses the current state of open digital twin data in Japan\,
which is compatible with the open database license ODbL. The data can be
imported into popular tools such as OpenStreetMap\, and converters have be
en developed for this purpose. Since 2022\, import work has been conducted
on an experimental basis in collaboration with national and international
communities. Sharing the results and challenges of this work is expected
to promote the use of 3D city model data globally.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Open data of digital twin city models in CityGML format and their i
mport into OpenStreetMap: Project PLATEAU2OSM - Taichi Furuhashi
URL:http://talks.osgeo.org/foss4g-2023/talk/RSNPM3/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-H7USCF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:This is a plug-in created using pyQGIS\, and an example of usin
g it as basic data for decision-making on noise measurement station select
ion policy will be presented.\nAs data for use in decision-making by publi
c institutions\, we introduce cases in which basic public data are utilize
d and processed to ultimately be used as core data for decision-making.\nI
t will be time to talk about how text-based data held and provided by publ
ic institutions is being used for their spatial expression and policy maki
ng\, and why the opening of public data will play a more important role in
the future.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Selection of noise measurement points based on road network using P
yQGIS - Choi Hyeong-gwan
URL:http://talks.osgeo.org/foss4g-2023/talk/H7USCF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-V9HQLU@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:This is the story of 2 twin projects (namely AIR-BREAK and USAG
E) undertaken by Deda Next on dynamic sensor-based data\, from self-built
air quality stations to the implementation of OGC standard compliant clien
t solution.\nIn the first half of 2022\, within AIR-BREAK project (https:/
/www.uia-initiative.eu/en/uia-cities/ferrara)\, we involved 10 local high
schools to self-build 40 low-cost stations (ca. 200€ each\, with off-the
-shelf sensors and electronic equipment) for measuring air quality (PM10\,
PM2.5\, CO2) and climate (temperature\, humidity). After completing the a
ssembling\, in late 2022 stations were installed at high schools\, private
households\, private companies and local associations. Measurements are c
ollected every 20 seconds and pushed to RMAP server (Rete Monitoraggio Amb
ientale Partecipativo = Partecipatory Environmental Monitoring Network - h
ttps://rmap.cc/).\nHourly average values are then ingested with Apache NiF
i into OGC’s SensorThings API (aka STA) compliant server of the Municipa
lity of Ferrara (https://iot.comune.fe.it/FROST-Server/v1.1/) based on the
open source FROST solution by Fraunhofer Institute (https://github.com/Fr
aunhoferIOSB/FROST-Server).\nSTA provides an open\, geospatial-enabled and
unified way to interconnect Internet of Things (IoT) devices\, data and
applications over the Web (https://www.ogc.org/standard/sensorthings/). ST
A is an open standard\, it builds on web protocols and on OGC’s SWE stan
dards and has an easy-to-use REST-like interface\, providing a uniform way
to expose the full potential of the IoT (https://github.com/opengeospatia
l/sensorthings/).\nIn second half of 2022\, within USAGE project (https://
www.usage-project.eu/)\, we released the v1 of a QGIS plugin for STA proto
col.\nThe plugin enables QGIS to access dynamic data from heterogeneous do
mains and different sensor/IoT platforms\, using the same standard data mo
del and API. Among others\, dynamic data collected by the Municipality of
Ferrara will be CC-BY licensed and made accessible from municipal open dat
a portal (https://dati.comune.fe.it/).\nDuring the talk\, a live demo will
be showcased\, accessing public endpoints exposing measurements (timeseri
es) about air quality (from EEA)\, water (BRGM)\, bicycle counters\, traff
ic sensors\, etc.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Low-cost AirQuality stations + open standard (OGC SensorThings) + o
pen data (CC-BY) + open source (FROST + QGIS plugin for sensors) - Piergio
rgio Cipriano\, Luca Giovannini\, Giacomo Magisano
URL:http://talks.osgeo.org/foss4g-2023/talk/V9HQLU/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-LPDRTF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:The collection\, curation and publication of geospatial informa
tion has been for centuries the sole prerogative of public sector organisa
tions. Such data has been traditionally considered the reference source fo
r datasets and cartographic outputs. However\, new geospatial data sources
(e.g. from the private sector and citizen-generated[1]) have emerged that
are currently challenging the role of the public sector [2]. In response
to this\, governments are currently exploring new ways of managing the cre
ation and update of their geospatial datasets [3]. \nDatasets of high rele
vance are increasingly produced by both private companies and crowdsourced
initiatives. E.g.\, in 2022 Microsoft released Microsoft Building Footpri
nts\, a dataset of around 1 billion building footprints extracted from Bin
g Maps imagery from 2014 to 2022. More recently\, in December 2022n Amazon
Web Services (AWS)\, Meta\, Microsoft\, and TomTom founded the Overture M
aps Foundation (https://www.linuxfoundation.org/press/linux-foundation-ann
ounces-overture-maps-foundation-to-build-interoperable-open-map-data)\, a
joint initiative in partnership with the Linux Foundation with the aim to
curate and release worldwide map data from the aggregation of multiple inp
ut sources including civic organisations and open data sources\, especiall
y OpenStreetMap data.\nThese initiatives aim to improve the coverage of ex
isting governmental geospatial information through the release of open dat
a and a strong dependency on OpenStreetMap. In particular\, the Overture
initiative has the explicit goal to add quality checks\, data integration\
, and alignment of schemas to OSM data.\nRecently\, the Italian Military G
eographic Institute (IGM\, one of the governmental mapping agencies in Ita
ly) has released a multi-layer dataset called “Database di Sintesi Nazio
nale” (DBSN\, https://www.igmi.org/en/dbsn-database-di-sintesi-nazionale
). The DBSN is intended to include geospatial information relevant to anal
ysis and representation at the national level\, with the additional purpos
e to derive maps at the scale 1:25\,000 through automatic procedures. The
creation of the DBSN builds on top of various information sources\, with r
egional geotopographic data as primary source of information and products
from other national public bodies (e.g. cadastral maps) as additional sour
ces. The source is recorded in a specific attribute field for each feature
in the database\, with a list of codes referencing the various sources. A
mong the external sources used as input for the work of integration in the
DBSN\, OpenStreetMap was explicitly considered and used.\nOne of the elem
ents of novelty\, at least in the Italian context\, is the release of the
DBSN under the ODbL licence (https://opendatacommons.org/licenses/odbl)\,
caused by the fact that the inclusion of OSM data requires derivative prod
ucts to be released with the same licence.\nCurrently\, the DBSN includes
data covering only 12 out of the 20 Italian regions (Abruzzo\, Basilicata\
, Calabria\, Campania\, Lazio\, Marche\, Molise\, Puglia\, Sardegna\, Sici
lia\, Toscana\, Umbria). The remaining ones will be released in the near f
uture.\nThe datasets have been downloaded from the official IGM website in
January 2023.\nThe DBSN schema is a subset of the specifications defined
in the "Catalogue of Spatial Data - Content Specifications for Geotopograp
hic Databases” (Decrete 10 November 2011) and is composed of 10 layers\,
29 themes and 91 classes. We compared it with the OpenStreetMap specifica
tions (based on the community-based tagging scheme at https://wiki.openstr
eetmap.org/wiki/Map_Features) and selected two main themes (buildings and
streets).\nThe analysis was performed through a set of Python scripts avai
lable under the open source WTFPL licence at https://github.com/napo/dbsno
smcompare.\nFirstly\, we analysed—for buildings and streets in the IGM d
atabase—where OSM data was used as the primary source of information. Th
e percentage of buildings derived from OSM is minimal\, ranging from 0.01%
in Umbria to 1.3% in Marche\; regarding streets\, the differences between
regions increase\, ranging from almost 0% in Abruzzo and Calabria to 94%
in Umbria.\nSecondly\, we calculated the area covered by buildings and the
length of streets in both the IGM and OSM databases to understand how muc
h OSM completeness is good\, compared to the official IGM dataset.\nIn the
12 regions\, the area covered by buildings in OSM is on average about 55%
of the corresponding area in IGM\, while the percentage of the length of
streets is about 78%. Anyway\, these numbers are highly variable among reg
ions\, ranging between 32% in Calabria and 105% in Puglia for buildings\,
and between 46% in Calabria and 103% in Umbria for streets.\nThese first r
esults show that the main source information in the DBSN (namely the offic
ial regional data) is highly variable across the 12 regions\, which requir
ed the IGM to find additional data sources to fill the gaps. OSM plays a m
inor role for integrating buildings in the database\, while it demonstrate
s a high potential for contributing to street information.\nResults also s
how that\, even with only a small contribution\, some elements that are pr
esent in OSM are still not included in the DBSN. This can be due to at lea
st two reasons: (i) the current workflow of selection of elements in OSM (
through tags) does not include some potentially relevant elements\; ii) th
e (ideally) daily update of OSM is able to bring in the database new featu
res at a pace that is unbeatable by the IGM\, and governmental organisatio
ns in general.\nWhile this study highlights the importance that OpenStreet
Map has achieved as a reference source of geospatial information for gover
nmental bodies as well\, providing evidence of its contribution to the nat
ional database of the IGM\, iit also paves the way for improving OpenStree
tMap itself by importing data for various layers\, benefiting from the rel
ease of the DBSN under the ODbL licence.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:OpenStreetMap as an input source for producing governmental dataset
s: the case of the Italian Military Geographic Institute - Marco Minghini\
, Alessandro Sarretta
URL:http://talks.osgeo.org/foss4g-2023/talk/LPDRTF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-8SQSSV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:Natural Earth is a public domain map dataset available at 1:10m
\, 1:50m\, and 1:110 million scales. Featuring tightly integrated vector a
nd raster data\, with Natural Earth one can build a variety of visually pl
easing\, well-crafted maps with cartography or GIS software.\n\nGeoServer
GeoCSS is a CSS inspired language allowing you to build maps without consu
ming fingertips in the process\, while providing all the same abilities as
SLD.\n\nIn this presentation we’ll show how we have built a world polit
ical map and a world geographic map based on Natural Earth\, using CSS\, a
nd shared the results on GitHub. We’ll share with you how simple\, compa
ct styles can be used to prepare a multiscale map\, including:\n* Leveragi
ng CSS cascading.\n* Building styles that respond to scales in ways that g
o beyond simple scale dependencies.\n* Various types of labeling tricks (c
onflict resolution and label priority\, controlling label density\, label
placement\, typography\, labels in various scripts\, label shields and mor
e).\n* Quickly controlling colors with LessCSS inspired functions.\n* Buil
ding symbology using GeoServer large set of well known marks.\n\nJoin this
presentation for a relaxing introduction to simple and informative maps.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Styling Natural Earth with GeoServer and GeoCSS - Andrea Aime
URL:http://talks.osgeo.org/foss4g-2023/talk/8SQSSV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZWSV8C@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:OSGeoLive is a self-contained bootable DVD\, USB thumb drive or
Virtual Machine based on Lubuntu\, that allows you to try a wide variety
of open source geospatial software without installing anything. It is comp
osed entirely of free software\, allowing it to be freely distributed\, du
plicated and passed around. It provides pre-configured applications for a
range of geospatial use cases\, including storage\, publishing\, viewing\,
analysis and manipulation of data. It also contains sample datasets and d
ocumentation. OSGeoLive is an OSGeo project used in several workshops at F
OSS4Gs around\nthe world.\n\nThe OSGeoLive project has consistently and su
stainably been attracting contributions from ~ 50 projects for over a deca
de. Why has it been successful? What has attracted hundreds of diverse peo
ple to contribute to this project? How are technology changes affecting OS
GeoLive\, and by extension\, the greater OSGeo ecosystem? Where is OSGeoLi
ve heading and what are the challenges and opportunities for the future? H
ow is the project steering committee operating? In this presentation we wi
ll cover current roadmap\, opportunities and challenges\, and why people a
re using OSGeoLive.\n- Project page https://live.osgeo.org\n- Link to the
presentation https://live.osgeo.org/en/presentation.html
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:OSGeoLive project report - Astrid Emde\, Angelos Tzotsos
URL:http://talks.osgeo.org/foss4g-2023/talk/ZWSV8C/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RNVJ3D@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:Introduction to basic but important concepts about Coordinate R
eference Systems (what is doable in 20 min \;)\n\n - Geographic Coordina
te (Reference) Systems\n - Different Datums/Ellipsoids\n - Projections
(Mercator\, UTM\, LCC\, ...)\n - EPSG catalog\n - WKT (well known tex
t) description\n - Reference to PROJ.org library\n\nThe purpose is to ex
plain basic concepts to have a good basis to understand later more complex
problems. The presentation will have a lot of links to go deeper into any
area of interest.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:Introduction to Coordinate Systems - Javier Jimenez Shaw
URL:http://talks.osgeo.org/foss4g-2023/talk/RNVJ3D/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-3JAH9S@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:GeoSolutions has been involved in a number of projects\, rangin
g from local administrations to global institutions\, involving GeoNode de
ployments\, customizations and enhancements. A gallery of projects and use
cases will showcase the versatility and effectiveness of GeoNode\, both a
s a standalone application and as a service component\, for building secur
ed geodata catalogs and web mapping services\, dashboards and geostories.
In particular the recent advancements in data ingestion and harvesting wor
kflows will be presented\, along with the many ways to expose its secured
services to third party clients. Examples of GeoNode’s builtin capabilit
ies for extending and customizing its frontend application will be showcas
ed.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:GeoNode at work: how do I do this\, how do I do that? - Alessio Fab
iani\, Giovanni Allegri
URL:http://talks.osgeo.org/foss4g-2023/talk/3JAH9S/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-YMDBBT@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:Japan fascinates the world with its rich culture\, materialized
with a full of cultural sites in its territory as example. To protect it\
, the Law for the protection of cultural properties established a “cultu
ral heritage” designation system\, where designated places should be pre
served. \nWith the collaboration of the Nara National Research Institute f
or Cultural Properties\, Japan cultural heritages has been mapped as a Web
GIS tool where more than 100\,000 places can be visualized. \nIn this talk
will be presented tool functionalities and technically its OpenSource bas
ed architecture.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N115 - Second Floor
SUMMARY:Mapping Japan cultural heritages with OpenSource based architecture
- IGUCHI Kanahiro\, Raymond Lay
URL:http://talks.osgeo.org/foss4g-2023/talk/YMDBBT/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-YVHNTL@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:The routing machine is about the route track a user can take fr
om one point to the other with directions after reaching each point. For p
aid services such as Google maps\, this already exists\, and Google has ap
plied a centralized model of usage. In this talk\, we will talk about the
type of libraries and already existing implementations that are almost dep
recated but we can keep alive\, since for the open source community\, the
ability to customize and change\, they are essential. There are no active
Open Source or community versions of the routing machine for maps. We need
to change that. We can do that by improving a couple of things that alrea
dy exist. Having more wrappers for different types of implementations\, s
ay Vue\, or React\, and finally Svelte. The routes should be updated and t
he selection of the type of route\, car\, bike\, or walking should reflect
the data received from maps. And define a safer business model. Open Sour
ce is more active and strong than paid and centralized services. We need t
o make sure that what we are offering and implementing as services to our
clients can reflect a similar dedication the first have.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Routing Machine\, state and side-effects - Marin Nikolli
URL:http://talks.osgeo.org/foss4g-2023/talk/YVHNTL/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XJH7JE@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T160000
DTEND;TZID=Europe/Tirane:20230629T163000
DESCRIPTION:**EOReader** is a remote-sensing opensource python library read
ing optical\nand SAR constellations\, loading and stacking bands\, clouds\
, DEM and spectral indices in a sensor-agnostic way.\n\n| **Optical**
| **SAR**
|\n|-------------------------------------------------
--------------------------------------------------------------------------
--------------------------------------------------------------------------
--------------------------------------------------------------------------
--------------------------------|-----------------------------------------
--------------------------------------------------------------------------
---------------------------------------------------------------|\n| `Senti
nel-2` and `Sentinel-2 Theia`
`Sentinel-3 OLCI` and `SLSTR`
`Landsat
` 1 to 9
`Harmonized Landsat-Sentinel`
`PlanetScope`\, `SkySat` and
`RapidEye`
`Pleiades` and `Pleiades-Neo`
`SPOT-6/7`
`SPOT-4/5`
`Vision-1`
`Maxar`
`SuperView-1`
`GEOSAT-2` | `Sentinel-1`
`C
OSMO-Skymed`
`TerraSAR-X`\, `TanDEM-X` and `PAZ SAR`
`RADARSAT-2` an
d `RADARSAT-Constellation`
`ICEYE`
`SAOCOM`
`Capella` |\n\nIt als
o implements **sensor-agnostic** features\, such as `load` and `stack` man
y bands:\n- satellite bands (optical or SAR)\n- spectral indices\n- clouds
\n- DEM\n\n## Context\n\nAs one of the [Copernicus Emergency Management Se
rvice](https://emergency.copernicus.eu/) Rapid Mapping and Risk and Recove
ry Mapping operators\, \n[SERTIT](https://sertit.unistra.fr/) needs to del
iver geoinformation (such as flood or fire delineation\, landslides mappin
g\, etc.) based on multiple EO constellations.\n\nIn rapid mapping\, it is
important to have access to various sensor types\, resolutions\, and sate
llites. Indeed\, SAR sensors are able to detect through clouds and during
nighttime while optical sensors benefit from of multi spectral bands to be
tter analyze and classify the crisis information.\n\nThis is why SERTIT de
cided to decouple the sensor handling from the extraction algorithms: the
latter should be able to ingest semantic bands without worrying about how
to load the specific sensor band or in what unit it is. \nThe assumption
was made that all the spectral bands from optical sensors could be [mapped
bands]( https://eoreader.readthedocs.io/en/latest/optical_band_mapping.ht
ml) between each other\, in addition to the natural mapping between SAR ba
nds.\n\n## Examples\n- [Why EOReader?](https://eoreader.readthedocs.io/en/
latest/notebooks/why_eoreader.html)\n- [Basic tutorial](https://eoreader.r
eadthedocs.io/en/latest/notebooks/base.html)\n- [Optical data](https://eor
eader.readthedocs.io/en/latest/notebooks/optical.html)\n- [SAR data](https
://eoreader.readthedocs.io/en/latest/notebooks/SAR.html)\n- [VHR data](htt
ps://eoreader.readthedocs.io/en/latest/notebooks/VHR.html)\n- [Water detec
tion on multiple products](https://eoreader.readthedocs.io/en/latest/noteb
ooks/water_detection.html)\n- [STAC](https://eoreader.readthedocs.io/en/la
test/notebooks/stac.html)
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:EOReader - Remote-sensing opensource python library for optical and
SAR sensors - BRAUN Rémi
URL:http://talks.osgeo.org/foss4g-2023/talk/XJH7JE/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-8TQ98Y@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:The presentation will be focused on the elaboration of the rele
vant legal basis of the Geological Service of Kosovo. In addition\, the de
scription of the main responsibilities will be made\, as well as the elabo
ration of technical analytical capacities which enable the development of
research in the field of geology.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Geological Service of Kosovo - Legal Infrastructure\, Responsibilit
ies & Technical - Analytical Research Capacities in Geology - Luan Morina
URL:http://talks.osgeo.org/foss4g-2023/talk/8TQ98Y/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KWDATH@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:Background & Problem: There are currently several software dedi
cated to the automatic creation of thematic maps. These can be proprietary
(e.g.\, ArcGIS Online\, Carto) or non-proprietary solutions (e.g.\, SDG V
iz\, AdaptiveMaps\, the GAV Toolkit\, the Geoviz Toolkit). An important dr
awback of these state-of-the-art solutions is that the expertise encapsula
ted in such software (e.g.\, enabling to choose a type of map or visual va
riables depending on the characteristics of the data contained in the map)
\, is usually not well communicated to the user. That is\, users can use t
hese tools to create meaningful maps for their open geographic datasets bu
t are offered little support regarding knowing why some suggestions of the
matic map types were made (e.g.\, why a dot map is proposed by a toolkit i
nstead of a choropleth map). Put simply\, users get little insight into th
e decision processes of current tools/toolkits for thematic web creation.\
n\nContributions & Target audience: To help users learn about the decision
processes of software for automatic map creation\, this work introduces t
he 3D4DT approach. The approach uses JSON (JavaScript Object Notation) as
a machine-readable format to represent decision trees and subsequently map
s JSON elements to user interface elements for an interactive 3D scene. Th
e contributions of the work are twofold: 1) a controlled vocabulary to sup
port the creation of machine-readable descriptions for decision trees of t
he Cartography literature\; and 2) an approach to navigate these decision
trees as interactive scenes in 3D. The approach is implemented as an open-
source prototype. It is relevant to both developers and users of software
for automatic thematic map creation. The controlled vocabulary is relevant
to developers\, who can encode the decision trees underlying their softwa
re as machine-readable data\, and make the ‘brain’ of their software a
vailable for reuse in multiple use cases. The exploration of the decision
trees as an interactive scene is relevant to users who can retrieve inform
ation about the inner workings of software for map creation in an interact
ive format.\n\nImplementation: The prototype is available as a web-based a
pplication on GitHub. The server is run using Node.js. To speed up the dev
elopment of the frontend\, we have used Vitejs. The 3D interactive scene i
s implemented using the JavaScript library Three.js. The choice of Three.j
s was motivated by the fact that it is 1) open source\, 2) expressive enou
gh to create a variety of 3D scenes in the browser\, and 3) is actively ma
intained by a community of contributors.\n\nEvaluation: To evaluate the ex
pressiveness of the controlled vocabulary (contribution 1)\, the work used
three decision trees for thematic map creation: 1) DecisionTreeA: the dec
ision tree of the AdaptiveMaps open-source prototype (Degbelo et al.\, 202
0)\; 2) DecisionTreeB: the decision tree for the choice of thematic map ty
pes from (Kraak et al.\, 2020)\; and DecisionTreeC: the visual variable sy
ntactics from (White\, 2017)\, which was converted to a decision tree. To
evaluate the usability of the 3D interactive scene (contribution 2)\, the
open-source prototype was tested through a lab-based user study. The study
compared the interaction with two decision trees using interactive 3D sce
nes to the same information displayed as a simple website (text+pictures).
12 participants were recruited via personal messages. They were asked to
interact with DecisionTreeA and DecisionTreeB using both conditions (inter
active 3D vs static). Six participants stated to have no experience at all
in the field of geoinformatics\, four claimed to be slightly experienced
and two considered themselves very experienced. None of the participants w
as familiar with the literature which was used for DecisionTreeA and Decis
ionTreeB. A critical difference between DecisionTreeA and DecisionTreeB is
that the latter was simpler in its hierarchical structure. We measured th
e efficiency (time taken to answer questions)\, effectiveness (number of c
orrect answers\, during the interaction with the prototype)\, and memorabi
lity (number of correct answers to questions asked to the users after the
prototype has been shut). The key takeaways from the experiments were: 1)
participants were slightly faster in the text+pictures condition\, but the
differences in efficiency values were not statistically significant\; 2)
using the 3D interactive scene\, participants could answer questions perta
ining to DecisionTreeB more accurately\; differences in effectiveness for
the more complex DecisionTreeA were not statistically significant\; and 3)
the differences in memorability between the two conditions (interactive 3
D vs static) were not statistically significant. Hence\, an interactive 3D
scene could be used as a complementary means to help users understand how
thematic maps are created especially when designers wish to convey this i
nformation most accurately.\n\nRelevance for the FOSSG Community: Since De
cisionTreeA is the brain of the AdaptiveMaps open-source prototype that he
lps create web maps semi-automatically\, helping users visually explore th
at decision tree through the 3D4DT approach is one way of realizing the re
quirement of algorithmic transparency for intelligent geovisualizations. T
he controlled vocabulary is relatively simple and could be reused to promo
te algorithmic transparency for other types of open-source geospatial soft
ware\, if their decision rules can be modelled as decision trees (i.e.\, i
f-then-else rules). \n\nReproducibility: the data collected during the use
r study\, the script for the analysis as well as all questions answered by
the participants can be accessed at https://figshare.com/s/60b1a4a12f9bd3
2d2759. The source code of the AdaptiveMaps prototype\, which used Decisio
nTreeA to create various thematic maps\, can be accessed at https://github
.com/aurioldegbelo/AdaptiveMaps . The source code of the 3D4DT prototype\,
the JSON schemas\, and the encoding of the decision trees as JSON can be
accessed at https://github.com/aurioldegbelo/3D4DT .\n\nReferences: \nDegb
elo\, A.\, Sarfraz\, S. and Kray\, C. (2020) ‘Data scale as Cartography:
a semi-automatic approach for thematic web map creation’\, Cartography
and Geographic Information Science\, 47(2). \nKraak\, M.-J.\, Roth\, R.E.\
, Ricker\, B.\, Kagawa\, A. and Sourd\, G.L. (2020) Mapping for a sustaina
ble world. New York\, USA: The United Nations.\nWhite\, T. (2017) ‘Symbo
lization and the visual variables’\, in J.P. Wilson (ed.) Geographic Inf
ormation Science & Technology Body of Knowledge.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:3D4DT: An Approach to Explore Decision Trees for Thematic Map Creat
ion as an Interactive 3D Scene - Auriol Degbelo
URL:http://talks.osgeo.org/foss4g-2023/talk/KWDATH/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-LAY3QC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:The open source based environmental impact assessment(EIA) deci
sion support verification tool(verification tool) is a web-based tool for
verifying the EIA algorithm based on the EIA review decision support algor
ithm using data for each Environmental Impact.\nThis verification tool was
developed using open source projects such as PostGIS\, GeoServer\, and Op
enlayers. However\, the flowchart library used a commercial software calle
d GoJS.\nThis verification tool is intended to verify the adequacy of the
implementation of the EIA algorithm developed by experts in each Environme
ntal Impact.\nIt is possible to support comprehensive decision-making\, in
cluding opinion gathering\, by operating the review decision-making algori
thm based on data by Environmental Impact and environmental impact analysi
s results.\nThe spatial analysis required to verify the algorithm was deve
loped using OpenGXT of the OGC WPS service. It includes a way to visualize
the result processed through this spatial analysis function.\n\nThis pape
r is based on the findings of the research project “Development of integ
rated decision support model for environmental impact assessment project\,
”(2023-003(R)) which was conducted by the Korea Environment Institute (K
EI) and funded by research and development project (Project No. 2020002990
003) of the Environmental Industry & Technology Institute (KEITI) and the
Ministry of Environment (MOE).
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N115 - Second Floor
SUMMARY:Development of tool for validity of decision support algorithm for
environment impact assessment (EIA) Based on open source - jinwoo park
URL:http://talks.osgeo.org/foss4g-2023/talk/LAY3QC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-NMRRZJ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:GeoServer is the start of so many great open source success sto
ries. \n\nThis talk introduces the core GeoServer application and explores
the ecosystem that has developed around this beloved OSGeo application. O
ur presentation draws on the GeoServer ecosystem for use-cases and example
s of how the application has been used successfully by a wide range of org
anizations.\n\nEach use-case highlights a capability of GeoServer providin
g an overview of the technology drawn from practical examples.\n\n* Andrea
Amie is on hand to share success stories highlighting GeoServer use in ma
naging vulnerable ecosystems\, agriculture information management\, and ma
rine data management.\n* Jody Garnett will look at how GeoServer technolog
y powers cloud services\n* Gabriel will look at am amazing remixes for Clo
ud Native GeoServer\n* GeoServer technology powering the OSGeo community\,
including GeoNode\, geOrchestra\n* A showcase of examples collected from
our user list\n\nAttend this talk to learn what GeoServer is good for out-
of-the-box\, and for inspiration on what is possible using GeoServer and t
he FOSS4G community.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:GeoServer used in fun and interesting ways - Andrea Aime\, Jody Gar
nett
URL:http://talks.osgeo.org/foss4g-2023/talk/NMRRZJ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PDLSXW@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:Project PLATEAU is an initiative led by the Ministry of Land\,
Infrastructure\, Transport and Tourism of Japan (MLIT)\, to develop and ut
ilize 3D city models compliant with CityGML standards. MLIT aims to establ
ish rules of creation of 3D city models as part of general operations in
each local government\, and also to release them as open data to promote u
tilization for urban planning and business creation.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Project PLATEAU ~The initiative of Digital Twin in Japan~ - UCH
IYAMA\, Yuya
URL:http://talks.osgeo.org/foss4g-2023/talk/PDLSXW/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QHJGRN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:In January 2022\, OSGeo and [OGC](https://www.ogc.org/) signed
a new and [updated version of the Memorandum of Understanding (MoU)](http
s://www.ogc.org/pressroom/pressreleases/4709) that aims to maximize the ac
hievement of the mission and goals of the two organizations: promoting the
use of Open Standards and Open source software within the geospatial deve
loper community. Identifying open source technologies that could be used a
s Reference Implementations for OGC Standards and validating OGC complianc
e tests are examples of activities that can take place within the scope of
the agreement.\n\nMore than one year after the agreement was signed and a
lmost one year after it was introduced to the OSGeo community in a keynote
at FOSS4G 2022\, this presentation will summarize all activities accompli
shed and future plans\, including the establishment of the OSGeo Standards
Committee within OSGeo and the organisation of the [3rd joint code sprint
](https://developer.ogc.org/sprints/20/)\, in Switzerland\, together with
the Apache Software Foundation.\n\nThe presentation will also reiterate th
e benefits of the new agreement\, which allows OSGeo charter members to re
present the priorities of OSGeo in the development of OGC Standards and su
pporting documents and services.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:OSGeo and OGC MoU: one year later! - Tom Kralidis\, Angelos Tzotsos
\, Joana Simoes\, Codrina Ilie
URL:http://talks.osgeo.org/foss4g-2023/talk/QHJGRN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-CRPWUS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:The interest on urban pedestrian networks is growing\, with imp
acts centered at UN SDGs numbered 3\, 11\, 10 and 13: the improvement of a
ccessibility helps in reducing inequalities and the fostering of non-motor
ized locomotion improves well-being and sustainability in urban scenarios.
The idea behind OpenSidewalkMap is to leverage the multi-purpose OpenStre
etMap data for the pedestrian network data. The structure of the project i
s decentralized\, with localities deployed as nodes on a world web-map. At
each node there’s a modular structure within a webpage\, containing app
s that have a different role\, in order to create what is intended to be a
full-fledged inventory\, whose functionality can be expanded as new modul
es can be added. Currently there are four modules: “Webmap” containing
an interactive cartographic representation of the data\; “Optimized Rou
ting” that uses the data to create an optimized routing\, currently only
for a wheelchair profile based on an empiric equation\; “Dashboard”
featuring statistical charts to look at the bigger picture of the data\, m
ainly focused on value percentages\, thus giving attribute completeness\,
also giving a look at the data aging and number of revisions\; “Data qua
lity tool” looking at most common possible errors on data\, giving direc
t link to editors\, being at this point focused on finding invalid values\
, with geometrical and topological error detection planned to be included\
; there are 4 planned modules: “data watching” to monitor changes on d
ata\, to track and combat possible vandalism against data since OSM data i
s universally editable\; “Tiles” giving raster and maybe vector tiles\
; “API” giving features on request\; “Surveying And Validation” to
list projects in different platforms/editors to expand and validate avail
able data. This way the inventory will include continuously the full cycle
of data: creation and collection\; storage\, maintenance and management\;
application and analysis. The project is aimed to have zero-maintenance
costs\, as long as everything is hosted using current freely available Mic
rosoft github infrastructure\, with all code and data being maintained ins
ide github repositories\, webpages deployed with github pages\, updated us
ing github actions. In case of shutdown of any of these services\, the sof
tware can still be deployed in another server infrastructure with a simila
r workflow. There is lots of room for improvement\, with only the node for
the city of Curitiba being available as of february 2023. The homepage of
the code is available at: https://kauevestena.github.io/opensidewalkmap/
.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Opensidewalkmap: A Project And Open Source Framework For An Web-Bas
ed Urban Pedestrian Network Inventory Using Openstreetmap Data - Kauê de
Moraes Vestena
URL:http://talks.osgeo.org/foss4g-2023/talk/CRPWUS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ECHVLX@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:The ever-increasing threat from disaster is an urgent call for
a proactive discourse on pragmatic elimination and reduction of the challe
nges and stresses caused by disasters. This study\, therefore\, leverages
on the research gap as it applies to the application of crowdsourced rapid
response mapping in a developing country of Nigeria\, where\, critical ge
ospatial data is grossly unavailable to respond to vulnerable resilient co
mmunities. The study deployed two research techniques namely: participator
y crowdsourced mapping and gamification. The HOT tasking manager data anal
ytics was used to analyze the level of participation and contribution of v
olunteer mappers over time while QGIS was used to produce maps unveiling b
uilding footprints generated in OSM\, before and after Mapathon. The study
delineated 8 LGAs for a mapping task of 2015 grids and 639 grids for Mapa
thon battle season-1 and 2 respectively.Season-1 was the months of flood(R
ainy Season) while Season-2 was the flood receding months (dry season) Re
sults unveiled analysis of flood response mapping season-1\, had a total
of 571\,659 edits comprising 481\,912 buildings and 22\,244km of roads con
tributed by initial 7\,601 participants\, but completed by 1\,644 voluntee
rs\, mapping 4\,946 grids within a timeline of 38months at the rate of thr
ee hours 38minutes per task. 70% of volunteer mappers engaged were beginne
r mappers Maps showing before and after Mapathon in OSM were produced for
ONELGA\, Numan Sarbon Birnin and Ilorin West LGAs respectively. However\,
analysis of flood response mapping season-2\, unveiled a total of 357\,168
edits comprising 325\,023 buildings and 7\,438km of roads were contribute
d by the initial 4\,006 participants\, but completed by 801 volunteer mapp
ers using 2\,238 grids within a timeline of 14months at the rate of two ho
urs 33minutes per task. Maps showing before and after in OSM were produced
for Afikpo North\, Warri South\, Logo and Jamare LGA respectively. The St
udy contributed to a measurable target of SDGs 1 to 7\, 11\, 13\, 15 and 1
7. The study generated massive critical open geospatial data needed for ef
fective disaster response and SDGs\, and paving way for effective geoinfor
mation e-governance in Nigeria. Lastly\, the study promotes the relevance
of citizen-generated data for national geospatial data infrastructure deve
lopment and participatory crowdsourced mapping using OpenStreetMap at loca
l levels. The study has also bridged a critical scientific research gap an
d inquiry in OSM GIScience.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:OpenStreetMap Seasonal Differential in Citizen Science Volunteered
Response Mapping of Flood Disaster Vulnerable Communities in Nigeria - Vic
tor N.Sunday
URL:http://talks.osgeo.org/foss4g-2023/talk/ECHVLX/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-Q7GHV7@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:The View Server (VS) is MIT licensed\, Docker based\, cloud-nat
ive\, scalable software stack providing external services for searching\,
viewing\, and downloading Earth Observation (EO) data. Services implementa
tions are following OGC Web services standards STAC\, OpenSearch\, WMS\, W
MTS\, WCS.\n\nHaving EOxServer and MapCache as core components\, enables E
O Data publication in a modular and configurable way. The process starts w
ith data harvesting\, preprocessing and metadata ingestion and ends with s
erving pre-cached and on demand rendered images through an attached Web cl
ient based on OpenLayers and EOxC libraries or on individual service endpo
ints.\n\nEOxServer allows dynamic generation of visual images from multi-s
pectral data. In this way\, specific bands or channels of the original ima
ges can be selected as the grey or red\, green\, and blue output colour ch
annels. It also supports flexible rendering based on previously extracted
image statistics\, pansharpening on the fly\, filtering the long time peri
ods of products intersecting with the query in CQL syntax utilizing metada
ta parameters and more.\n\nVS provides both S3\, OpenStack Swift\, HTTP an
d local files support when considering data storage and can be deployed in
Docker Swarm environment via docker-compose templates or in Kubernetes en
vironment as a set of Helm charts.\nThe software stack was and is used by
EOX in a quite a number of operational deployments for ESA\, like the VirE
S projects\, Copernicus Space Component Data Access system (CSCDA)\, or mo
re recently Earth Observation Exploitation Platform Common Architecture.\n
\nLinks:\nhttps://eox.at/2021/09/eoxserver-1-0/\nhttps://eoxserver.org/\nh
ttps://github.com/EOxServer/eoxserver/\nhttps://gitlab.eox.at/vs/vs
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:View Server - EO Data Visualization in a Cloud Native Way - Lubomir
Dolezal
URL:http://talks.osgeo.org/foss4g-2023/talk/Q7GHV7/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-DF3KEG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:Raster data is a type of digital image data that is stored and
processed as a grid of cells\, each of which represents a specific area or
location in the image. This grid is known as a raster or pixel grid\, and
each cell contains a value that represents a characteristic of the corres
ponding area or location in the image\, such as color\, elevation\, temper
ature\, or other attributes. Depending upon the resolution of the data the
se raster file sizes can vary from a few MBs to few GBs. Hence reading dat
a from a large set of raster dataset which has time dimension associated w
ith it is challenging.\n\nPostgreSQL can be used to store time series rast
er datasets\, which are raster datasets that have a time dimension associa
ted with them. This can be useful for storing and analyzing raster data th
at changes over time\, such as satellite images\, climate data\, or land c
over change data.\n\nTo store time series raster datasets in PostgreSQL\,
we will use the postgis_raster extension\, which provides support for stor
ing and manipulating raster data in the database\, and the TimescaleDB ext
ension to add time series functionality to PostgreSQL\, allowing us to sto
re and query raster data with a time dimension.\n\nUsing the TimeScaleDb e
xtension we will partition the raster table by converting it to hypertable
which is what TimescaleDB uses to optimally store and process time series
data. This can help us to optimize query time. \nFor aggregated values f
rom raster data over time and space\, we will use the Continuous aggregate
feature of TimescaleDB which is a form of materialized view to pre-comput
e and store raster data over time.\nMoreover\, TimescaleDB allows compress
ion of data which can be very helpful in cases where the data is huge whic
h is usually the case with raster datasets in postgres saving us space in
the Database and optimizing some queries. \n\nThe proposed presentation wi
ll be of interest to developers\, data scientists\, and geospatial analyst
s who work with Raster datasets. It will provide a practical guide to quer
ying the raster datasets in PostgreSQL with TimescaleDB and postgis_raster
extension.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Time series raster data in PostgreSQL with the TimescaleDB and post
gis_raster - Jashanpreet Singh
URL:http://talks.osgeo.org/foss4g-2023/talk/DF3KEG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-VGTSTV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:Discrete Global Grid Systems (DGGS) are gaining popularity as a
new method of geospatial data representation. This presentation will prov
ide an overview of the concept of DGGS and its advantages over traditional
geospatial data representation methods. \n\nWe will explore the similarit
ies and differences between these different DGGS frameworks\, including th
eir cell shapes\, grid resolutions\, and ability to handle different types
of geospatial data. We will also discuss the benefits of using DGGS in ge
ospatial data applications\, such as remote sensing\, climate modeling\, a
nd environmental monitoring.\n\nOverall\, this presentation will provide a
comprehensive overview of the concept of DGGS and its potential applicati
ons in geospatial data analysis and visualization. Attendees will gain a d
eeper understanding of the advantages and challenges associated with diffe
rent DGGS frameworks and will gain insights into the ongoing research effo
rts in this field.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:DGGSs and you! - James Banting
URL:http://talks.osgeo.org/foss4g-2023/talk/VGTSTV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-D9EVPE@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T163000
DTEND;TZID=Europe/Tirane:20230629T170000
DESCRIPTION:National Land Survey of Finland (NLS) has built multiple featur
e services based on the OGC API Features standard since 2019. These servic
es provide cadastral and topographic data\, buildings\, geographic names\,
and addresses both as open and contract-based APIs.\n\nThe engine behind
these services is Hakunapi – a high performance server implementation to
easily build “off-the-shelf” Simple Features and customized Complex F
eatures services with geospatial data backed by a PostGIS database. Curren
tly the OGC API Features (Part 1\, 2 and 3) standard is supported. The cod
ebase is based on Java\, and it utilizes also other geospatial libraries s
uch as JTS Topology Suite and GeoTools.\n\nHakunapi is now Free Open-Sourc
e Software available at GitHub with the version 1.0 released in May 2023.
On the last few years NLS has internally used the library for services pro
viding both Simple Features (like traditional topographic database) and Co
mplex Features (cadastral registry and geographic names with some hierarch
ical feature structures too).\n\nThis talk presents key features and benef
its of using Hakunapi for implementing feature services based on the OGC A
PI Features standard. Also experiences and best practices by NLS on develo
ping these services and our roadmap towards modern OGC API services is dis
cussed.\n\nDemo: https://beta-paikkatieto.maanmittauslaitos.fi/inspire-add
resses/features/v1/ \n\nCode: https://github.com/nlsfi/hakunapi
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:OGC API feature services built with Hakunapi - Teemu Sipilä
URL:http://talks.osgeo.org/foss4g-2023/talk/D9EVPE/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RQB7FG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230629T170000
DTEND;TZID=Europe/Tirane:20230629T173000
DESCRIPTION:Powerful earthquakes hit southern Turkey and Syria on 6 Februar
y 2023. These earthquakes in Turkey and Syria caused thousands of casualti
es and destroyed cities. Geospatial infrastructure is critical to respond
to these earthquakes during rescue operations\, humanitarian effort as wel
l as planning recovery activities.\n\nYercizenler coordinated mapping acti
vation with the collaboration of Humanitarian OpenStreeMap team to improve
open geodata infrastructure in the earthquake affected region and support
ing humanitarian response in the scope of mapping. \n\nTürkiye Earthquake
s Mapping Response aims to complete open map data infrastructure before an
d after the event in affected areas. This response is structured with foll
owing workstreams\; Remote Mapping\, Post-disaster Field Data Collection\,
Global Community Activation and Geo-data Integration.\n\nIn this talk\; w
e will talk about how open data and community activation helped save lives
after earthquakes\, what challenges we faced and what we have learnt duri
ng the Türkiye Earthquakes mapping Response effort.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Türkiye and Syria Earthquakes Mapping Response - Said Turksever
URL:http://talks.osgeo.org/foss4g-2023/talk/RQB7FG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-BDS8PS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T093000
DTEND;TZID=Europe/Tirane:20230630T100000
DESCRIPTION:“Whether it is to know where children are\, what access they
have to facilities (education\, health\, transportation)\, what environmen
t they live in (water\, air)\, where risks exist (hazards\, diseases)\, wh
ere events happen or where services and resources are available\; most of
the operational data used by UNICEF is geospatial” (UNICEF Geospatial Ro
admap\, 2019). At UNICEF we realize that we need to leverage geospatial in
formation to enhance decision-making and optimize resource allocation and
drive effective interventions. Geo-enabling UNICEF’s data\, systems and
processes aims at transforming data into easily accessible\, readily avail
able\, and actionable geospatial information that can address key question
s\, such as: “How many children have been affected by a flood?”\, “W
here children have limited access to schools and limited access to health
services?”. This information is critical to support decision-making to u
ltimately drive better results for children.\nUNICEF has recently adopted
a hybrid corporate geospatial architecture\, which aims at bringing togeth
er the advantages of both commercial and open-source GIS world. This prese
ntation aims at discussing how UNICEF is leveraging modern open-source geo
spatial solutions to address some of the key data-management challenges.\n
Specifically\, two open-source geospatial projects developed by UNICEF wil
l be showcased and discussed: GeoRepo and GeoSight. GeoRepo is a web-based
system that will help us store\, manage and share a commonly agreed\, ver
sioned\, official set of administrative boundaries and other core geospati
al datasets. It will help us ensure that geospatial data is used consisten
tly across all internal systems and will also strengthen our interoperabil
ity with external systems. GeoSight\, on the other hand\, is a web geospat
ial data platform developed by UNICEF to bridge the gap between web mappin
g systems and the Business Intelligence / data analytical platforms. GeoSi
ght is specifically designed to simplify the process of harmonizing data f
rom multiple data sources. It also allows users to easily create online ma
ps for visualizing multiple indicators at subnational levels (e.g. at the
province or district level). Both platforms are built using Django and Rea
ct and use modern open-source geospatial standards and libraries\, such as
MapLibre and vector tiles.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:How UNICEF is leveraging open-source geospatial solutions to drive
better results for children - Jan Burdziej
URL:http://talks.osgeo.org/foss4g-2023/talk/BDS8PS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-V9TPXN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T100000
DTEND;TZID=Europe/Tirane:20230630T133000
DESCRIPTION:In recent years\, the combination of technological advances and
spatial data abundance revolutionised the field of geoinformation (GI). N
ew methodologies and techniques established in other fields of knowledge p
roved to be relevant to keep up to date and fully benefiting from all this
technological richness. Consequently\, new areas of knowledge have emerge
d\, such as geospatial artificial intelligence (GeoAI) or big geodata. Sim
ultaneously\, the formulation in 2015 of the 2030 Agenda for Sustainable D
evelopment and its multiple goals by the United Nations (UN)\, impose a sp
ecific framework for the application and further development of geoinforma
tion science. Furthermore\, the recent COVID-19 pandemic accelerated the t
ransition towards different modalities of distance education as well as th
e arrival of multiple digital instruments to fulfil this purpose. At the s
ame time\, the use of free and open-source software (FOSS) keeps gaining m
omentum\, standing out as the best technological solution to attain sustai
nable and democratic approaches to geospatial problems.\n\nAll these facto
rs have profoundly impacted the way of teaching with GI and about GI. Both
technical and socio-emotional skills required to successfully perform as
a GI scientist in the near future are changing. And so are the means to le
arn those skills. As a result\, the training curriculum for educators in t
his field is being revised and updated. In this presentation\, we will fir
st discuss the challenges currently faced by educators in the field of GI
and explore new didactic and pedagogical proposals to overcome them. We wi
ll analyse how teaching GI science in academic settings (i.e.\, high schoo
l\, university) differs from teaching it to staff members at public organi
sations. We will then explore how to successfully implement the ADDIE (i.e
.\, Analyse-Design-Develop-Implement-Evaluate) model of instructional desi
gn in both settings. Finally\, we will explore together in detail a recent
ly designed refresher course on geodata analysis and dissemination that co
mbines state-of-the-art pedagogical approaches and the use of FOSS4G.\n\n*
*Schedule** \n\nDate: June 30th\, 2023\n\n- 09:00 – 10:15 Welcome and i
ntroduction \nPresentation I: Teaching GI with FOSS today: challenges an
d opportunities\n- 10:15 – 10:30 Break\n- 10:30 – 11:30 Presentation I
I: Differences between academic and organisational training. How to proper
ly design education for different educational settings?\n- 11:30 – 11:40
Break\n- 11:40 – 12:00 Case study: Online refresher course “Geo-web a
pplication building with FOSS”\n- 12:00 – 12:30 Plenary discussion\n-
Closing\n\n[Register here](https://forms.gle/PVp5F12CrDwmt4qs9) for partic
ipating in the event.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Teaching GI with FOSS tools: an update for higher education teacher
s and trainers at public organizations - Lucas De Oto
URL:http://talks.osgeo.org/foss4g-2023/talk/V9TPXN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-7JPRVK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T103000
DTEND;TZID=Europe/Tirane:20230630T110000
DESCRIPTION:Among the human-wildlife conflicts\, wildlife vehicle collision
s is one of the most evident to the general public. Human-wildlife conflic
ts can be defined as the breaking of a relationship of coexistence which o
ccurs when the needs or the behavior of a species negatively affect human
activity. Among the causes there are: land use change\, especially urbaniz
ation\, with the construction of infrastructures that interrupt natural ha
bitats\, but also conversion of forests to agriculture and pastures\, that
leads to damages of crops and predation of livestock and also the increas
ed presence of people in wilderness area for recreational activities (Corr
adini et al. 2021). Often these conflicts lead to the killing and persecut
ion of species\, thus compromising the conservation of the species itself.
This problem is globally widespread\, both in those countries where the L
and Use Change already occurred in historical times as well as where the l
and use change is presently occurring at a dramatic pace. In the last deca
des\, in Europe there was actually a recover of large mammal populations\,
due to the legal protection and abandonment of traditional agriculture (C
hapron et al 2014). The increased amount of large mammals lead to an incre
ased human wildlife interaction\, including roadkill and car accidents. \n
This study investigates wildlife vehicle collisions in the territory of th
e Italian Autonomous Province of Trento (PAT) 541\,692 inhabitants\, exten
ding for 6\,207 km2\, a mountainous area interested by a significant summe
r and winter tourist presence. The species taken into account are Roe deer
(Capreolus capreolus) and Red deer (Cervus elaphus) that are the most com
mon species involved in road accidents in the area. In the last 10 years a
n average of 700 annual collisions were registered\, the animals are often
killed and the vehicles are heavily damaged leading to injuries and occas
ionally to human fatalities. A solution of the problem is becoming urgent
in a highly anthropic environment like the Alpine one. \nDifferent measure
s can be adopted to reduce the risks of collisions\, e.g. underpasses\, ov
erpasses\, viaducts and fly-overs\, fences\, animal detection systems\, wa
rning signs\, nets\, or also a combination of the former (van der Ree et a
l 2015). \nThe main purpose of this work was to use FOSS4G to identify the
road sections characterized by a greater number of collisions and to prop
ose and design practical solutions focusing mitigation efforts on these ho
tspots. The practical solutions were chosen among those more appropriate t
o each specific situation and when a specific project is proposed it inclu
des the costs to realize it.\nInitially the work focused on the geostatist
ical study of roads collisions with ungulates to determine their trends in
space and time. The road sections characterized by a greater number of ac
cidents were identified with accuracy and reliability\, by combining GIS g
eostatistical analysis and a detailed study of the morphology\, land cover
and other boundary conditions. \nQGIS 3.16.6 was used to import data and
standardize the data set\, as well as to process data and produce heat ma
ps\, analysis and most of the final maps. GRASS GIS 8.2 was used to perfor
m data integrity check fixing data errors and resample or recombine data f
rom different sources.\nA large amount of different environmental co varia
tes such as forest coverage\, ecological corridors\, roads and infrastruc
tures were collected while others (e.g. contours and slope) were created s
tarting from the Digital Elevation Model (DEM)\, the Digital Terrain Model
(DTM). Data about ungulates collisions were provided by the Wildlife Serv
ice of the Autonomous Province of Trento.\nSince the January 2000\, every
road collision caused by ungulates reported by the Forest Service or by th
e Hunters Association or by the Road Service was stored in a geo database.
In this database are stored the date\, the species of affected ungulate
\, the sex\, an indication of the age and the geographical coordinates. La
st update used for this study is 08/2022 and the datum is ETRS89\, frame E
TRF2000\, projection UTM zone 32 N.\nThe ungulates are active mainly durin
g the first at dusk and dawn when the greatest number of investments are a
lso recorded (Mayer et al. 2021). Speed limit of the roads in the hotspots
are often disregarded. In a straight tract located on the state road 47 i
n Valsugana\, the maximum speed is set at 90 km/h and about 60% of the ve
hicles transit with a speed exceeding the limit (90 km/h) with a daily ave
rage of more than 19\,000 vehicles per day.\nOnce the areas of interventi
on were identified with QGIS we carried out on-site inspections to define
the best solutions to be adopted in each specific case. GIS processing pro
ved to be extremely informative both in the preliminary design phase and i
n the final design phase in which the works and interventions were defined
in detail.\nThe five hotspots chosen for intervention were located along
four state roads and one provincial road For each case a specific analysi
s was carried out and a series of tailored interventions (underpasses\, ov
erpasses\, viaducts and fly-overs\, fences\, road tunnels) and works aimed
at mitigating road accidents with ungulates were identified. Each site wa
s different and posed different construction problems and for each site we
developed a specific solution. In addition\, a first rough estimative met
ric computation is developed to determine the order of magnitude of the co
st required to implement the recommended interventions.\nThe proposed proj
ects may create a guideline for the future politics of the provincial gove
rnment. \nMoreover\, with the aim of creating a tool for planning interven
tions at provincial scale a new map was created classifying the road secti
ons in 5 categories based on the number of road accidents with ungulates.
\nSharing the capabilities of FOSS4G to improve the procedures in designi
ng interventions that can reduce the collisions can inspire further resear
chers and technicians to experiment these solutions to plan the positionin
g of crossing structures\, thus helping to mitigate Human-wildlife conflic
t (HWC).
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Human-wildlife conflict and road collisions with ungulates. A risk
analysis and design solutions in Trentino\, Italy - Marco Ciolli
URL:http://talks.osgeo.org/foss4g-2023/talk/7JPRVK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-G8GFAC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T103000
DTEND;TZID=Europe/Tirane:20230630T110000
DESCRIPTION:Let's look away from familiar continents and comfortable symbol
ics. When you are making an entirely new world\, how do you map it? When a
ny choice can be made from scratch\, why game makers sometimes use common
carthographic paradigms\, or circumvent them? And given we are at a GIS co
nference\, what can we learn from imaginary maps\, that can improve our re
al-world work? Let's connect a Nintendo Switch to a projector and dive int
o games!
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:What in-game maps can teach us - Ilya Zverev
URL:http://talks.osgeo.org/foss4g-2023/talk/G8GFAC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-EC7HDG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T103000
DTEND;TZID=Europe/Tirane:20230630T110000
DESCRIPTION:In recent years\, the software industry has witnessed a remarka
ble trend away from traditional standalone applications and towards online
multiplayer platforms that offer users a more integrated and collaborativ
e experience. \n\nAs this trend continues\, it is becoming increasingly im
portant for open source tools to stay competitive by providing seamless ac
cess to data and connectivity.\n\nIn this talk I will introduce mapstack\,
outline our mission to bring all of the world’s open location data toge
ther in one place\, and share my thoughts on how such an unprecedented ope
n resource will benefit the wider FOSS4G ecosystem.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Why FOSS4G Needs a Global Open Data Platform - Christopher Brown
URL:http://talks.osgeo.org/foss4g-2023/talk/EC7HDG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XZAY9C@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T103000
DTEND;TZID=Europe/Tirane:20230630T110000
DESCRIPTION:Motivation\n\nNew\, evolving technologies allow to host data an
d program code (smart contracts) on distributed blockchains. Beside other
aspects\, like validating geospatial data and their transactions\, this te
chnology might also be interesting for building distributed services for t
he ‘classical’ spatial data infrastructures. \n\nPrototype\n\nDuring
the last months a prototype was developed to test the capabilities of sma
rt contracts to distribute spatial data using the OGC API – Features spe
cification and gain some experiences in its design\, typical workflows\, l
imitations etc.\nThe prototype is designed as smart contract on the ‘Int
ernet Computer (IC)’ blockchain (see https://internetcomputer.org/). Thi
s allows to store program code and the spatial data in one container on th
e blockchain and execute it on demand.\nTo simplify the test\, a fixed wor
kflow is implemented. \n\n1) Data providers upload a spatial dataset (curr
ently glider GNSS tracks in the IGC format) on a simple webpage running wi
thin the container\n\n2) The spatial data is persisted on the IC blockchai
n \n\n3) Users access the data via OGC API – Features with their browser
(html representation) or with their GIS\n\nPresentation\n\nIn the present
ation\, I would like to share some experiences on developing geospatial in
terfaces in a blockchain environment and show the current state of the pro
totype. Especially the coding with the programming language ‘Motoko’\,
the exposed interfaces\, and the distribution on the blockchain with its
costs will be addressed. \nI would further like to discuss use cases of th
e approach\, e.g. a simplified data distribution for smaller data provider
s\, and the potential extensions on this approach\, like introducing a use
r management\, adding metadata or integrating dynamic data sources. \n\nLi
nks\n- Entrypoint (OGC API Features): https://mtlom-hiaaa-aaaah-abtkq-cai.
raw.ic0.app/\n- Github page (mainly Motoko code): https://github.com/jansc
hu/igc_tools \n\nRelated:\n- Internetcomputer (IC): https://internetcomput
er.org/\n- IGC - International Gliding Commission – GNSS Flight Recorder
s Spec: https://www.fai.org/sites/default/files/igc_fr_specification_2020-
11-25_with_al6.pdf \n- OGC API – Features: https://ogcapi.ogc.org/featur
es/
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Running OGC API - Features as Smart Contract - Jan Schulze Althoff
URL:http://talks.osgeo.org/foss4g-2023/talk/XZAY9C/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-HVEF8X@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T103000
DTEND;TZID=Europe/Tirane:20230630T110000
DESCRIPTION:GeoNode is a Web Spatial Content Management System that uses th
e Django Python web framework. MapStore is an open source WebGIS product a
nd highly customizable framework that has been used as the default user in
terface to visualize catalog\, map viewer and geospatial applications in G
eoNode.\n\nThis presentation provides an overview of the integration of th
e MapStore framework inside the GeoNode ecosystem and the main differences
with the MapStore product\, along with guidelines and references to resou
rces for its customization and the development of custom functionality.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:GeoNode UI: Deep Dive on MapStore and Django integration for GeoNod
e - Giovanni Allegri\, Stefano Bovio
URL:http://talks.osgeo.org/foss4g-2023/talk/HVEF8X/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-JGFMRP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T103000
DTEND;TZID=Europe/Tirane:20230630T110000
DESCRIPTION:The extractive sector in Malawi has been marked as one of the d
evelopment enablers to achieve the 2063 Agenda established by African nati
ons. As the mining sector continues to develop\, open-source software such
as QGIS has been a vital and cost-effective tool in monitoring mining act
ivities for the purpose of tracking the effects of mining on the environme
nt and human populations and encouraging accountability from stakeholders
in relation to the Malawi government regulations. Open-source software and
data have also been vital in resolving compensation issues in communities
that exist in mining areas and allow for geoscientists to give needed to
advice to affected stakeholders.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:The role of FOSS in mining sector in Malawi - Ruth Mumba
URL:http://talks.osgeo.org/foss4g-2023/talk/JGFMRP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-Y9R9VH@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T103000
DTEND;TZID=Europe/Tirane:20230630T110000
DESCRIPTION:This talk describes the creation of a water quantification data
set for the entire world. Tracking changes of water-bodies over time helps
in timely action to combat drought and floods. The tools used to build th
is dataset are all free and open source (postgis\, gdal\, geopandas\, scip
y) and are built on top of data from OpenStreetMap.\nThe dataset is update
d everyday with new measurements of lake water extent across the globe. Th
e solution to detect and track water bodies involved fetching satellite da
ta using STAC API\, pre-processing it to remove cloud cover and invalid pi
xels\, identifying water bodies using band ratio\, converting to vector an
d applying post-processing filters to avoid false-positive detection to fi
nally serve it through an API. This solution has allowed us to track and q
uantify changes in a lake's water extent over time with high accuracy.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Monitoring Inland water bodies - Aman Bagrecha
URL:http://talks.osgeo.org/foss4g-2023/talk/Y9R9VH/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MNJEPP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T110000
DTEND;TZID=Europe/Tirane:20230630T113000
DESCRIPTION:Through a (re)mapping and spatial modeling of a city’s past\,
we can build data-rich exploratory platforms to examine urban histories a
nd engage both scholars and the public. Geospatial technologies can be app
lied to extract data from archives and other data sources to build histori
cal data models\, geodatabases\, and geocoders that subsequently enable th
e development of web-based dynamic map interfaces connected to rich digita
l content. This paper outlines a project within a larger consortium of ins
titutions and researchers that focuses on methods in open data and open-so
urce development of the historical mapping of cities. \n\nOpenWorld Atlant
a (OWA) is an example of the possibilities of such a web map platform. OWA
seeks to provide public access to historical information about Atlanta\,
Georgia (United States) during the late 19th century and early 20th centur
y through engaging 3D and dynamic interfaces. Drawing upon historical maps
\, city directories\, archival collections\, newspapers\, and census data\
, projects like OWA allow researchers to analyze spatially grounded questi
ons. \n\nRecent effort on this project focuses on the 1920s\, a dynamic pe
riod in the city’s history that saw the rapid expansion of the urban foo
tprint driven by an increase in population and public infrastructure. Betw
een 1870 and 1940\, the city was shaped by its primary modes of transporta
tion\, heavy rail\, and the electric streetcar. By the 1940s\, the commute
r automobile began transforming Atlanta into the sprawling landscape it is
today. These developments happened under racist “Jim Crow” laws\, and
as such\, the project thus allows new avenues into investigating the long
and contentious histories of racial discrimination and the Civil Rights M
ovement. \n\nThis paper addresses the development of OWA which was built o
n open-source methods and philosophy. The design of its interface and feat
ures\, including the call of spatial data and digital objects from server
resources\, the function of metadata\, the evaluation of the project in us
ability studies\, and the building of consortia around these methods are e
xplored. Further\, the interdisciplinary approach of its research and deve
lopment team and the engagement of students in the process from coding\, b
uilding\, and evaluation. With OWA being built using Leaflet and other for
ms of coding it is designed to pull spatial data and map overlays organize
d and stored on Emory’s instance of Geoserver developed by the Open Geos
patial Consortium (OGC). \n\nFurthermore\, another vital component is the
structure of the information\, data\, and digital objects that are stored
on an instance of Omeka which is a free\, open-source content management
system (CMS) designed for the management and dissemination of digital coll
ections and exhibitions. It is primarily used by archives\, museums\, libr
aries\, and other cultural heritage institutions to create and manage thei
r online collections and exhibitions. Omeka allows student researchers and
assistants to prepare and upload non-spatial content that will be populat
ed as features into the platform. With Omeka\, users can create and manage
items such as images\, documents\, and audio and video files\, as well as
add metadata to describe these items and make them searchable. \n\nMetada
ta plays an especially significant role in the function of the OWA platfor
m. Geospatial features are then linked to records and the corresponding pi
eces of information\, data\, and digital objects\, including images and 3D
models. A modified Dublin Core schema was utilized in Omeka with categori
es designed to better fit the geospatial and historical data collected. As
an example\, the fields for the buildings of a data layer include archite
cts\, date built/demolished\, racial classification of residents or busine
sses\, head of households (from census data and city directories)\, etc. T
o populate these fields\, research teams comprised of graduate and undergr
aduate students. Engaging with faculty and staff\, the students collect hi
storical information from newspapers\, archives\, and online resources and
enter the information into the database. \n\nThe spatial data in OWA com
prises many vector layers including administrative boundaries\, roads\, ra
il lines\, buildings\, and more. The design includes multiple avenues for
exploration based on specific years and special themes. A key feature is t
he buildings layer\, which was populated with historical information inclu
ding people\, race\, entity name\, addresses\, and more from the building
of historical geocoders. The 1928 historical geocoder is complete and was
used to populate the 1928 map layer\, 1878 is currently in production and
with the years surrounding the 1928 geocoder we are using machine learning
to produce geocoders for 1927\, 1929\, and 1930. \n\nAnother important as
pect is the recognition of the necessity of usability and user experience
studies. Researchers at Yonsei and Emory Universities have collaborated to
evaluate the ease of use and overall user experience of the platform. The
usability study's goal is to find areas of improvement in the user interf
ace and user flow and to gather feedback on the product's design and funct
ionality. A primary goal is to serve as an example of and future framework
for usability studies centered on diverse use groups (insider vs. outside
r\, academic/public\, etc.). Test participants were grouped by level of fa
miliarity with Atlanta to capture the diversity of users of the platform.
This investigation focused on analyzing and evaluating user experience to
explore data and content\, conduct analyses\, and contribute via feedback
or to the resource directly. Therefore\, our key questions in these groups
sought to address how we can better design interactive web maps of city h
istories to accommodate diverse user groups. \n\nThe authors of this paper
include collaborators from Emory University\, Yonsei University\, Stanfor
d University\, and The University of Arkansas. Further\, other collaborato
rs include The University of São Paulo (USP)\, a public research universi
ty located in São Paulo\, Brazil and Kaziranga University\, a private uni
versity located in the state of Assam\, India both of which are engaged in
similar or related projects. The collaborators of these projects seek to
share ideas and methods surrounding the historical mapping of cities.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Methods and Evaluation in the Historical Mapping of Cities - Michae
l Page
URL:http://talks.osgeo.org/foss4g-2023/talk/MNJEPP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-LSFNSA@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T110000
DTEND;TZID=Europe/Tirane:20230630T113000
DESCRIPTION:Never before have we had such a rich collection of satellite im
agery available to both companies and the general public. Between missions
such as Landsat 8 and Sentinels and the explosion of cubesats\, as well a
s the free availability of worldwide data from the European Copernicus pro
gram and from Drones\, a veritable flood of data is made available for eve
ryday usage.\nManaging\, locating and displaying such a large volume of sa
tellite images can be challenging. Join this presentation to learn how Geo
Server can help with with that job\, with real world examples\, including:
\n\n* Indexing and locating images using The OpenSearch for EO and STAC pr
otocols\n* Managing large volumes of satellite images\, in an efficient an
d cost effective way\, using Cloud Optimized GeoTIFFs.\n* Visualize mosaic
s of images\, creating composite with the right set of views (filtering)\,
in the desired stacking order (color on top\, most recent on top\, less c
loudy on top\, your choice)\n* Perform both small and large extractions of
imagery using the WCS and WPS protocols\n* Generate and view time based a
nimations of the above mosaics\, in a period of interest\n* Perform band a
lgebra operations using Jiffle\n\nAttend this talk to get a good update on
the latest GeoServer capabilities in the Earth Observation field.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Serving earth observation data with GeoServer: COG\, STAC\, OpenSea
rch and more... - Andrea Aime
URL:http://talks.osgeo.org/foss4g-2023/talk/LSFNSA/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-EQTR3R@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T110000
DTEND;TZID=Europe/Tirane:20230630T113000
DESCRIPTION:Open data and geospatial technology have the potential to revol
utionize decision-making processes across a variety of sectors\, including
urban planning\, disaster response\, environmental management\, and more.
However\, the use of open data in the geospatial domain poses its own set
of challenges\, including data quality\, reliability\, and standardizatio
n concerns. Managing\, maintaining\, and updating large datasets can also
be resource-intensive\, posing a challenge for organizations and communiti
es that rely on open data.\n\nThis talk will explore the opportunities and
challenges of using open data in the context of geospatial technology. I
will begin by discussing the potential benefits of open data\, including i
ncreased transparency\, improved collaboration\, and the ability to make m
ore informed decisions. I will then delve into the key challenges of using
open data in geospatial contexts\, including issues related to data quali
ty and reliability\, standardization\, and the sheer volume of data. We wi
ll explore strategies for managing and maintaining large datasets\, such a
s crowdsourcing and automated data processing\, and discuss best practices
for ensuring data quality and reliability.\n\nThis talk is relevant to an
yone interested in the intersection of open data and geospatial technology
\, including data scientists\, GIS professionals\, policymakers\, and comm
unity leaders. Attendees will come away with a deeper understanding of the
opportunities and challenges of using open data in geospatial contexts an
d gain practical insights on how to leverage this data to drive social and
economic impact. By the end of the talk\, attendees will be equipped with
the knowledge and tools they need to make the most of open data in the ge
ospatial domain.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Open Data for Geospatial: Opportunities and Challenges - Dimple Jai
n
URL:http://talks.osgeo.org/foss4g-2023/talk/EQTR3R/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-N3SC9W@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T110000
DTEND;TZID=Europe/Tirane:20230630T113000
DESCRIPTION:ST_LUCAS is an open-source system designed for providing harmon
ized space-time aggregated LUCAS data. LUCAS (Land Use and Coverage Area f
rame Survey) is an activity managed by Eurostat that performs in-situ surv
eys (points in 2x2km grid) over Europe every three years since 2006. For e
ach LUCAS point\, the land cover and land use classes are examined\, five
photos taken\, and various agro-environmental attributes collected. Eurost
at is providing data in plain CSV files. LUCAS nomenclature is changing ea
ch survey year\, some attributes were removed\, added or renamed.\n\nST_LU
CAS was created with the goal to provide harmonized (each LUCAS survey is
translated into common nomenclature) and space-time aggregated (for each L
UCAS point\, a single location and set of harmonized attributes for each s
urvey year are provided) data. The ST_LUCAS system offers analysis-ready d
ata through the Python API and QGIS plugin (“ST_LUCAS Download Manager
”)\, which minimizes obstacles to use the data by the wider audience. Us
ers may easily access land cover/use information about 1 350 847 points co
vering 28 EU countries measured from 2006 till 2018 by Eurostat. LUCAS poi
nts are retrieved from the ST_LUCAS system based on specified spatial\, te
mporal\, attribute\, and thematic filters. The Python API and QGIS plugin
also allow retrieving photos (one facing photo and four landscape photos i
n the cardinal compass directions) for each LUCAS point. Additionally\, tw
o analytical functions are available: user-defined LUCAS land cover classe
s aggregation and the possibility to translate LUCAS nomenclature into oth
er nomenclatures.\n\nSee ST_LUCAS website https://geoforall.fsv.cvut.cz/st
_lucas/ for detailed information.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:ST_LUCAS reference data for online automated land cover mapping - M
artin Landa\, Ondřej Pešek
URL:http://talks.osgeo.org/foss4g-2023/talk/N3SC9W/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-EXKEL9@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T110000
DTEND;TZID=Europe/Tirane:20230630T113000
DESCRIPTION:Born in 2016 thanks to the funding of the National Operational
Program for Metropolitan Cities (PON METRO 2014-2020) the current Spatial
Data Infrastructure (SDI) of the city of Genova is a hybrid infrastructure
\, where open source components and technologies are merged together with
proprietary ones (such as the Oracle Database) in a well designed platform
with respect of all national guidelines (promoted by AgID - Agenzia per l
’Italia Digitale) and international standards. \nTo support the Geoporta
l initiative\, the city of Genova has collaborated with GeoSolutions as a
company closely involved in the most important Open Source projects worldw
ide in the geospatial field with the aim to provide the necessary support
for all the SDI stack in terms of deployment\, development but also the s
taff training to make it autonomous as much as possible in the maintenance
of the overall system.\nThe city of Genova Geoportal as well as the wider
Geospatial Infrastructure are both reachable online.\nA simple and at the
same time robust WebGIS based on the Open Source MapStore software is pro
vided with the inclusion of both advanced GSI functionalities and also mos
t common geospatial tools like:\n\n- Geospatial data search via OCG Web Se
rvices and Nominatim\n- 2D and 3D visualization of geospatial data using a
map agnostic engine supporting OpenLayers\, Leaflet and Cesium for the 3D
\n- Editing and Styling of geospatial layers\n- Download functions of geos
patial data working on top of OGC services \n- And many more\n\nThe aim is
to provide ready-to-use tools for all users (both citizens and employed a
nalysts worked in the PA) by leveraging the maturity of the Open Source So
ftware as well as the simplicity of integration with the pre-existing COTS
software in order to maximize the reuse of the existing infrastructure an
d minimize the need for customizations and a possible use of commercial su
pport even for educational purposes.\nMany cross-cutting projects usually
gravitate around the SDI in the Public Administration and its own Geoporta
l. To date\, more than 300 geospatial layers are available in the Geoporta
l which allows them to be viewed and consulted within preconfigured MapSto
re maps\, dashboards and geostories and/or used through geospatial service
s (such as WMS\, WMTS\, WFS\, WCS and CSW) developed according to internat
ional standards (OGC - Open Geospatial Consortium) and exposed through Geo
Server and GeoNetwork with also a fine grained security tier represented b
y GeoFence to manage authorizations on geospatial data.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:MapStore real world case study: the hybrid infrastructure of the Ci
ty of Genova - Stefano Bovio
URL:http://talks.osgeo.org/foss4g-2023/talk/EXKEL9/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-A3AJPJ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T110000
DTEND;TZID=Europe/Tirane:20230630T113000
DESCRIPTION:Diagonal is a steward-owned data science consultancy working wi
th projects in the built environment. We build interactive tools to help p
eople understand the tradeoffs inherent in their plans to evolve cities. O
ur tools are powered by B6 - an in-memory geospatial analysis engine we bu
ilt to work with large data sets describing the built environment. We typi
cally use it work work with OpenStreetMap and open government data. To ena
ble others to repeat our analyses\, we recently released B6 as open source
. In this talk\, we'll give an overview of B6\, including how it's impleme
nted\, and how we use it in our commercial work.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:B6\, Diagonal's open source geospatial analysis engine - Andrew Ela
nd
URL:http://talks.osgeo.org/foss4g-2023/talk/A3AJPJ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-79EEYF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T110000
DTEND;TZID=Europe/Tirane:20230630T113000
DESCRIPTION:At the Norwegian Water and Energy Directorate (NVE)\, the OSGeo
Community project actinia was introduced together with the Open Source Ap
ache Airflow software as a platform for delivering operational Copernicus
services at national scale.\nIn the presentation\, we will illustrate how
Airflow and actinia work together and present current and future applicati
ons operationalized on the platform.\n\nThose applications cover currently
: \n- Avalanches\n- Flooding\n- snow cover\n- lake ice\n\nMore services re
lated to NVE`s area of responsibility are being investigated\, like landsl
ides\, slush flows\, glacier lake outburst floods\, or specific land cover
changes...
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Implementing Copernicus services at the Norwegian Water and Energy
Directorate with Airflow and actinia - stbl
URL:http://talks.osgeo.org/foss4g-2023/talk/79EEYF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-N8DXEN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T110000
DTEND;TZID=Europe/Tirane:20230630T113000
DESCRIPTION:pycsw is an OGC CSW server implementation written in Python and
is an official OSGeo Project. pycsw implements clause 10 HTTP protocol bi
nding - Catalogue Services for the Web\, CSW of the OpenGIS Catalogue Serv
ice Implementation Specification\, version 3.0.0 and 2.0.2. pycsw allows f
or the publishing and discovery of geospatial metadata\, providing a stand
ards-based metadata and catalogue component of spatial data infrastructure
s. The project is certified OGC Compliant\, and is an OGC Reference Implem
entation.\n\nThe project currently powers numerous high profile catalogues
such as IOOS\, NGDS\, NOAA\, US Department of State\, US Department of In
terior\, geodata.gov.gr\, Met Norway and WMO WOUDC. This session starts wi
th a status report of the project\, followed by an open question answer se
ssion to give a chance to users to interact with members of the pycsw proj
ect team. This session will cover how the project PSC operates\, the curre
nt project roadmap\, and recent enhancements focused on ESA's EOEPCA\, Ope
n Science Data Catalogue and OGC API - Records.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:pycsw project status 2023 - Tom Kralidis\, Angelos Tzotsos
URL:http://talks.osgeo.org/foss4g-2023/talk/N8DXEN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-USXAVW@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T110000
DTEND;TZID=Europe/Tirane:20230630T113000
DESCRIPTION:As well trained and experienced members of the free software co
mmunity from Turkey\, we were caught off guard\, when the earthquakes happ
ened on February 6\, 2023. We started mapping campaigns with HOT\, we aggr
egate different data sources on a GeoServer installation\, we did several
visualizations on QGIS\, but we always felt like something was missing.\n\
nIf we had a guideline of disaster response for free software communities\
, we would feel better at the beginning.\n\nThis session's aim is\, to pre
pare a dynamic guideline of disaster response actions for geospatial commu
nities\, focused on free software and open data.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Creating The Red Book of Disaster Response for FOSS4G Community - O
rkut Murat YILMAZ
URL:http://talks.osgeo.org/foss4g-2023/talk/USXAVW/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PWNXDY@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113000
DTEND;TZID=Europe/Tirane:20230630T120000
DESCRIPTION:Small scale food production has in the past not been a priority
for AI supported analysis of satellite imagery\, mostly due to the limite
d availability of satellite imagery with sufficient spatial and spectral r
esolution. Additinally\, small scale food producers might find it challeng
ing to articulate their needs and might not recognize any added benefit in
new analysis approaches.\n\nOur case study\, situated in the geographical
ly and politically complex Alas Mertajati in the highlands of Bali\, demon
strates the opportunities of applying satellite assets and machine learnin
g supported classification to the detection of one particular small-scale
farming practice\, agroforestry. To this end\, we are collaborating with t
he non-governmental organization WISNU as well as BRASTI\, a local organiz
ation representing the interests of the indigenous Tamblingan.\n\nThe prac
tice of agroforestry is widespread across Southeast Asia [5]. Agroforestry
plots are 3-dimensional food sources with a variety of species of trees\,
shrubs\, and plants combined into a compact spatial unit. Agroforestry pl
ots are typically small\, ranging from fractions of a hectare to a few hec
tares\, and they are often owned by local residents and farmers. Agrofores
try plots are tended to manually due to the low cost of manual labor\, the
small sizes of the plots\, the lack of appropriate farm automation system
s\, as well as a desire to maintain traditional\, time-tested land use pra
ctices. Small-scale agroforestry can produce a continuous and stable sourc
e of valuable and essential foods. The assemblage of vegetation with varyi
ng root depth also assists in reducing landslides\, an increasingly common
event during extreme rainfall in the highlands of the Alas Mertajati. As
such\, agroforestry is a robust hedge against some forms of climate change
than monoculture farm plots [4]. \n\nIn Bali\, agroforestry sites typical
ly contain several major cash crops including clove\, coffee\, and banana
together with a variety of additional trees such as palms\, as well as pla
nts and shrubs such as mango\, papaya\, and taro. Because of the small plo
t sizes and the diversity of plants contained in agroforestry sites\, dete
ction of agroforestry in satellite imagery with statistical approaches is
difficult [2].\n\nWhile other researchers see in the explosion of remote s
ensing systems an opportunity for the exploration of new algorithms [1]\,
our contribution focuses on the under-valued process of ground truth data\
, both to improve landcover classification as well as to engage with a loc
al community that will profit from the process.\n\nThe latest generation o
f Planet Labs satellite imagery (Superdove) offers additional spectral inf
ormation (Coastal Blue (431-452 nm)\, Blue (465-515 nm)\, Green I (513-549
nm)\, Green (547-583 nm)\, Yellow (600-620 nm)\, Red (650-680 nm)\, Red E
dge (697-713 nm)\, Near-infrared (845-885 nm)) at the same spatial resolut
ion (3.7/m) as the earlier Dove constellation [3]. These new spectral sour
ces offer a new window onto the presence of plants associated with agrofor
estry practices in the Alas Mertajati (Figure 1). After collecting a first
set of reference data\, we selected several popular machine learning algo
rithms (Random Forest\, SVM\, Neural Networks) to produce classifiers that
are able to capture the distribution of agroforestry in the study area to
varying degrees. These maps are the first representations of agroforestry
in Bali Indonesia (Figures 2\, 3).\n\nWe shared these first-generation ma
ps with members of the Tamblingan (through our project partners) who have
long-standing claims to the Alas Mertajati as ancestral lands. Their obser
vations found some of the areas identified as agroforestry to be false\, c
apturing errors and slippages our research team was not aware of.\n\nToget
her with a local guide\, we collected additional ground truth examples in
the field. We re-trained the classification systems on the augmented data
set to produce updated agroforestry representations. The improvements are
twofold. First\, as a GIS product. The new map (Figure 4) show a different
distribution of agroforestry sites than the previous results. \nAgrofores
try seems more widely established within the dominant clove gardens. The p
revious result had a kappa index of 0.714815\, and the new result generate
s a kappa index of 0.734687\, and we expect this result to further improve
as we fine-tune our classification process.\n\nSecond\, as a science comm
unication project. In our discussion with our partners\, it became clear t
hat the first maps were visually difficult to understand. The “natural
” coloration of water\, forest\, and settlements made it difficult for s
ome non-GIS schooled members to read the information. Consequently\, we cr
eated a new visualization approach that limited the content to a single ca
tegory. We projected this information onto an infrared image – from the
same satellite asset that delivered the data – to an ‘unnatural’ ima
ge with lower barriers to readability (Figures 5\, 6). \n\nWe used the sam
e approach to visualize the hydrology of the Alas Mertajati (Figure 7). Th
e hydrology data sourced from the Indonesian Government's Badan Informasi
Geospatial is superimposed on the same infrared image for visual clarity.
However\, the data is over 20 years old (Figure 8). There is no updated hy
drology map. As such\, the image depicts a water rich region that has more
recently been identified as water poor due to a rapid rise in water use b
y the changes in weather patterns and an expanding tourism industry. In fa
ct\, a first round of data collected in the field during the rain season o
f 2023 found multiple dry river beds (Figure 9). As a consequence\, the Ta
mblingan though BRASTI are establishing this water poor ground truth by ve
rifying water flow (or lack thereof) in river beds (Figure 10).\n\nFinally
\, the project demonstrates the usefulness of our software repository COCK
TAIL. Built upon GDAL\, ORFEO and QGIS modules\, COCKTAIL allows us to inv
oke popular GIS land cover classification algorithms to classify Planet La
b and Sentinel2 imagery. Moreover\, COCKTAIL collects all settings used to
create a classification and saves them\, so the products can be easily re
produced. COCKTAIL works with remote storage providers to stash large file
s on low-cost servers. This is of particular interest when working in reso
urce constrained environments.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Agroforestry in the Alas Mertajati of Bali\, Indonesia. A case stud
y in applying AI and GIS to sustainable small-scale farming practices. - m
arc böhlen\, Rajif Iryadi\, Jianqiao Liu
URL:http://talks.osgeo.org/foss4g-2023/talk/PWNXDY/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UMHYBF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113000
DTEND;TZID=Europe/Tirane:20230630T120000
DESCRIPTION:The name fAIr is derived from the following terms:\n\nf: for fr
eedom and free and open-source software\nAI: for Artificial Intelligence\n
r: for resilience and our responsibility for our communities and the role
we play within humanitarian mapping\n\nfAIr is an open AI-assisted mapping
service developed by the Humanitarian OpenStreetMap Team (HOT)\, designed
to enhance the efficiency and accuracy of mapping efforts for humanitaria
n purposes. By utilizing computer vision techniques and open-source AI mod
els\, fAIr detects crucial map features from satellite and UAV imagery\, s
tarting with buildings. The service fosters collaboration with local commu
nities\, enabling them to create and train their own AI models\, ensuring
relevance and fairness in mapping. Through a constant feedback loop\, fAIr
progressively improves its computer vision models\, contributing to the c
ontinuous advancement of humanitarian mapping.This talks will talk about o
ur journey and vision for using AI
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:fAIr - Free and Open Source AI for Humanitarian Mapping - Kshitij R
aj Sharma
URL:http://talks.osgeo.org/foss4g-2023/talk/UMHYBF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MDZQAG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113000
DTEND;TZID=Europe/Tirane:20230630T120000
DESCRIPTION:At the end of 2022 the Swiss geodata catalogue\, geocat.ch\, wa
s migrated to GeoNetwork version 4. A more modern user interface as well a
s a more powerful search based on Elasticsearch makes it easier to search
the more than 14000 geometadata contained in geocat.ch.\n\nThis new versio
n of geocat.ch has been the subject of a usability study focusing on geoda
ta search. Some developments based on the results of this study have been
proposed to the GeoNetwork developer community. To discuss these proposals
with the other users of GeoNetwork\, a GeoNetwork user community should b
e founded and could be helpful in the further developments of GeoNetwork.
In addition\, the usability study showed that the search for geodata is ve
ry dependent on the quality of the information entered into the catalog.\n
\nThe geometadata in geocat.ch come from different organizations (direct e
ntry or harvesting)\, have different spatial extents\, are multilingual an
d some have different data models. The harmonized entries of the most impo
rtant information are essential and form the basis for efficient searches.
The Swiss geometadata standard (GM03)\, which is currently under review w
ith the aim of simplifying and updating the Swiss geometadata model\, alwa
ys based on international standards.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:The Swiss geometadata catalogue: new version (GeoNetwork V4) & firs
t results of a usability study - Raphaëlle Arnaud
URL:http://talks.osgeo.org/foss4g-2023/talk/MDZQAG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-VNNMBZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113000
DTEND;TZID=Europe/Tirane:20230630T120000
DESCRIPTION:(or what happens when GeoServer and PostGIS meet Active Directo
ry)\n\nThis talk will present a case study of how Astun implemented a sing
le sign on (SSO) system for a large \ncommercial client. The client stored
their spatial data in a PostGIS database and provided both direct access
\nto the database via QGis and from QGis via WMS using GeoServer to carry
out the styling and rendering of the \ndata. Staff are divided into 4 team
s and then are subdivided by end client in to small groups. Some of the \n
data in the system is restricted to just the group working on a specific p
roblem for a specific client\, other \ndata is shared with the whole team\
, and some is available to the whole company.\n\nThe client brief was to m
ove their on site system to "the cloud"\, and to allow staff to connect to
the data \nfrom anywhere in the world with only one user account and pass
word for access to PostGIS and GeoServer data. \nInitially\, the project p
lanned to leverage the existing corporate Azure Active Directory system to
provide the \nnecessary authentication and authorizations. However\, earl
y experiments showed that the time between \nrequesting a new group and it
appearing on the server was (sometimes) longer than the lifetime of the n
ew \ngroup. \n\nAstun provided an open source solution\, using Keycloak to
handle the user and administrator facing frontends\, \nwith user data bei
ng stored in an OpenLDAP server. It was then possible to make use of the L
DAP service to \nperform authentication and authorization of users to both
PostGIS and GeoServer\, making sure that data \nrestrictions applying in
one were duplicated in the other. \n\nThe talk will cover details of the p
rocess and look at some of the issues that were encountered during the \np
roject.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Securing Your Open Source Geospatial Stack with Single Sign On - Ia
n Turton
URL:http://talks.osgeo.org/foss4g-2023/talk/VNNMBZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XYLZPW@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113000
DTEND;TZID=Europe/Tirane:20230630T120000
DESCRIPTION:n the West African Sahel\, farmers and herders are critically v
ulnerable to climate shocks and need access to climate information to secu
re their livelihoods. Herders use data on pasture and water availability t
o move their livestock and farmers need weather predictions for planting.
While satellite imagery has made much of this information readily accessib
le to the spatial community\, few channels exist to transmit this informat
ion to farmers and herders. As a result\, climate data has become more pow
erful than ever before\, yet mostly inaccessible to those who depend on th
is information for their livelihoods.\n\nThis talk will share the lessons
of the GARBAL programme\, an initiative that seeks to bridge this gap. GAR
BAL is a call center that uses Copernicus Earth Observation imagery and fi
eld data to provide farmers & herders with information on pasture\, water
and markets in Mali\, Niger and Burkina Faso. GARBAL was first developed i
n 2015 and this talk will provide lessons from several years of practice.\
n\nThe GARBAL interface uses an open-source stack including PostGIS and Ma
pserver to create a user-friendly interface for call center agents\, who t
hen use that interface to answer questions from callers on pasture conditi
ons\, market prices and weather forecasts (among others). \n\nThe talk wi
ll share lessons from the technical and programmatic aspects of the projec
t. The technical side will go over the architecture of the data treatment\
, demo the interface\, talk about successes and failures and show how you
can play with the data yourself. The programmatic side focuses more on how
the user needs evolved over the years\, techniques for translating GIS da
ta into information useful to farmers and herders\, operating in areas of
active conflict and how EO data fits into existing centuries-old tradition
al data collection systems in the Sahel.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Open EO and FOSS4G serving Sahelian farmers and herders: lessons fr
om the GARBAL programme - Alex Orenstein
URL:http://talks.osgeo.org/foss4g-2023/talk/XYLZPW/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-7WYYYR@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113000
DTEND;TZID=Europe/Tirane:20230630T120000
DESCRIPTION:pygeoapi is an OGC API Reference Implementation. Implemented in
Python\, pygeoapi supports numerous OGC APIs via a core agnostic API\, di
fferent web frameworks (Flask\, Starlette\, Django) and a fully integrated
OpenAPI capability. Lightweight\, easy to deploy and cloud-ready\, pygeoa
pi's architecture facilitates publishing datasets and processes from multi
ple sources. The project also provides an extensible plugin framework\, en
abling developers to implement custom data adapters\, filters and processe
s to meet their specific requirements and workflows. pygeoapi also support
s the STAC specification in support of static data publishing.\n\npygeoapi
has a significant install base around the world\, with numerous projects
in academia\, government and industry deployments. The project is also an
OGC API Reference Implementation\, lowering the barrier to publishing geos
patial data for all users.\n\nThis presentation will provide an update on
the current status\, latest developments in the project\, including new co
re features and plugins. In addition\, the presentation will highlight key
projects using pygeoapi for geospatial data discovery\, access and visual
ization.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:pygeoapi project status 2023 - Tom Kralidis\, Francesco Bartoli\, A
ngelos Tzotsos\, Just van den Broecke
URL:http://talks.osgeo.org/foss4g-2023/talk/7WYYYR/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-EMXZAK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113000
DTEND;TZID=Europe/Tirane:20230630T120000
DESCRIPTION:The Open Metadata platform allows the integration of data and m
etadata for the management of governance within an organization to integra
te different sources\, control its publication\, its access\, standardize
the processing and even to be able to analyze the lineage. What we are goi
ng to share is the adaptation of one of the data sources to the OGC - CSW
service to be able to consume the cataloged metadata transparently in the
system.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Data Governance with Open Metadata Integrating OGC - CSW Services -
Ariel Anthieni\, Walter Shilman
URL:http://talks.osgeo.org/foss4g-2023/talk/EMXZAK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QDVGCU@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113000
DTEND;TZID=Europe/Tirane:20230630T113500
DESCRIPTION:Various disciplines such as traffic simulations\, driving simul
ations and applications in autonomous driving require highly detailed road
network datasets. OpenDRIVE evolved as an open industry standard for mode
lling of lane-level road networks (HD maps). Acquiring such datasets is ve
ry expensive tough because it has to be done through mobile mapping in mos
t cases. We want to introduce to the FOSS4G community two recently and ope
nly published road network datasets from Brunswick (https://doi.org/10.528
1/zenodo.7071846) and Wolfsburg (https://doi.org/10.5281/zenodo.7072631).
Investment in both datasets has been funded by German authorities and cove
red more than 100.000 Euro. We will also give a short appetiser on how to
use this data with free and open GIS tools.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:New lane-detailed OpenDRIVE datasets (HD maps) from Germany openly
available - Michael Scholz
URL:http://talks.osgeo.org/foss4g-2023/talk/QDVGCU/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KH3VZV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113000
DTEND;TZID=Europe/Tirane:20230630T120000
DESCRIPTION:We are currently living in an era for Earth Observations that m
aybe 20 years ago we could not image. Petabytes and Petabytes of data are
being created\, having so much data it is a good problem to have but the n
ext question is how we can make sure that the Data created it is really be
ing used to solve the challenges we are facing on Earth. The Copernicus Pr
ogram has given us the opportunity of having Open Data from a variety of d
iverse sensors but at the same time more and more companies are part of th
e New Space era in the one commercial companies are launching Optical and
SAR satellites that are complementing the Open Data sources.\n\n\n\nIn my
daily job doing Partnerships in the industry\, I have the chance to work t
ogether with most of the New Space companies trying to find the best way t
o promote how we all can take advantage of all the data we have available
from the Open Data sources and the Commercial sources\, this can be optica
l data working together with SAR and how it can be a game changer in many
future projects in Earth Observation.\n\nMy presentation will go around ho
w in the last few years there are more options to be able to build product
s helping to solve earth's challenges by taking advantage of the resources
we have in the New Space Industry.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Unlocking the potential or Earth Observation combining Optical and
SAR data - Miriam Gonzalez
URL:http://talks.osgeo.org/foss4g-2023/talk/KH3VZV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-9KCVBK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T113500
DTEND;TZID=Europe/Tirane:20230630T114000
DESCRIPTION:Various applications with the need of highly detailed road netw
ork models emerged within the last decade. Apart from traffic simulations
in context of urban planning\, especially the automotive industry plays an
important role in geodata consumption for development\, testing and valid
ation of autonomous driving functions. In this domain\, human-centred driv
ing simulation applications with their realistic 3D virtual environments p
ose the highest demands on real-world data and lane-level road network mod
els. It is not uncommon for such road network data to not only be mathemat
ically continuously modelled\, but also to contain all the necessary topol
ogical links and semantic information from traffic-regulating infrastructu
re – such as signs and traffic lights. Schwab and Kolbe [1] give a compa
ct overview of the requirements of such fields of application and describe
different domain-specific road data formats\, which are commonly used for
such tasks. Of these peculiar road description formats\, OpenDRIVE [2] ev
olved as an open industry standard. In 2017 we proposed a driver for conve
rsion of OpenDRIVE’s continuous road geometry elements into standardized
GIS geometries according to OGC Simple Features Access [3] via the free a
nd open-source Geospatial Data Abstraction Library (GDAL) [4]. By then\, t
his was the first open source conversion tool from OpenDRIVE into more GIS
-friendly encodings. Since then\, other OpenDRIVE conversion tools have po
pped up\, such as [5]\, [6]\, [7]\, [8]. But none of those allows such a c
omfortable integration into common GIS tools like our proposed GDAL extens
ion by\, for example\, simply dragging and dropping an OpenDRIVE dataset i
nto QGIS. We now present a refurbished version of our OpenDRIVE GDAL drive
r which is based on the novel C++ library libOpenDRIVE. It integrates well
in GDAL’s new CMake building process and offers a more convenient start
ing point for developers and researchers who want to bring OpenDRIVE data
easily into context with other geodata such as with aerial images\, OpenSt
reetMap or cadastral data. Apart from OpenDRIVE\, other specialized road n
etwork description formats are crucial to the automotive engineering and r
esearch domain. Where Road2Simulation [9] and laneLet2 [10] already come a
long in GIS-friendly encodings\, RoadXML and NDS Open Lane Model [11] coul
d also profit from such a GDAL-based conversion approach. By bringing the
domains of automotive engineering and GIS closer together we hope to stimu
late interdisciplinary knowledge transfer and the creation of an interconn
ected research community.\n\n[1] https://doi.org/10.5194/isprs-annals-iv-4
-w8-99-2019\n[2] https://www.asam.net/standards/detail/opendrive\n[3] http
s://www.ogc.org/standards/sfa\n[4] https://elib.dlr.de/110123\n[5] https:/
/doi.org/10.5281/ZENODO.7023152\n[6] https://doi.org/10.5281/zenodo.777170
8\n[7] https://doi.org/10.1109/itsc48978.2021.9564885\n[8] https://doi.org
/10.5281/zenodo.7702312\n[9] https://doi.org/10.5281/ZENODO.3375525\n[10]
https://doi.org/10.1109/itsc.2018.8569929\n[11] https://olm.nds-associatio
n.org
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Providing a libOpenDRIVE-based GDAL driver for conversion of lane-d
etailed road network datasets commonly used in automotive engineering into
GIS tools - Michael Scholz
URL:http://talks.osgeo.org/foss4g-2023/talk/9KCVBK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-98E3RR@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T114000
DTEND;TZID=Europe/Tirane:20230630T114500
DESCRIPTION:Virtual Constellations-as-a-Service and Virtual Image Catalogs\
n\nSharing remote sensing assets among multiple tenants is crucial to unlo
ck the value of new space earth imaging constellations. In these schemes\,
a tenant has access to a so-called virtual constellation consisting of de
dicated access to a number of assets as well as automated mechanisms to pr
ocure additional imagery from other assets. Access to this virtual constel
lation is mediated through a virtual catalog client-side that looks to the
user as if it comes from its own dedicated assets and is fully interopera
ble with open-source standards for cloud optimized pipelines\, such as STA
C and COG.\n\nSatellogic Inc.\, a leader in sub-meter resolution Earth Obs
ervation data collection recently reached a three-year agreement with the
Government of Albania to develop a Dedicated Satellite Constellation. This
unique program derives from Satellogic's Constellation-as-a-Service model
and will provide Albania with responsive satellite imagery capabilities a
cross its sovereign territory. Two satellites\, ALBANIA1 and ALBANIA2 were
launched in January 2023\, to provide imagery for national map generation
to support emergency response\, land use management as well as environmen
tal monitoring of sustainability goals.\n\nTo support this government effo
rt we have developed a secure\, encrypted end-to-end data platform\, conti
nuously updated archival imagery in dedicated client-side cloud along with
support for open source standards such as STAC and COG. We also discuss f
uture directions in terms of the resulting ability to build integrations w
ith external image processing platforms and open source data exploitation
projects.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Virtual Constellations-as-a-Service and Virtual Image Catalogs - De
nis Rykov
URL:http://talks.osgeo.org/foss4g-2023/talk/98E3RR/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PBV3F7@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T120000
DTEND;TZID=Europe/Tirane:20230630T123000
DESCRIPTION:This paper presents different approaches to map bark beetle inf
ested forests in Croatia. Bark beetle infestation presents threat to fores
t ecosystems and due to large unapproachable area presents difficulties in
mapping infested areas. This paper will analyse available machine learnin
g options in open-source software such as QGIS and SAGA GIS. All options w
ill be performed on Copernicus data\, Sentinel 2 satellite imagery. Machin
e learning and classification options that will be explored are maximum li
kelihood classifier\, minimum distance\, artificial neural network\, decis
ion tree\, K Nearest Neighbour\, random forest\, support vector machine\,
spectral angle mapper and Normal Bayes. Maximum likelihood algorithm is co
nsidered the most accurate classification scheme with high precision and a
ccuracy\, and because of that it is widely used for classifying remotely s
ensed data. \nMaximum likelihood classification is method for determining
a known class of distributions as the maximum for a given statistic. An as
sumption of normality is made for the training samples. During classificat
ions all unclassified pixels are assigned to each class based on relative
probability (likelihood) of that pixel occurring within each category’s
probability density function. \nMinimum distance classification is probabl
y the oldest and simplest approach to pattern recognition\, namely templat
e matching. In a template matching we choose class or pattern to be recogn
ized\, such as healthy vegetation. Unknown pattern is then classified into
the pattern class whose template fits best the unknown pattern. Unknown d
istribution is classified into the class whose distribution function is ne
arest (minimum distance) to the unknown distribution in terms of some pred
etermined distance measure.\nA decision tree is a decision support tool th
at uses a decision tree model and its possible consequences\, including th
e outcomes of random events\, resource costs\, and benefits. It's a way of
representing an algorithm that contains only conditional control statemen
ts. Decision trees are commonly used in operations research\, particularly
in decision analysis to identify the strategy most likely to achieve a go
al\, but they are also a popular tool in machine learning.\nK Nearest Neig
hbour is a simple algorithm that stores all the available cases and classi
fies the new data or case based on a similarity measure. It is mostly used
to classifies a data point based on how its neighbours are classified.\nR
andom forests or random decision forests is an ensemble learning method fo
r classification\, regression and other tasks that operates by constructin
g a multitude of decision trees at training time. For classification tasks
\, the output of the random forest is the class selected by most trees. Fo
r regression tasks\, the mean or average prediction of the individual tree
s is returned. \nSupport vector machines (SVM) are supervised learning mod
els with associated learning algorithms that analyse data for classificati
on and regression analysis. SVMs are one of the most robust prediction met
hods\, being based on statistical learning frameworks. Given a set of trai
ning examples\, each marked as belonging to one of two categories\, a SVM
training algorithm builds a model that assigns new examples to one categor
y or the other\, making it a non-probabilistic binary linear classifier.\n
Spectral image mapper is a spectral classifier that can determine spectral
similarity between image spectra and reference spectra by calculating the
angle between the spectra\, treating them as vectors in a space with dime
nsionality equal to the number of bands used each time. Small angles betwe
en the two spectrums indicate high similarity\, and high angles indicate l
ow similarity.\nBayesian networks (normal Bayes) are a type of probabilist
ic graphical model that uses Bayesian inference to calculate probability.
Bayesian networks aim to model condition dependence by representing condit
ional dependence by edges in directed graph. Bayesian networks are designe
d for taking an event that occurred and predicting the likelihood that any
one of possible known causes was a factor.\nCopernicus\, also known as Gl
obal Monitoring for Environment and Security (GMES) is a European program
for the establishment of European capacity for Earth observation. European
Space Agency is developing satellite missions called Sentinels where ever
y mission is based on constellation of two satellites. Main objective of S
entinel-2 mission is land monitoring and it is performed using multispectr
al instrument. Sentinel-2 mission is active since 2015. Sentinel-2 mission
carries multispectral imager (MSI) covering 13 spectral bands. Sentinel 2
mission produces two main products\, level-1C and level-2A. Level-1C prod
ucts are tiles with radiometric and geometric correction applied. Geometri
c correction includes orthorectification. Level-1C products are projected
combining UTM projection and WGS84 ellipsoid. Level-2A products are consid
ered as the mission Analysis Ready Data.\nEach method is evaluated with er
ror matrix and each method is compared to each other. A confusion matrix\,
also known as an error matrix\, is a specific table layout that allows vi
sualization of the performance of an algorithm\, typically a supervised le
arning one (in unsupervised learning it is usually called a matching matri
x). Each row of the matrix represents the instances in an actual class whi
le each column represents the instances in a predicted class\, or vice ver
sa – both variants are found in the literature. The name stems from the
fact that it makes it easy to see whether the system is confusing two clas
ses. Each error matrix contains Kappa value. Kappa coefficient is a statis
tic that is used to measure inter-rater reliability for qualitative (categ
orical) items. It is generally thought to be a more robust measure than si
mple percent agreement calculation\, as κ considers the possibility of th
e agreement occurring by chance.\nAll analyses are performed on data locat
ed in Republic of Croatia\, Primorsko-goranska county.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:COMPARING DIFFERENT MACHINE LEARNING OPTIONS TO MAP BARK BEETLE INF
ESTATIONS IN REPUBLIC OF CROATIA - Nikola Kranjčić
URL:http://talks.osgeo.org/foss4g-2023/talk/PBV3F7/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-HCQTLP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T120000
DTEND;TZID=Europe/Tirane:20230630T123000
DESCRIPTION:Learn how Humanitarian Openstreetmap Team uses modern tools lik
e Terraform\, AWS serverless\, and other tools to modernise the collaborat
ive mapping tool - Tasking Manager. The talk will focus on balancing infra
structure costs\, cloud vendor lock-in\, performance and DevOps processes.
\n\nTasking Manager is an important collaborative mapping tool that is con
sidered a public good. In recent times\, the tool has left a lot to be des
ired in terms of performance and availability. The HOT Tech team set out t
o overhaul the architecture\, and deployment processes of Tasking Manager.
I discuss the soon-to-go-live improvements that touch upon Terraform\, AW
S Serverless\, CircleCI\, Observability processes\, and Developer Experien
ce. \n\nLinks: https://github.com/hotosm/tasking-manager
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Modernising Tasking Manager infrastructure using Terraform\, cloud-
native tools and good sense - Yogesh Girikumar
URL:http://talks.osgeo.org/foss4g-2023/talk/HCQTLP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-VWBVSS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T120000
DTEND;TZID=Europe/Tirane:20230630T123000
DESCRIPTION:geOrchestra is a complete spatial data infrastructure (SDI) and
combines a number of widely used open source components. These include Ge
oNetwork as a metadata catalogue\, GeoServer\, GeoWebCache\, GeoFence\, an
d Jasig CAS. During this talk we will present the project and its latest d
evelopments.\n\ngeOrchestra is an open source\, modular\, interoperable an
d secure spatial data infrastructure designed by people for people.\n\nThe
technical architecture is based on modularity and interoperability. The e
xtensive use of the Spring Framework allows the integration of additional
components. Compliance with OGC standards is central\, because only then c
an the various components and any external IDS work together.\n\ngeOrchest
ra is supported by an underlying server infrastructure\, which can be conf
igured in an automated way if necessary. We support deployment on Kubernet
es as well as Ansible. geOrchestra has proven to be an innovative IDS in a
highly orchestrated environment. Its modular architecture allows it to de
ploy individual components as microservices. Individual components such as
GeoServer-cloud or GeoNetwork Microservices can therefore be scaled as ne
eded.\n\nNevertheless\, an SDI must be user-friendly and adopt a user-cent
ric approach. This is the latest development that the geOrchestra communit
y has started to follow. New modules such as the Datafeeder simplifies the
data registry and the Datahub portal makes it very easy for a user to fin
d the right dataset.\n\nCurrent developments related to geOrchestra includ
e a rewrite of the GeoNetwork metadata catalogue to provide a complete new
user interface for editing metadata.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:geOrchestra - project status - Emmanuel Belo\, VAN DER BIEST Franç
ois
URL:http://talks.osgeo.org/foss4g-2023/talk/VWBVSS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ST8VRG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T120000
DTEND;TZID=Europe/Tirane:20230630T123000
DESCRIPTION:We show how Mergin Maps can be used in various real-world situa
tions to use the power of QGIS ecosystem to speed up and effectively captu
re data in the field and reliably collaborate with your team. We will not
dive into technical details\, but focus more on general understanding of w
hat can be done nowadays in the field of professional geo-data capturing.\
n\nDo you need to capture the location of plants or animals with your pers
onal phone? Or distribute this task to a group of volunteers without need
to train them? Or your company has a network of pipes or fiber cables\, yo
u use QGIS in the office for analysis and you want to use the same map as
your colleagues on site? Are you fed up with using for such tasks a camera
and MS Excel or even pen and paper? This talk can show you how others so
lve these challenges with Mergin Maps.\n\nMergin Maps is a free and open-s
ource platform powered by QGIS rendering engine to capture and share geo-
data with ease. It has been developed by Lutra Consulting since 2017 and i
t has served thousands of companies and individuals in full production for
more than 2 years. It comes with Android\, iOS apps that do not need any
training to be used by the general public. Also a powerful server to store
\, version and collaborate on your QGIS projects.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:Mergin Maps: capture geo-data and share your QGIS projects with eas
e - Peter Petrik
URL:http://talks.osgeo.org/foss4g-2023/talk/ST8VRG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TPTH3F@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T120000
DTEND;TZID=Europe/Tirane:20230630T123000
DESCRIPTION:MapLibre GL JS\, Leaflet\, Esri Leaflet\, OpenLayers\, and Cesi
um JS are all great mapping libraries. However\, it can be difficult to de
cide which one to use for different applications. In this talk\, I compare
the strengths and weaknesses of each library based on different criteria.
The criteria include the following: \n\n1. Library footprint and modular
ity. \n2. Load times for vector tile and image tile layers. \n3. Renderin
g performance of GeoJSON data. \n4. Styling and rendering features. \n5.
Viewport performance and screen size responsiveness.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:Open source mapping library shoot out - Anita Kemp
URL:http://talks.osgeo.org/foss4g-2023/talk/TPTH3F/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FTMPSP@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T120000
DTEND;TZID=Europe/Tirane:20230630T123000
DESCRIPTION:Albania is one of the most vulnerable countries in terms of the
trend of climate change in the Western Balkans. Changing weather patterns
have already been observed over the last 15 years with increasing tempera
tures\, decreasing precipitation\, and more frequent extreme events like f
loods and droughts. Among the most affected cities is Tirana\, where a tim
e series analysis was done using FOSS data and tools. Our aim was to provi
de accurate map representations of local climate zones (LCZs) to track the
changes of the last decade based on an open online platform running on Go
ogle Earth Engine. This is called LCZ generator and aims to use free data
sources from the Copernicus Hub (Demuzere et al. 2021). The satellite data
based analysis was done by using 5-15 training areas for each LCZ types.
It provided a 100 by 100 m ground resolution supervised classification for
the entire municipality of Tirana. The analysis shows that the quick urba
nization process resulted in a decreasing proportion of green areas\, and
unpaved surfaces in the municipality of Tirana\, which consequently increa
sed the vulnerability of the city to extreme weather events.\nA large-scal
e map was also compiled using a free and open source Geographic Informatio
n System (QGIS)\, which seems to be the most effective in identifying the
varying urban climate zones on the city planning level\, since it shows th
e city's structures and even highlights the role of a building or small pa
rk (Cenameri\, 2021).
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Correlation between the greening rate of a city and local climate z
ones using free and open source data and tools (case study: city of Tirana
) - Anja Cenameri
URL:http://talks.osgeo.org/foss4g-2023/talk/FTMPSP/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GECX9K@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T120000
DTEND;TZID=Europe/Tirane:20230630T123000
DESCRIPTION:This presentation is the follow up of the datahub paradigm pres
ented last year: The confluence of geo data and open data. This time we wi
ll look at the metadata edition and maintenance aspect.\n\nWriting metadat
a to describe a dataset is an essential part of managing a catalog. Each r
ecord in a catalog has been written\, or at the very least enriched\, by a
ctual humans. GeoNetwork is a very widely used open-source metadata catalo
g\; as such\, it offers powerful tools in this regard: custom edition form
s\, batch editing\, templates\, custom XSL processing\, advanced edition i
n XML\, etc.\nDespite all these features\, authoring metadata is often fel
t as a difficult process\, involving complex actions\, convoluted validity
rules and an intricate knowledge of metadata schemas like ISO19139.\n\nOu
r vision for this new metadata editor can be summed up in three phrases:\n
- Make metadata accessible to everyone\n- Forget about metadata schemas\n-
Build your own editor\n\nThis editor is made to feed content into your Da
tahub. Whether you want to describe open data\, geo data or anything else\
, the editor will make it simple for you! Come and discover the concepts b
ehind the scenes.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Rethink geo/open metadata edition in GeoNetwork - Olivia Guyot\, Fl
orent Gravin
URL:http://talks.osgeo.org/foss4g-2023/talk/GECX9K/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-A8ZSET@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T133000
DTEND;TZID=Europe/Tirane:20230630T140000
DESCRIPTION:The substantial reduction of disaster risk and life losses\, a
major goal of the Sendai Framework by the United Nations Office for Disast
er Risk Reduction (UNISDR)\, requires a clear understanding of the dynamic
s of the built environment and how it affects\, in case of natural disaste
rs\, the life of communities\, represented by local governments and indivi
duals. The framework states that communities participating in risk assessm
ents should increase their understanding of efficient risk mitigation meas
ures. \n\nEarthquakes are threatening many regions in the world with const
antly increasing risk due to rapid urbanization and industrialization. Ear
thquakes do not kill people\, buildings do. Thus\, the main threat of eart
hquakes comes from building damage and collapse. To improve resilience and
preparedness\, we need to estimate the risk\, the possible damage of buil
dings and the related human and financial losses. This requires not only t
he position\, size and class of buildings\, but also the reconstruction va
lue and the number of people inside the building at any time. For this\, e
xposure models are used that translate the physical earthquake hazard to b
uilding damage\, human and financial losses. Exposure models usually descr
ibe the built environment of administrative regions as groups (aggregates)
of different building classes and their frequency.\n\nWe present our open
\, dynamic\, and global approach to describe\, model\, and classify every
building on Earth with the greatest level of detail. Our model is based on
the building data from OpenStreetMap and engineering information from ope
n exposure models\, combining these two sources to a building-by-building
description of the exposed assets. We retain the aggregated descriptions w
here the building coverage in OpenStreetMap is incomplete and describe eve
ry building separately where building data is available. Due to the near-r
eal-time computations of our model\, it directly profits from the growth o
f OpenStreetMap and with about 5 million buildings added each month (or ap
prox. 2 per second)\, the areas of incomplete coverage are constantly shri
nking\, making way for our building-specific exposure model.\n\nHere\, we
introduce shortly the earthquake phenomenon\, how it affects the built env
ironment\, why a high level of detail is necessary for useful assessments
of the impact and the consequences of earthquakes\, how OpenStreetMap and
other open data helps us to achieve this goal and how communities can bene
fit for the model for their own risk assessments.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Earthquakes and OpenStreetMap - Danijel Schorlemmer
URL:http://talks.osgeo.org/foss4g-2023/talk/A8ZSET/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-T8KPJF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T133000
DTEND;TZID=Europe/Tirane:20230630T140000
DESCRIPTION:In the FOSS4G 2021 programme\, the word 'notebook' appeared ten
times and the word 'jupyter' ten times too in the abstracts of four works
hops and four presentations.\n\nIn 2022\, 'jupyter' and 'notebook' appear
in two workshops and two presentations abstracts.\nMore discreetly\, at le
ast three workshops and one scientific paper used notebooks without mentio
ning them.\nAs we can see\, notebooks are becoming increasingly common in
data science and the geospatial world.\n\nBut what is a notebook? What is
it useful for? What are its limitations? \nAre there other platforms than
Jupyter?\nCan we do anything other than Python? What about geospatial? Are
these tools FOSS?\nThese are some of the questions that this presentation
will try to answer.\n (TL\;DR: yes!)\n\nIf you have never heard of Quarto
\, Observable or Org-mode\, this presentation is for you.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Notebooks in (geo)datascience - Nicolas Roelandt
URL:http://talks.osgeo.org/foss4g-2023/talk/T8KPJF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GHEMBD@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:Finland is reputed to be the Land of a Thousand Lakes\, but a m
ore precise estimate is that Finland has 57000 lakes which are larger than
one hectare. The precise shorelines of all the lakes have been available
as open data since 2012 but the situation with the bathymetric data is not
as good. Depth contours are available for about 80% of the total lake are
a\, but oldest soundings are from the end of the 19th century. Bathymetric
data of the lakes has not been considered particularly important and the
old measurements have not been systematically updated and verified. Theref
ore\, the most common acquisition method in the existing bathymetric data
is still manual measurement with a plumb line through the ice. Because the
depth points are frequently 75-100 meters apart\, such data are only usab
le for creating rather approximate depth contours.\n\nHowever\, since mid
1980s the Finnish Environment Agency\, the Finnish Transport and Communica
tions Agency Traficom\, and their predecessors\, have been mapping lake ba
thymetry with sonar sounding. In recent years these agencies have publishe
d their depth point data as open data under the CC-BY 4.0 license. These n
ew datasets are essentially XYZ point clouds. Thanks to open source GIS pr
ograms anybody can take these datasets and create digital elevation models
(DEM) of the lake bottoms\, colored hillshade visualizations\, 3D-models\
, and even traditional depth contours.\n\nThis presentation will dig into
the nature of the data that is collected with sonar soundings and how it a
ffects the selection of the interpolation method. A complete open source w
orkflow that is using GDAL and Generic Mapping Tools (GMT) will be present
ed. The workflow begins from raw point measurements and lake shoreline vec
tors\, and yields a DEM\, hillshade visualization with a color table\, and
depth contours. Results for more than 1800 Finnish lakes will be availabl
e online\, but the main outcome is the workflow itself. Because only comma
nd line tools which can be scripted and parameterized are used\, it is sim
ple to tune the process so that the output will suit different needs.
DTSTAMP:20240328T234514Z
LOCATION:UBT D / N112 - Second Floor
SUMMARY:Lake bottom DEMs from open data with GDAL and GMT - Jukka Rahkonen
URL:http://talks.osgeo.org/foss4g-2023/talk/GHEMBD/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UKZ7EA@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:R is well-known for its unsurpassed provision of well documente
d statistical functions and packages in the default installation. Less wel
l-known is its excellent support for spatial data through packages such as
sf\, terra\, and stars. A thriving ecosystem of diverse and often topic-s
pecific packages build on these foundations\, making R a powerful command-
line GIS (Geographic Information System) for reproducible research. Howeve
r\, dedicated GIS software (e.g. QGIS) offers specific processing algorith
ms that are either not available in R\, or may achieve a higher level of p
erformance than their equivalents in R. This presentation describes how it
is now possible to combine the strengths of R and QGIS through R packages
that interface processing algorithms provided by QGIS. These packages (qg
isprocess\, qgis) allow users to create data processing pipelines that com
bine R and QGIS algorithms almost seamlessly. We discuss the current state
of these R packages and demonstrate the usage of their most important fun
ctions by example. Finally\, we shed light on future development direction
s and seek feedback from the community.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Interfacing QGIS processing algorithms from R - Floris Vanderhaeghe
URL:http://talks.osgeo.org/foss4g-2023/talk/UKZ7EA/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-DCFDXR@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:Deck.gl is a framework for visualization\, animation and 3D edi
ting of large volumes of data (up to millions of points)\, in the browser\
, with optimal performance thanks to WebGL technology and the computing po
wer of the GPU.\n\nDeck.gl is prepared to work seamlessly with WebGL based
map libraries such as MapLibre GL JS\, Mapbox GL JS or Google Maps. It ex
tends their capabilities with a large number of formats\, data types and l
ayer visualizations\, such as point clouds (tessellated or not)\, real 3D
vector data\, 3D models\, on-the-fly clustering\, trip animations\, GPU fi
ltering\, etc. The deck.gl code is not only free\, but designed with exten
sibility in mind\, making it very easily customizable.\n\nIn this presenta
tion we will show 4 use cases developed for companies and administrations
with specific needs. We chose deck.gl (over Mapbox/MapLibre alone) to prov
ide rich interactivity and the ability to visually analyze large amounts o
f data.\nWe will expose the challenges we faced and how deck.gl was used:\
n1. Information system for precision irrigation: in a region of 25\,000 pl
ots\, we show animated time series of evapotranspiration data\, vegetative
vigor\, or water needs during an annual cycle.\n2. Biodiversity world map
: instant loading of a dataset of 200\,000 points with GPU filtering\, pro
viding interactivity and refresh rates far beyond the ones offered by Mapb
ox or MapLibre.\n3. Precision topographic measurements on terrain surface
models: visualization of point clouds\, terrains\, textures\, contour line
s and other vector cartography in 3D\, multi-profiles\, and in-browser 3D
editing.\n4. Urban data control panel: from a dataset of 40\,000 georefere
nced records\, we apply spatiotemporal and categorical filtering\, 3D dyna
mic aggregation and symbolization\, and computation of indicators and grap
hs in real time.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:When vector tiles are not enough: advanced visualizations with deck
.gl - Marti Pericay\, oscarfonts
URL:http://talks.osgeo.org/foss4g-2023/talk/DCFDXR/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QDS7YC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:Initiated in 2002\, the OSGeo project deegree has developed to
an important and mature building block for Spatial Data Infrastructures (S
DI) over the last 20 years. The project provides 9 official Reference Impl
ementations of OGC Standards such as GML\, WFS\, WMS\, and OGC API - Featu
res.\n\nIn this talk\, we will focus on the recent improvements available
in deegree webservices v3.5 and the updated roadmap for the next version w
hich lists support of Java 17. We will also show how the OGC Standards OG
C API - Features Core and CRS have been implemented and can be used with e
xisting configurations.\n\nFinally\, we will present the future directions
of the project and what developments are currently planned.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:State of deegree: The 2023 update - Torsten Friebe\, Dirk Stenger
URL:http://talks.osgeo.org/foss4g-2023/talk/QDS7YC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PH3KFN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:In recent years\, the democratisation of access to Earth Observ
ation (EO) data\, in parallel to the increased volume and variety of such
data\, have led to the paradigm shift towards “bringing the user to the
data” [4]. This is exemplified by the European Copernicus Programme\, wh
ich on a daily basis makes available terabytes of high quality\, openly-li
censed EO data suitable for a wide range of research and commercial applic
ations. The computational power required to work with these large amounts
of data\, as well as a renewed interest for Artificial Intelligence models
\, and the need for large storage volumes were met with a rise of cloud-ba
sed digital infrastructures and services. These infrastructures provide en
vironments that can be readily instantiated and equipped with the necessar
y data and processing tools all accessible in one place\, in a highly auto
mated and scalable manner to support users in analysing EO data in the clo
ud. Several such infrastructures as well as other initiatives (the latter
also including services and components offering specific capabilities) hav
e been developed\, either as a byproduct of single companies leveraging en
ormous hyperscale computing powers (such as Google Earth Engine\, Microsof
t Planetary Computer and Earth on AWS) or as projects funded and operated
by international communities that are primarily driven by specific policy
objectives. Examples are projects publicly funded by the European Commissi
on and the European Space Agency\, such as the Data and Information Access
Services (DIAS) platforms\, and the Thematic and Regional Exploitation Pl
atforms.\nThe current landscape of digital infrastructures and initiatives
for accessing and processing EO data is fragmented\, with varying levels
of user onboarding and uptake success\, see e.g. [3]. Within this context\
, we offer a user-centric framework used to review 50+ existing digital in
frastructures and initiatives for EO. Our work is expected to extend the s
cope and outlook of similar smaller reviews [1]\, where 7 digital infrastr
uctures are qualitatively compared according to a set of ten criteria\, ma
inly of a technical nature. The proposed review framework is conceptualise
d from a user-driven perspective by mapping user needs to current infrastr
ucture and service offers\, ultimately aiming at identifying overlaps and
gaps in the existing ecosystem. The framework is organised around 5 pillar
s corresponding to common problem areas: 1) sustainability of the service\
, 2) redundancy of service\, 3) user onboarding\, 4) price and 5) user nee
ds. Within each problem area\, we further identified a number of good prac
tices for user-centric developments of infrastructure and services. The go
od practices are derive from the authors’ longstanding experience in usi
ng digital EO infrastructures and are framed around several aspects relate
d to open principles\, both from the technical and the organisation side.\
nThe first pillar is the sustainability of the infrastructure/initiative a
fter the initial funding phase. Good practices include: fostering the crea
tion of a community of users/developers that ensures preservation/evolutio
n of the infrastructures/tools\; releasing software under open source lice
nses\, which encourages the reuse and growth of products considered to be
useful by the community\; adopting open standards and releasing specificat
ions in the public domain\, facilitating interoperability and reuse.\nThe
second pillar is the fragmentation between infrastructures/initiatives cau
sing redundancy of services. Relevant good practices involve the use of op
en source licensing models in favour of collaboration and reuse\, the adop
tion of common open standards and Application Programming Interfaces (APIs
)\, the federation of resources and federated authentication. \nThe third
pillar consists of the steep learning curve often needed to start using di
gital infrastructures/initiatives\; related good practices include\, in ad
dition to well-written and openly available documentation (including resou
rces such as step-by-step videos and tutorials)\, the availability of sand
boxing solutions that allow users to experiment with the infrastructure/in
itiative to understand if the offer matches the needs. \nThe fourth pillar
is the price of using infrastructures\, which is not always transparent a
nd/or clearly describing the services offered. The related good practice c
onsists in the provision of a full and transparent list of services and re
lated costs. \nThe fifth and last pillar is the top-down design and implem
entation of the infrastructure/initiative\, with limited consideration of
user’s needs. Good practices include co-design approaches\, where users
are actively involved in all phases and their feedback used to adjust the
developed prototype [2]\, the establishment of helpdesks\, forums\, mailin
g lists and channels fostering community growth around the project\, and t
he adoption of open source development and open governance.\nThe results o
f applying this review framework to 50+ digital EO infrastructures and ini
tiatives shed light on a first set of limitations (from a user-driven pers
pective) common to many platforms. The most important include: discoverabi
lity of available datasets\; steep learning curve to start using their ser
vices\; difficulty to understand what the offered services are and whether
they fit user needs\; not fully transparent pricing\; no reusability of s
oftware components\; poor interoperability\; vendor lock-in\; no facilitat
ion for code sharing/reuse\; lack of guarantee of long-term sustainability
of the infrastructure\; internal policies hampering publication of commer
cial added-value code/algorithms. At the same time\, the review identified
some promising digital EO infrastructures and initiatives that already ad
opt most of the aforementioned good practices. These include\, among other
s\, the OpenEO API initiative\, which aims to facilitate interoperability
between cloud computing EO platforms\, and the infrastructure of the Open
Earth Monitor project\, which adopts an open source\, open data and open g
overnance model by default.\nThis review\, which is currently being applie
d to a growing number of infrastructures and initiatives\, is expected to
help the user community identify overlaps\, gaps and synergies as well as
to inform the providers of infrastructures and initiatives on how to impro
ve existing services and steer the development of future ones.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Digital Earth Observation infrastructures and initiatives: a review
framework based on open principles - Margherita Di Leo
URL:http://talks.osgeo.org/foss4g-2023/talk/PH3KFN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-XR8WAT@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:The Open Geospatial Consortium API family of standards (OGC API
) are being developed to make it easy for anyone to provide geospatial dat
a to the web\, and are the next generation of geospatial web API standards
designed with resource-oriented architecture\, RESTful principles and Ope
nAPI. In addition\, OGC APIs are being built for cloud capability and agil
ity.\n\nThe OGC API - Processes standard supports the wrapping of computat
ional tasks into executable processes that can be offered by a server thro
ugh a Web API and be invoked by a client application. The standard specifi
es a processing interface to communicate over a RESTful protocol using Jav
aScript Object Notation (JSON) encodings. Typically\, these processes exec
ute well-defined algorithms that ingest or process vector and/or coverage
data to produce new datasets or analyses.\n\npygeoapi is an open source Py
thon server implementation of the OGC API suite of standards. The project
emerged as one of the most effective reference implementations that provid
es the capability for organizations to deploy OGC API endpoints using Open
API\, GeoJSON\, and HTML. pygeoapi is built on an extensible plugin framew
ork in support of clean\, adaptive data integration and easy customization
.\n\nPrefect is an open source data workflow orchestration platform develo
ped in Python. It provides robust orchestration of workflows and offers a
large set of features that range from monitoring to supporting cloud stora
ge\, to periodic execution\, etc. It is a robust and very capable workflow
engine\, which is a perfect fit for managing execution of OGC API – Pro
cesses requests in pygeoapi.\n\nThis presentation will provide an overview
of the prefect process manager plugin for pygeoapi and will demonstrate:\
n\n- How to use pygeoapi for handling OGC API - Processes use cases\n- How
the pygeoapi prefect plugin is a good match for managing the execution of
processes and what are its main strengths as a geospatial data processing
platform
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Implementing OGC API - Processes with prefect and pygeoapi - France
sco Bartoli\, Ricardo Garcia Silva
URL:http://talks.osgeo.org/foss4g-2023/talk/XR8WAT/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-9CSGBM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:Orfeo ToolBox is now a mature software with more than 100 appli
cations dedicated to remote sensing and data extraction. \nIt is used bot
h in academic works\, in operational processing chains.\nOTB now needs to
be more modular ("core"\, "machine learning"\, "SAR"\, "feature extraction
") and also easier to use through Python. \nWe will present the recent dev
elopments and our roadmap.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Orfeo ToolBox : roadmap to a more modular and pythonic OTB - Yannic
k TANGUY
URL:http://talks.osgeo.org/foss4g-2023/talk/9CSGBM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-BKTZWV@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:This presentation focuses on the use of MapStore to navigate ur
ban scenarios using its 3D tools and capabilities. Latest versions of MapS
tore include improvements and tools related to the exploitation of 3D data
such as Map Views\, Styling\, 3D Measurements and more. Support for 3D Ti
les and glTF models through the Cesium mapping library has also been great
ly enhanced to provide support for more powerful integration.\n\nAttendees
will be presented with a selection of use cases around the following topi
cs: visualization of new projects for urban planning\, relations between d
ifferent levels of a city and descriptions of events inside a city. At the
end of the presentation attendees will be able to use the presented work
flows to replicate them on different urban scenarios using the 3D tools of
the MapStore WebGIS application.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Navigate urban scenarios with MapStore 3D tools - Lorenzo Natali\,
Stefano Bovio
URL:http://talks.osgeo.org/foss4g-2023/talk/BKTZWV/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-PB7CHM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:In preparation for a new Alpine Club map by the Institute of Ca
rtography of the TU Dresden around Mt. Ushba in Georgia in the Great Cauca
sus\, the decision was made to use OpenStreetMap as the primary data sourc
e for the map. As a result\, the fieldwork in place contributed to OpenStr
eetMap to use gained information for map production by using OpenStreetMap
. In the past\, data import and organized mapping had already happened\, l
eaving gaps only fillable by fieldwork.\n\nMapping campaigns took place in
2021 and 2022. In preparation\, it was necessary to identify missing or u
ncertain information. The catalogue of objects which should be mapped was
derived from existing Alpine Club maps and the feature tags of OpenStreetM
ap. Several trails currently missing in OpenStreetMap were identified by c
ollecting and comparing openly available GPS tracks\, hiking guides\, and
old maps. The comprehensive information collection summarized the knowledg
e of all the sources. It became central for planning the office work on th
e data and organizing the extensive on-site mapping.\n\nBased on the colle
cted information\, the routes were planned in advance and during the field
work assigned to the mapping teams. On tour\, new data was collected\, whi
ch could not be obtained from aerial images such as small paths\, hiking r
outes\, guideposts\, and POIs. \n\nThe collection of geographical names w
orked similar to the collection of missing paths. After reviewing and sele
cting various sources\, an updated set of names has been compiled. Old map
s play an important role because they sometimes contain names that need to
be added or allow updates for more recent documents. Combined with backgr
ound literature on the region\, uncertainties in assigning geographical fe
atures can frequently be solved. Asking locals helped in finding the ideal
spelling. The result is a much more consistent toponym base both in the O
penStreetMap database and in the derived produced map.\n\nThe presentation
will share the knowledge on preparing and organizing the fieldwork for su
ch a project. Significant aspects are how to identify missing ways and to
collect geographic names.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:How to improve OpenStreetMap for the production of a hiking map - M
athias Gröbe
URL:http://talks.osgeo.org/foss4g-2023/talk/PB7CHM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UHDCZ7@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T140000
DTEND;TZID=Europe/Tirane:20230630T143000
DESCRIPTION:In this talk we give an example of how open source tooling enab
les companies to fast-track software development\, while simultaneously be
nefitting the FOSS4G community. Our use case is the development of the use
r interface for hydrodynamic simulation software\, including editing and a
nalysis\, called the 3Di Modeller Interface.\n\nTraditionally hydrodynamic
simulation software companies develop their own user interfaces\, usually
closely resembling GIS packages\, (re-)implementing features like backgro
und maps\, layer management\, geoprocessing tools\, and styling options. I
n our approach we turned it around. Instead of developing our own GIS-like
software\, we used QGIS to leverage development. Specifically for larger
governmental agencies (where a certain well-known proprietary GIS suite is
often the only GIS that employees are allowed to use)\, we packaged our i
mplementation in an installer\, enabling modellers to use QGIS for hydrody
namic analysis within their organisations.\n\nThis approach has several ad
vantages for users and for the FOSS4G community. For users\, hydrodynamic
modelling tools seamlessly integrate with the ever expanding GIS capabilit
ies that QGIS has to offer\; and users can built their own custom tooling\
, combining our own open libraries for hydrodynamic modelling with FOSS4G
libraries like PyQGIS\, Shapely\, NetworkX\, GDAL or QGIS.\nFor the FOSS4G
community\, this approach increases the user base\, including users that
are into developing their own plugins\, it increases sustainable membershi
ps\, and creates job opportunities for FOSS4G developers.\n\nThe 3Di Model
ler Interface is developed by Nelen & Schuurmans\, a Dutch water and IT co
mpany\, in collaboration with Lutra Consulting\, a European FOSS4G company
. Its development relies on several open source projects: QGIS\, Shapely\,
GDAL\, GeoAlchemy2\, and NetworkX\, amongst others. When we started in so
ftware development\, we used open source mainly because it was free of cos
t. During the development\, the board of directors became convinced that c
ontributing to several open source projects (financially and/or developing
) is the way forward.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Open source tooling for hydrodynamic simulation software developmen
t - Leendert van Wolfswinkel
URL:http://talks.osgeo.org/foss4g-2023/talk/UHDCZ7/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KXQPY3@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T143000
DTEND;TZID=Europe/Tirane:20230630T150000
DESCRIPTION:OpenStreetMap (OSM) is the largest crowd-sourced mapping effort
to date\, with an infrastructure network that is considered near-complete
. The mapping activities started as any crowd-sourced information platform
: the community expanded OSM anywhere there was a collective interest. Ini
tial efforts were found around universities or hometowns of mappers. Event
s\, such as natural disasters can also trigger a major update. The recent
earthquakes in Turkey and Syria lead to a massive contribution by the Huma
nitarian OSM Team (HOT) of more than 1.7 million buildings in the region i
n less than a month after the event1. This type of activities result in a
map that is of non-uniform completeness\, with some areas having all build
ing footprints in\, while other areas remain incomplete or even untouched.
Currently\, with 550 million footprints\, OSM identifies between a quarte
r and half of the total building footprints in the world\, if we estimate
that there are around 1-2 billion buildings in the world.\n\nA global view
on the local completeness of buildings in OSM did not yet exist. Unlike o
ther efforts\, that only look at a subset of OSM building data (Biljecki &
Ang 2020\; Orden et al.\, 2020\; Zhou et al.\, 2020)\, we have used the G
lobal Human Settlement Layer (GHSL) to estimate completeness of the entire
dataset. The remote sensing dataset is distributed onto a grid of approxi
mately 100x100 meter tiles. In each tile of the grid\, the built area of G
HSL is compared to the total area of OSM building footprints. The computed
ratio is measured against a completeness threshold that is calibrated usi
ng areas that were manually assessed. \n\nUsing information derived from r
emote sensing datasets can be problematic: GHSL does not only measure buil
ding footprints: it includes any human-built structures\, including infras
tructure and industrial areas. Next to that\, due to sub-optimal input dat
a or failing algorithms\, the dataset is not of the same quality as the cr
owd-sourced data in OSM in areas that are complete. Even with these limita
tions\, a comprehensive global completeness assessment is created. The ass
essment should not be used as ground truth\, but rather as reflection on t
he OSM building dataset as is and as a guideline for priorities for the fu
ture. Statistics on regional completeness can be created and the quality o
f GHSL could be assessed on countries that are considered to be complete\,
such as France or the Netherlands.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:The state of OpenStreetMap buildings: completeness assessment using
remote sensing data - Laurens Oostwegel\, Danijel Schorlemmer
URL:http://talks.osgeo.org/foss4g-2023/talk/KXQPY3/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-7NEL3P@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T143000
DTEND;TZID=Europe/Tirane:20230630T150000
DESCRIPTION:The National Land Survey of Finland (NLS) is rebuilding its top
ographic data management system using open source components. The new syst
em will be based on QGIS and PostgreSQL. The goals of the renewal are: \n-
Utilization of new technologies and standards \n- Advancement in the tran
sition from producing map data to producing spatial data \n- Enhancement o
f the quality and timeliness of data \n- Enhancement of the production thr
ough automation and better tools \n\nThe current system has been in use fo
r over 20 years and has been developed throughout its lifespan. NLS is pla
nning to replace the current production system after the first phase of de
velopment in 2025. \n\n \n\nIn this talk\, I will talk about the status of
the development\, elaborate the main objectives of the first phase and in
troduce the published OS components so far. In the first two years of the
development the focus was on concurrent data management by 100 operators a
nd on the integration of the stereo mapping tools (proprietary). In additi
on\, we have designed and implemented OS quality assurance tools to ensure
the logical consistency of the features concerning the attributes\, the g
eometries and the topology. These tools also include a topological rule se
t for topographic data management in PostgreSQL. \n\n \n\nWe have also pub
lished some plugins for the operators to improve the digitizing workflow.
To facilitate the development work\, we have contributed some development
tools for QGIS plugin developers. The OS publications of the service and c
lient components of the concurrent data management tools are not yet on th
e roadmap although our final goal. \n\n \n\nThe current process of maintai
ning topographic data includes some field work too. QField is the chosen O
S tool for that purpose. Now\, we are defining the additional functionalit
ies needed to make the field work efficient enough and to smooth out the d
ata transfer between the main system and the mobile application. \n\nAfte
rwards\, we have yet to make significant progress in the integration of TD
MS with the systems that produce and provide products. In relation to our
products\, we need to find a way to easily maintain base topographic data
and its enriched cartographic derivates and place names\, as part of the p
roduction process.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Development of QGIS based topographic data management system - Eero
Hietanen
URL:http://talks.osgeo.org/foss4g-2023/talk/7NEL3P/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-QYP7YU@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T143000
DTEND;TZID=Europe/Tirane:20230630T150000
DESCRIPTION:### Introduction\nThe analysis of georeferenced social media (S
M) data holds broad potential for informing municipal policy-making. Local
adaptation to climate change and disaster resilience\, transforming city
centers\, gentrification\, and demographic change are significant challeng
es for municipalities. \nIn light of these pressing topics\, a growing awa
reness for data-driven decision making has fostered geospatial interfaces
that allow practitioners to interactively explore data source. \nParticula
rly SM offers the potential of a live feed and continuous reflection of ev
ents at scale. Although many studies have an urgent need for a purpose-dri
ven\, customized visualization of spatial data\, little emphasis has been
put on how to display these data.\nMany studies on map-based visualization
in SM use traditional cartographic methods\, such as pins or choropleth m
aps\, with varying color scales or heatmaps to represent absolute or relat
ive values. However\, SM data presents challenges that require more sophis
ticated statistical metrics and flexible visualization techniques. We asse
ss the signed chi metric\, specifically designed for mapping via binning\,
and expand its use in a Bonn case study using an on-the-fly hexagonal bin
ning method for frontend applications like dashboards. We then evaluate th
e advantages and disadvantages of the various proposed metrics and visuali
zations in terms of their practical applications.\n\n### Problem Statement
\nAs the overview by (Teles da Mota & Pickering 2020) has shown\, research
involving geo-SM from different platforms has become increasingly popular
but bears specific problems inherent to the characteristics of volunteere
d geographic information (VGI) – volume\, veracity\, velocity\, variety
are just broad categories used to characterize these.\n\nFirstly\, Access
to SM databases\, such as Meta or Twitter\, is usually limited to capital
intensive partner companies. Instagram's public-facing API is largely undo
cumented and opaque to end-users\, causing uncertainty about data selectio
n criteria (Dunkel 2023). Hence\, the lack of knowledge about data context
and possible biases can affect the representativeness of the data subset.
\n\nSecond\, "super users" sharing repeated content may create noise and
skew analysis outcomes if absolute values are solely considered.\n\nThird\
, as Teles da Mota & Pickering (2020) point out\, research has been conduc
ted mainly for large areas ranging from national parks to entire countries
or seldomly even the whole world (cf. Dunkel et al. 2023). Studies workin
g with data on the municipal level where individual locations and differen
ces of only a few meters play a significant role\, are usually not focusin
g on methodological cartographic issues or appropriate metrics but rather
on effectively communicating core research results. Due to this lack of re
ference material for the municipal level\, a research gap of proper visual
ization methods is identified.\n\nLastly\, VGI\, as practiced by Instagram
\, poses a unique problem for researchers. Users are allowed to create pub
lic "Instagram Locations" and tag their posts with a coordinate of their c
hoice\, which can then be referenced by other users as well. However\, the
user is not obligated to provide a clear definition of what exactly is me
ant by the location they choose\, creating ambiguity. For instance\, the [
"Bonn" location](https://www.instagram.com/explore/locations/107481562)'s
coordinates (50.7333\, 7.1) are situated in the city's center. What it act
ually refers to is entirely subject to the interpretion of the user. It co
uld refer to different extents of the city center\, the official administr
ative boundaries of Bonn or anything loosely associated with Bonn\, includ
ing cultural references or events. This ambiguity which Meta is aware of (
Delvi et al. 2014) can be observed on different zoom levels such as city d
istricts\, cities\, countries or continents throughout Instagram data and
poses an enormous challenge to researchers working with city-scale areas o
f interest.\n\n### Research Interest\nIn order to deal with these challeng
es\, a thorough data cleaning is insufficient. We propose an application-o
riented system of metrics for data processing and visualization depending
on the user’s needs\, by comparing possible application scenarios as wel
l as limitations based on a case study for the city of Bonn with Instagram
data from 2010 - 2022:\n1. Absolute values – absolute number of observe
d posts per location or bin\n2. Relative values – relation between obser
ved and expected posts per location or bin\n3. Signed chi – statistic va
lue indicating significance and direction per location or bin\n\nThe *obse
rved* value usually refers to a quantity found at a specific bin\, using a
specific query such as a thematic filter. In contrast\, the *expected* va
lue often refers to an average quantity of a generic query\, such as the a
verage of all SM posts in Bonn\, and it is used to identify over- or under
represented spatial patterns at local bins (Visvalingam 1978). However\, w
hat is considered as the observed value for normalization is up to the ana
lyst (Wood et al. 2007). One could also compare average thematic posts in
all German cities (the expected value) to those found in Bonn\, as a means
to concentrate on the difference of the subject under analysts (posts in
the city of Bonn). Or\, another option could be to use discrete periods of
historical time intervals as the expected value\, and compare to the rece
nt posts quantities to identify recent and unusual spatial posting behavio
r trends. \n\nWe evaluate these metrics through a hexagonal on-the-fly bin
ning approach with different color scaling and propose easily customizable
scripts for the [leaflet-d3 plugin](https://github.com/bluehalo/leaflet-d
3). We provide all our scripts for reproduction with explanations and usag
e recommendations as well as a demo dashboard in a public GitHub repositor
y.\n\nOur findings suggest that all of the investigated metrics can offer
insight into data\, but their appropriate use highly depends on the resear
ch question at hand. When using the dashboard frontend\, outliers should b
e highlighted\, non-significant values reduced in opacity\, or intra-datas
et validations being carried out through automatic comparisons across metr
ics and filters. Overall\, the absolute metric is to be used sparingly. Th
e relative metric generates only a very narrow gain in knowledge whereas t
he signed chi metric yields the best overall results and deals very well w
ith the above issues.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:An application-oriented implementation of hexagonal on-the-fly binn
ing metrics for city-scale georeferenced social media data - Dominik Weckm
üller
URL:http://talks.osgeo.org/foss4g-2023/talk/QYP7YU/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KWEXHK@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T143000
DTEND;TZID=Europe/Tirane:20230630T150000
DESCRIPTION:[BBOX](https://github.com/sourcepole/bbox) is a new OGC API Ope
n Source implementation\, with support for established OGC services driven
by MapServer or QGIS Server. BBOX is implemented in Rust\, with a built-i
n high-performance web server.\n\nSupported OGC API Services:\n* OGC API -
Maps\, with support for OGC WMS 1.3\n* OGC API - Tiles\, with support for
WMTS and XYZ endpoints\n* OGC API - Features\n* OGC API - Processes\, wit
h multiple processing engine backends\n\nEnterprise ready:\n* Authenticati
on / Authorization\n* Instrumentation + Monitoring\n* First class Docker s
upport\n\nSimple usage:\n* bbox-server serve –map alaska.qgz
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:BBOX – a modular OGC API server - Pirmin Kalberer
URL:http://talks.osgeo.org/foss4g-2023/talk/KWEXHK/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-FJFFMF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T143000
DTEND;TZID=Europe/Tirane:20230630T150000
DESCRIPTION:Keeping (OGC) Geospatial Web Services up-and-running is best ac
commodated by continuous monitoring: not only downtime needs to be guarded
\, \nbut also whether the services are functioning correctly and do not su
ffer from performance and/or other Quality of Service (QoS) issues.\nGeoHe
althCheck (GHC) is an Open Source Python application for monitoring uptime
and availability of OGC Web Services.\nIn this talk we will explain GHC b
asics\, how it works\, how you can use and even extend GHC (plugins).\n\nT
here is an abundance of standard (HTTP) monitoring tools that may guard fo
r general status and uptime of web services. \nBut OGC web services often
have their own error\, "Exception"\, reporting not caught by generic HTTP
uptime\ncheckers. For example\, an OGC Web Mapping Service (WMS) may provi
de an Exception as a valid XML response or\nin a error message written "in
-image"\, or an error may render a blank image. \nA generic uptime checker
may assume the service is functioning as from those requests and an HTTP
status "200" is returned.\n\nOther OGC services may have specific QoS issu
es not directly obvious. A successful and valid "OWS GetCapabilities" resp
onse may not \nguarantee that individual services are functioning correctl
y. For example an OGC Web Feature Service (WFS) based on a dynamic databas
e may \nreturn zero Features on a GetFeature response caused by issues in
an underlying database. Even standard HTTP checkers supporting "keywords"
\nmay not detect all failure cases. Many OGC services will have multiple "
layers" or feature types\, \nhow to check them all?\n\nWhat is needed is a
form of semantic checking and reporting specific to OGC services!\n\nGeoH
ealthCheck (GHC) is an Open Source (MIT) web-based framework through which
OGC-based web services can be monitored. GHC is written in \nPython (with
Flask) under the umbrella of the GeoPython GitHub Organization. It is cur
rently an OSGeo Community Project. \n\nGHC consists of a web-UI through wh
ich OGC service endpoint URLs and their checks can be managed\, \nand moni
toring-results can be inspected\, plus a monitoring engine that executes s
cheduled "health-checks" on OGC service endpoints. \nA database stores res
ults\, allowing for various forms of reporting.\n\nGHC is extensible: a pl
ugin-system is available for "Probes" to support an expanding number of \n
cases for OGC specific requests and -checks. Work is in progress to provid
e a GHC API for various integrations.\n\nInfo\, sources\, demo: https://ge
ohealthcheck.org
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:GeoHealthCheck - QoS Monitor for Geospatial Web Services - Tom Kral
idis\, Just van den Broecke
URL:http://talks.osgeo.org/foss4g-2023/talk/FJFFMF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TMVRKW@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T143000
DTEND;TZID=Europe/Tirane:20230630T150000
DESCRIPTION:Climate Change is affecting our daily lives. Already for many y
ears\, we are interested in how this will influence agriculture and liveli
hoods on the African continent. In this talk we will show a tracking metho
dology with open data and opensource software. The main data source is sat
ellite imagery from METEOSAT (MSG) as well as rainfall estimates by NOAA t
o show trends in the last 15 years. We will share links to free data and s
cripts and make a list of all software used in a step-by-step guide.
DTSTAMP:20240328T234514Z
LOCATION:Drini
SUMMARY:Tracking Climate Change in Africa with open data - Peter Hoefsloot
URL:http://talks.osgeo.org/foss4g-2023/talk/TMVRKW/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-JSB3VT@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T143000
DTEND;TZID=Europe/Tirane:20230630T150000
DESCRIPTION:Vectortile ecosystem have made big changes in Web Mapping\, esp
ecially in terms of Client-side map rendering. Thesedays\, costs of produc
ing and streaming tiles have been dramatically reduced by some techniques
- tippecanoe\, PMTiles… and so on. However we have the problem important
but unsolved yet: Dynamic tiles. Techniques which are matured and widely
used are for Static tiles. Static tiles are not good at streaming data fre
quently updated but we sometimes need to dynamically serve such data. In t
his talk\, I’ll survey techniques for Dynamic tiles which already exist
and propose the solution for this.
DTSTAMP:20240328T234514Z
LOCATION:Mirusha
SUMMARY:The Survey of Vectortile techniques: Static vs Dynamic - IGUCHI Kan
ahiro
URL:http://talks.osgeo.org/foss4g-2023/talk/JSB3VT/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-AB3UJS@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T143000
DTEND;TZID=Europe/Tirane:20230630T150000
DESCRIPTION:We’re drowning in data\, but the geospatial world lags badly
behind in versioning tools compared to our software counterparts. Kart (ht
tps://kartproject.org) is solving this with a practical open tool for vers
ioning datasets\, enabling you to work more efficiently and collaborate be
tter.\n\nWe will introduce you to Kart and demonstrate some of the key fea
tures\, including our QGIS plugin. And we'll highlight what’s coming nex
t on our roadmap.\n\nSince 2022 we have added support for Raster and Point
Cloud datasets\, and we'll be showing how we build on Kart's versioning a
nd spatial filtering techniques to efficiently navigate\, access\, and use
large and small datasets. For rasters and point-cloud datasets\, we'll sh
ow how you can get the benefits of Kart without having to duplicate data t
hat is already hosted in S3 in a useful format.\n\nKart allows you to quic
kly and easily manage history\, branches\, data schemas\, and synchronisat
ion for large & small datasets between different working copy formats\, op
erating systems\, and software ecosystems.\n\nModern version control unloc
ks efficient collaboration\, both within teams and across organisations me
aning everyone stays on the same page\, you can review and trace changes e
asily: ultimately using your time more efficiently.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Kart: Practical Data Versioning for rasters\, vectors\, tables\, an
d point clouds - Robert Coup
URL:http://talks.osgeo.org/foss4g-2023/talk/AB3UJS/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-YPPH9C@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T143000
DTEND;TZID=Europe/Tirane:20230630T150000
DESCRIPTION:QWC2 (QGIS Web Client 2) is the official web application of QGI
S\, that allows you to publish your projects with the same rendering\, tha
nks to QGIS Server. The environment is composed of a modern responsive fro
nt-end written in JavaScript on top of ReactJS and OpenLayers\, and severa
l server-side Python/Flask micro-services to enhance the basic functionali
ties of QWC2 and QGIS Server.\n\nQWC2 is modular and extensible\, and prov
ides both an off-the-shelf web application and a development framework: yo
u can start simple and easy with the demo application\, and then customize
your application at will\, based on your needs and development capabiliti
es.\n\nThis talk aims at introducing this application and to show how easy
it is to publish your own QGIS projects on the web. An overview of the QW
C2 architecture will also be given. It will also be an opportunity to disc
over the last new features that have been developed in the past year and i
deas for future improvements.
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Easily publish your QGIS projects on the web with QWC2 - Sandro Man
i
URL:http://talks.osgeo.org/foss4g-2023/talk/YPPH9C/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-9C99XJ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T150000
DTEND;TZID=Europe/Tirane:20230630T153000
DESCRIPTION:In the US\, less than 20% of OpenStreetMap (OSM) buildings have
a height tag (less than 10% globally). Providing buildings with height ta
gs helps several use cases including 3D map visualization. At Meta\, we ha
ve begun using open mapping data to estimate building heights and providin
g them back to the community. At the end of 2022\, we used data from city
GIS departments to estimate millions of heights and release them to the pu
blic through the Daylight Map Distribution (https://daylightmap.org/2022/1
2/02/building-heights.html). In 2023\, we are using publicly available USG
S/3DEP aerial lidar and releasing to the public through the Overture Maps
Foundation – processing millions of square kilometers. This talk will co
ver the challenges\, algorithm\, QA process\, and accuracy metrics from th
is effort. It is our hope that over the course of the year\, we can estima
te and publish heights for the majority of the buildings in the US and beg
in work on non-US open data sources as well.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N110 - Second Floor
SUMMARY:Building heights: From open data to open maps - Yunzhi Lin
URL:http://talks.osgeo.org/foss4g-2023/talk/9C99XJ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-RMH8LF@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T150000
DTEND;TZID=Europe/Tirane:20230630T150500
DESCRIPTION:Geographic Information Systems (GIS) has been around for more t
han 60 years. It has become a significant part of many scientific discipli
nes with a spatial component. In the last decades the educators have been
trying to figure out a way\, how to adopt its tools for their own field of
study\, the classrooms (Milson et al.\, 2012). Since then\, several studi
es of their efforts have been carried out. Thanks to the emergence of open
source software and open data\, new opportunities for their visions have
unfolded (Petráš\, 2015). Particularly QGIS\, in environments where teac
hers do not have access to sufficient funding\, has been lately getting mo
re attention. \n\nEducators\, backed up by years of research\, believe tha
t by collecting\, displaying and analyzing spatial data\, students can sol
ve local problems\, foster and drive their learning process of geography p
henomena. After the use of GIS they are supposed to gain digital skills an
d extraordinary thinking that can be essential for their future careers an
d be motivated to pursue a career in science and engineering (Bednarz\, 20
04). \n\nImplementation of GIS software into high school geography classes
is\, however\, a lengthy process that requires a lot of patience and conf
idence. A teacher may come across four major obstacles: 1) lack of hardwar
e\, software or data\, 2) lack of teacher training and materials\, 3) lack
of support for innovations\, and 4) lack of time to learn and teach GIS (
Kerski\, 2003). The biggest issue has come to be the insufficient pre-serv
ice and in-service teacher training in geoinformatics and its application.
A recent systematic study (Bernhäuserová et al.\, 2022) has concluded t
hat the majority of the limits were related to teachers and resources. \n\
nIn our study\, we have tried to create strategies that can lead to the su
ccessful adaptation of QGIS tools in high school geography education. To r
each out the goal and answer more questions\, we have designed ten lecture
s that focus on the basics of QGIS. We drew inspiration from several offic
ial QGIS cookbooks and manuals. In each lesson\, we applied a set of the m
ost essential tools. For our study\, we chose a qualitative method of desi
gn-based research (DBR)\, which focuses on designing study materials\, tes
ting them in classes and coming up with a theory (methodic) that can innov
ate learning environemnts (Bakker\, 2018). To pilot our ready-to-use lectu
res and data\, we have partnered with a 4-year South Moravian high school
based in Brno\, Czechia\, which offered us two classes of second and final
-year students. The research lasted three months\, during which we taught
12 courses. Older students tried out lectures 1 to 7\, except 6 (1 and 2 a
t home) and younger students tried lectures 1 to 3 and 8 to 9. After every
class\, students had to fill out a short questionnaire reflecting on thei
r feelings and experience. They had to do a set of exercises for each lect
ure as homework and turn it in along with the finished maps. At the end of
each trial\, the groups were tested on their knowledge. Based on the obse
rvation that was carried each class\, three categories according to the st
udents' experience were drown out: ones that had no problem following the
lecturer´s instructions\, ones that often faced problems and those that w
orked individually. Students were asked to identify with one of them and t
hen asked to participate in a voluntary interview\, in which their experie
nce would be discussed. \n\nDuring both trials\, students had to bring the
ir own computers\, which for some\, caused several issues\, from failed in
stallations to technical complications during each lecture. The large numb
er of students in each class (app. 30) also proved that the lecturer canno
t assist every student in such conditions. Students chose different approa
ches and strategies. Most of them wanted to finish the task and faced no p
roblems. A much smaller amount focused on understanding and worked individ
ually. Only a few played with the program and found interest in it. In eac
h group\, only one student had previous experience with QGIS. However\, mo
st of the students understood every lecture\, and found its content enjoya
ble\, and in the test\, they have proven to learn the basics of the progra
m. If it would be up to them\, they would implement GIS in the geography c
urriculum\, change the tempo of the lectures (to progress more slowly) and
divide them into smaller groups\, which would benefit both parties. The o
lder students were less motivated to participate\; they were used to class
es that were more passive and did to have enough free time to focus on any
thing except their graduation exam. Younger students were easier to motiva
te\; more of them were interested in geography and had more time for homew
ork. Both groups have produced unique maps\, which display their gradually
gained cartography skills and knowledge. They advise anyone interested in
learning QGIS to have enough patience\, gather good learning materials (r
eferring to the ones we made) and work on a computer they know very well.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Adaptation of QGIS tools in high school geography education - Jakub
Trojan
URL:http://talks.osgeo.org/foss4g-2023/talk/RMH8LF/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-D9SYDC@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T150000
DTEND;TZID=Europe/Tirane:20230630T153000
DESCRIPTION:At Bellingcat\, a non-profit investigative organization in the
Netherlands\, we research war crimes\, find tiger smugglers\, monitor envi
ronmental degradation and track extremist hate. To do this\, we use "open
sources"\, including public databases\, social media posts\, and a wide ra
nge of geospatial data and tools. The use of these new online sources has
dramatically changed investigative journalism and humanitarian accountabil
ity research in the past five years\, and there remains tremendous potenti
al for further development\, especially in the geospatial realm.\n\nIn thi
s talk\, Bellingcat data scientist Logan Williams will present case studie
s from our research to illustrate how invaluable open source geospatial to
ols and data are for "open source" investigative research. Some of the mos
t useful tools for investigators are designed for very different purposes\
, from academic meterology to outdoor recreation. Additionally\, some of B
ellingcat's own FOSS geospatial tools\, based on Open Street Map and Coper
nicus satellite data\, will be showcased. Finally\, the talk will discuss
opportunities for deepening the connections between the open source geospa
tial community and the open source investigation community.\n\nBy popular
demand this is an encore of the talk held on 28.06 @ 15:00
DTSTAMP:20240328T234514Z
LOCATION:Lumbardhi
SUMMARY:Investigating war crimes\, animal trafficking\, and more with open
source geospatial data (encore) - Logan Williams
URL:http://talks.osgeo.org/foss4g-2023/talk/D9SYDC/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-MUDTQN@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T150000
DTEND;TZID=Europe/Tirane:20230630T153000
DESCRIPTION:The CARTO Analytics Toolbox (AT) is a collection of spatial fun
ctions that add spatial capabilities to Data Warehouses. At the moment\, B
igQuery\, Snowflake\, Redshift and PostgreSQL versions are available.\n\nT
his talk will show some of the main functions of the AT\, and discuss some
examples of spatial data analysis performed in different DWs. Special emp
hasis will be put on the functionality related to spatial indexes\, partic
ularly H3 and Quadbin.\n\nThe Analytic Toolbox functions are also the buil
ding blocks for other tools both from CARTO and outside of CARTO\, which w
ill be briefly introduced as well.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Spatial Analysis with the CARTO Analytics Toolbox - Víctor Olaya
URL:http://talks.osgeo.org/foss4g-2023/talk/MUDTQN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZVPWQM@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T150000
DTEND;TZID=Europe/Tirane:20230630T153000
DESCRIPTION:The presentation will provide a comprehensive introduction to G
eoServer's own authentication and authorization subsystems. The authentica
tion part will cover the various supported authentication protocols (e.g.
basic/digest authentication\, CAS\, OAuth2) and identity providers (such a
s local config files\, database tables\, and LDAP servers). It will also c
over the recent improvements implemented with the OpenID integrations and
the refreshed Keycloak integration.\n\nIt will explain how to combine vari
ous authentication mechanisms in a single comprehensive authentication too
l\, as well as provide examples of custom authentication plugins for GeoSe
rver\, integrating it in a home-grown security architecture. We’ll then
move on to authorization\, describing the GeoServer pluggable authorizatio
n mechanism\, and comparing it with an external proxy-based solution. We w
ill explain the default service and data security system\, reviewing its b
enefits and limitations.\n\nFinally\, we’ll explore the advanced authori
zation provider\, GeoFence. The different levels of integration with GeoSe
rver will be presented\, from the simple and seamless direct integration t
o the more sophisticated external setup. Finally\, we’ll explore GeoFenc
e’s powerful authorization rules using:\n\n- The current user and its ro
les.\n- The OGC services\, workspace\, layer\, and layer group.\n- CQL rea
d and write filters.\n- Attribute selection.\n- Cropping raster and vector
data to areas of interest.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N109 - Second Floor
SUMMARY:Mastering Security with GeoServer\, GeoFence\, and OpenID - Andrea
Aime\, Alessio Fabiani
URL:http://talks.osgeo.org/foss4g-2023/talk/ZVPWQM/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-DT7QST@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T150000
DTEND;TZID=Europe/Tirane:20230630T153000
DESCRIPTION:Based on the implementation of a set of forms in Kobo Toolbox\,
an information flow for the Fire Management Commission of the Argentine R
epublic was created to be able to integrate from the field the fire report
s (on line / off line) in a simple way and their different stages of evolu
tion. The automation of the ingestion to a Geonode\, as a geospatial data
manager allows the integration with weather forecast data\, near real time
information\, fire incidences\, hot spot detection and predictive fire in
dexes.\nThe integration is done with the Airflow tool\, which guarantees i
ntegration and monitoring of information flows\, simplifying the process d
uring incidents.
DTSTAMP:20240328T234514Z
LOCATION:UBT C / N111 - Second Floor
SUMMARY:Kobo Toolbox Automation with Geonode for Risk Management - Walter S
hilman
URL:http://talks.osgeo.org/foss4g-2023/talk/DT7QST/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-TMKBHE@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T150000
DTEND;TZID=Europe/Tirane:20230630T153000
DESCRIPTION:OpenMapTiles is an open-source set of tools for processing Open
StreetMap data into zoomable and web-compatible vector tiles to use as hig
h-detailed base maps. These vector tiles are ready to use in MapLibre\, Ma
pbox GL\, Leaflet\, OpenLayers\, and QGIS as well as in mobile application
s.\n\nDockerized OpenMapTiles tools and OpenMapTiles schema are being cont
inuously upgraded by the community (simplification\, performance\, robustn
ess). The presentation will demonstrate the latest changes in OpenMapTiles
. The last release of OpenMapTiles greatly enhanced cartography and map st
yling possibilities\, especially the enrichment of Points of Interest and
improvement of land use or land cover layer. The new version of Natural Ea
rth brought updated data to upper zoom levels and included a new OSM OpenM
apTiles style\, showing all features in well know colors for vector tiles.
OpenMapTiles is also used for generating vector tiles from government ope
n data secured by Swisstopo.
DTSTAMP:20240328T234514Z
LOCATION:UBT F / N212 - Floor 3
SUMMARY:OpenMapTiles - vector tiles from OpenStreetMap & Natural Earth Data
- Tomáš Pohanka
URL:http://talks.osgeo.org/foss4g-2023/talk/TMKBHE/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KYQG9K@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T150500
DTEND;TZID=Europe/Tirane:20230630T151000
DESCRIPTION:In recent years\, the need for distance education solutions has
been a point of attention for the Faculty ITC of the University of Twente
(The Netherlands). Starting in 2017\, a fully online program spread over
nine months offered an alternative path to start an MSc in Geo-Information
Science and Earth Observation. As using proprietary software is more diff
icult in distance courses\, the focus shifted towards open-source alternat
ives. The experience and lessons learned came to their full potential when
\, in 2020\, many students could not travel due to the travel restrictions
imposed by the COVID pandemic. In response\, ITC offered the fully online
course Principles and Applications of Geographic Information Systems and
Earth Observation as the first quartile of what is supposed to be a fully
presential MSc Program. The course was developed around four fundamental p
rinciples: (1) The course was exercise led\; (2) Every concept taught shou
ld be demonstrated and operationalized\; (3) The number of different softw
are tools should be minimized\; (4) The software tools should be inclusive
and encourage technological independence. Two Open-Source tools were sele
cted: The Living Textbook a digital textbook developed and maintained by u
s [1]\, and QGIS to operationalize the concepts. For synchronous communica
tion and iteration\, Big Blue Button Conferences were integrated into the
Learning Management System environment and organized according to time zon
es to serve a student population spread across eight time zones.\n\nAfter
running the course\, we evaluated the impact of the new set-up on students
(satisfaction and performance) and staff (attitude towards open source to
ols and open courseware). Additionally\, we also evaluated the impact of t
he course in strengthening the wider Open Science initiative. Results show
that for students\, both satisfaction levels and attainment levels of the
course’s learning outcomes were high. For the teachers\, the feedback w
as generally positive\, highlighting the importance of using flexible and
inclusive tools. The courseware developed for the course is now offered to
the Open Science community as open courseware [2] . It is the basis of ha
ving the Faculty recognized as a QGIS Certified Organization\, thus streng
thening the relationship between academia and FOSS4GIS\, particularly QGIS
.\n\nInternally\, this experience brought essential insights into successf
ul online course design. These include but are not limited to (A) consiste
ncy – the tools and support materials of the course should remain the sa
me during the course\; and (B) accessibility – the tools used should not
have any accessibility barrier\, especially when it comes to licenses\, b
ut also when it comes to imposing operating system platforms or assuming f
ile format preferences. Important results include changing the teaching st
aff attitude towards a more aware and confident use of FOSS4GIS. That chan
ge resulted in new paradigm shift faculty-wide paradigm where FOSS4GIS is
now the primary choice for teaching. Finally\, on a larger plane\, the com
mitment of ITC to the Open Science agenda has\, in its compromise to adopt
and contribute to the development of Open Source Software\, an essential
element of the Open Science agenda.\n\n[1] https://www.itc.nl/about-itc/or
ganization/resources-facilities/living-textbook/\n[2] https://principles-a
nd-applications-of-rs-and-gis.readthedocs.io/en/latest/
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Teaching Geographic Information Science concepts with QGIS and the
Living Textbook – towards a sustainable and inclusive Distance Education
- Andre da Silva Mano
URL:http://talks.osgeo.org/foss4g-2023/talk/KYQG9K/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-CCEWUQ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T151000
DTEND;TZID=Europe/Tirane:20230630T151500
DESCRIPTION:Digitization and update of road network databases represents a
crucial topic for a good management of critical infrastructures by public
administrations. Similarly to other European countries such as Cyprus (Ch
ristou et al.\, 2021)\, since 2001\, Italian road-owning agencies have bee
n required by the Ministry of Infrastructure and Trasport to build and mai
ntain a road cadastre\, i.e.\, a mapping inventory of their road networks.
Such architecture should include georeferenced information about streets
as well as all ancillary elements regulated by road regulations\, ranging
from safety and protection assets to traffic signs. In particular\, due to
the high frequency of new signals installation and substitution\, traffic
signs require a well-structured\, flexible and efficient workflow for col
lecting and manipulating georeferenced data.\n\nIn agreement with the offi
cial national requirements\, in 2019 the Province of Piacenza adopted and
implemented a digital cadastre with GIS and WebGIS functionalities built o
n top of free and open-source software like PostgreSQL as Database Managem
ent System and QGIS for the manipulation of geodata. Such software infrast
ructure ensures flexibility of usage as well as the possibility to expand
its functionalities with other easy-to-use open-source applications in an
architecture (Gonzalez Alba et al.\, 2019\, Gharbi & Haddadi\, 2020). In
this framework\, this work illustrates a case study of a flexible and low-
cost mapping methodology for documenting the current state of traffic sign
s. Indeed\, mobile applications are able to substitute the old procedure t
hat consisted in the documentation of element installation on paper suppor
t\, implying the risk of transcript errors as well of loss or deterioratio
n of the original survey document.\n\nBefore defining the required steps o
f mobile mapping\, understanding how traffic signs are modelled inside th
e adopted DB model was crucial. Such elements are indeed implemented throu
gh a one-to-many relationship between an entity representing the sign hold
er (parent table) and another one for the signs themselves (child table).
In this way\, it is possible to collect and manage individually informatio
n about each sign (main ones and supplementary ones as well) always linked
to their support pole.\n\nTogether with the road cadastre responsible\, a
n analysis was conducted to understand the specific needs for the applicat
ion and the type of users involved in the in-situ survey process. This pha
se resulted in the choice of two possible open-source solutions to be test
ed and compared in terms of compatibility and usability by users with diff
erent technical background\, integration with the actual infrastructure an
d possibility of customisation: Qfield because of its native compatibility
with QGIS libraries and ODK Collect thanks to its simplified graphic user
interface (GUI) that resembles commonly used data collection forms withou
t a visible GIS GUI.\n\nFor the entire workflow\, differences in the two a
pplications were evaluated. For instance\, having a direct inheritance of
the original QGIS attribute table for Qfield\, while in the case of ODK C
ollect the definition of each attribute of the form is required. Peculiari
ties in implementing 1-n relationships and widget formats have been identi
fied too\, aiming to understand the reproducibility of both procedures. On
ce the form design was finalised for both the applications\, a guided fiel
d survey was conducted in order to train new users and to test the usabili
ty of the mobile mapping solutions. For this purpose\, a series of test si
tes was chosen\, identifying roads to be surveyed with different features
or conditions. A diverse sample of test users was involved in the data col
lection activity\, ranging from people with no previous experience in geos
patial technologies to GIS technicians.\n\nFinally\, the data collected wi
th both applications were reviewed in QGIS environment in a validation pha
se aimed at identifying differences between the dataset\, their completene
ss\, their position accuracy and their coherence with a ground truth repre
sented by photos of corresponding traffic signs taken on field with mobile
devices. First\, the validation consisted in checking if the mapped eleme
nts were located within buffers (of 5\, 25 and 50 meters) calculated along
the surveyed streets and then evaluating the coherence between the street
code inserted in the element field and the one of the roads in whose buff
er such sign is included. Hence\, a similar approach was adopted for comp
aring the value of municipality associated to the single sign field to the
administrative boundaries within which it falls. A semantic validation on
the traffic sign type documented with the mobile mapping was conducted by
comparing values with what was depicted in photos taken on field. The ent
ire validation routine process was automatized as much as possible with Py
thon scripts using the PyQGIS library. All the validation scripts together
with sample dataset will be included in a Github repository in order to m
ake them openly reusable and adaptable to other specific project needs. An
analysis on the synchronization process of the collected data on the orig
inal main database was evaluated too\, marking different approaches involv
ing plugins or automatic scripts.\n\nIn order to evaluate user experiences
with the different mobile applications\, a LimeSurvey feedback form was p
rovided to users who tested the tools on field. Such form was designed to
collect insights on different steps of the workflow – form design\, data
collection and post-processing -\, tracking and evaluating possible diffe
rences between users with different background and no previous knowledge o
f geospatial concepts. This resulted in highlighting potentials and issues
linked to the adoption of Qfield or ODK Collect for traffic signs mapping
.\n\nThis work aims at presenting a case study for the adoption of a mobil
e mapping solution in the field of public administration\, understanding p
otentials and limitations of these possible approaches\, also in terms of
introducing new users to FOSS4G applications. Because of this\, the transp
arency of the entire workflow is being documented on a dedicated Github re
pository with informative guides\, a QGIS demo project\, ODK format defini
tion files and all codes adopted for validation and synchronization purpos
es.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Mobile mapping solutions for the update and management of traffic s
igns in a road cadastre free open-source GIS architecture - Federica Gaspa
ri
URL:http://talks.osgeo.org/foss4g-2023/talk/CCEWUQ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-UYFZ9B@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T151500
DTEND;TZID=Europe/Tirane:20230630T152000
DESCRIPTION:Motivation \n \nThe state-of-the-art container format
s for managing map tiles are the Mapbox MBTiles specification and the OGC
GeoPackage standard. Since both formats are based on an SQLite database\,
they are mainly designed for a block-oriented POSIX-conform file system ac
cess. This design approach makes these file formats inefficient to use in
a cloud native environment\, especially in combination with large tilesets
. To depoly a MBTiles database in the cloud\, the tiles must be extracted
and either uploaded individually to an object storage or imported in a clo
ud database and accessed by an additional dedicated tileserver. The main d
isadvantages of both options are the complex workflow for the deployment a
nd the expensive hosting costs. The Cloud Optimized GeoTIFF (COG) format a
lready solves the problem for providing large satellite data in the cloud\
, creating a new category of so-called cloud optimized data formats. Based
on the concepts of this type of format\, geospatial data can be deployed
as a single file on a cheap and scalable cloud object storage like AWS S3
and directly accessed from a browser without the need for a dedicated back
end. COMTiles adapt and extend this approach to provide a streamable and r
ead optimized single file archive format for storing raster and vector til
esets at planet-scale in the cloud.\n\n \nApproach \n \nThe bas
ic concept of the COMTiles format is to create an additional streamable in
dex which stores the offset and size to the actual map tiles in the archiv
e as so-called index entries. In combination with a metadata document\, th
e index can be used to define a request for a specific map tile in the arc
hive stored on a cloud object storage based on HTTP range requests. The me
tadata are based on the OGC “Two Dimensional Tile Matrix Set” specific
ation which enables the usage of different tile coordinate systems. To min
imize the transferred amount of data and to optimize the decoding performa
nce\, a combination of two different approaches for the index layout is us
ed. As lower zoom levels are accessed more frequently and the number of ti
les is manageable up to a certain zoom level (0 to 7 for a planet-scale ti
leset)\, all index entries are stored in a root pyramid and retrieved at o
nce when the map is initially loaded. To minimize the size\, the root pyra
mid is compressed with a modified version of the RLE V1 encoding of the OR
C file format. For lazy loading portions of the index on higher zoom level
s index fragments are used. To enable random access to the index without a
ny additional requests\, the index entries are bitpacked per fragment with
a uniform size. Since the data are only lightweight compressed\, the inde
x entries can also be stream decoded and processed before the full fragmen
t is loaded. To further minimize the number of HTTP requests the queries f
or the index fragments and tiles can be batched as they are both ordered o
n a space-filling curve like the Hilbert curve. \n \nResults \n
\nOne advantage that became obvious during the evaluation of COMTiles is t
he simplified workflow of deploying large tilesets. As only a single file
must be uploaded to a cloud storage and no dedicated tile backend to be se
tup\, COMTiles can also be deployed by non-GIS experts in a quick and easy
way. During evaluation the main hypothesis could be confirmed that COMTil
es can be hosted on a cloud storage with only fraction of the costs compar
ed to the usage of a dedicated tile backend or an individual tile deployme
nt. To determine the actual hosting costs of a planet-scale OSM tileset wi
th 90 gigabytes in size was deployed on a Cloudflare R2 storage and access
ed with 35 million tile requests. With the pricing plans of Cloudflare at
the time of writing\, only a cost of $1.35 per month has been incurred for
the specified deployment. In this context the tile batching approach turn
ed out to be an additional effective way of reducing the number of tile re
quests and therefore the costs. For example\, when displaying a map in ful
lscreen mode the number of requests could be reduced by up to 80% on HD di
splay and up to 90% on a UHD display. In terms of user experience\, test u
sers rated the additional latency for the index requests as negligible\, e
specially when an additional CDN was used. Testing COMTiles against PMTile
s\, another cloud-optimized tile archive solution\, was performed using tw
o different map navigation patterns to measure the differences in the numb
er of requests\, data size transferred\, and decoding performance. COMTile
s outperformed PMTiles in a about 63 times faster decoding of portions of
the index\, reducing the processing time from about hundreds of millisecon
ds to a few milliseconds in a single user session. COMTiles also fetches a
bout 3 times less data on average from a cloud storage. In addition the ra
ndom-access design of the COMTiles index leads to one initial roundtrip le
ss to the server\, resulting in a faster initial map load. The main advant
age of PMTiles is a about 10 times smaller size for a planet-scale index (
~91 MB to ~880 MB). However\, since cloud storage is cheap\, the additiona
l cost of the difference in the index size proved to be negligible.\n \n<
b>Conclusions \n\nIn the evaluation it could be proven that COMTiles
can simplify the workflow for deploying large tilesets and significantly
reduce the storage costs while preserving almost the same user experience
compared to a dedicated tile backend. The author is therefore confident th
at the concepts of the COMTiles format will play an essential role in the
future for managing and deploying map tiles in a cloud native environment.
\n\n\nSources\n\nThe evaluation steps and further improvements of t
he existing COMTiles format which form the basis of this paper are availab
le under https://github.com/mactrem/com-tiles-evaluation. The derived impr
ovements will be merged into the main repository under https://github.com/
mactrem/com-tiles.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:COMTiles: a case study of a cloud optimized tile archive format for
deploying planet-scale tilesets in the cloud - Markus Tremmel
URL:http://talks.osgeo.org/foss4g-2023/talk/UYFZ9B/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-ZPFBDA@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T152000
DTEND;TZID=Europe/Tirane:20230630T152500
DESCRIPTION:In 2017\, the Media Engineering Institute (MEI) and the Institu
te of Territorial Engineering (INSIT) developed a proof-of-concept locatio
n-based augmented reality (AR) application that enabled the visualization
of geospatial data on biodiversity. A test with ten-year-old pupils confir
med the relevance of using this technology to support educational field tr
ips. However\, it also revealed usability challenges that needed to be add
ressed in a subsequent iteration. More precisely\, three main issues were
outlined: The system should allow non-expert users to create AR experience
s using open geospatial data [2]\; Users should be able to publish observa
tions in AR rather than being restricted to a passive viewing role\; The i
nstability of the points of interest (POIs) causes usability problems such
as a prolonged interaction time with the screen. \nIn an attempt to addre
ss the first two of these challenges\, we have designed and developed a ca
rtographic authoring tool for the creation of location-based AR experience
powered by open web frameworks (A-frame\, leaflet.js\, vue.js\, hapi.js
…) by leveraging a user-centered methodology [1]. We also developed a mi
nimalist library for the creation of WebXR location-based POIs in A-frame.
The resulting application allows anyone without technological know-how to
create AR learning experiences by importing/exporting open geospatial dat
a and customizing the appearance of POIs by attaching medias (3D files\, p
ictures\, sound…) to them. These can be location-triggered (visible/audi
ble) according to different conditions based on distance thresholds set by
the user. The environments can be shared publicly so that anyone may cont
ribute\, or set to visible but non-editable for visualization privileges o
nly. The application also features geolocation tracing and in-app event lo
gging for analysis. \n\nThe third challenge disclosed by the proof-of-conc
ept application was imputed to the inaccurate geolocation data available\,
as evidenced by previous studies [3–5]. Indeed\, geolocated POIs are an
chored in the AR interface by computing the geographical coordinates they
are anchored to related to the user’s esteemed position. On mobile devic
es\, GNSS accuracy typically lies between 1 m and 30 m. Due to its impact
on anchoring\, this lack of accuracy can have deleterious effects on usabi
lity. We wondered whether using more accurate data would lead to a better
usability score. We thus designed a comparative user test (n = 54) to eval
uate the application used in combination with two different geolocation da
ta types: While half of the participants used the BiodivAR application in
combination with data provided by the devices’ embedded GNSS as a contro
l group\, an experimental group used the application combined with Ardusim
ple RTK kits. During the test\, in-app events and geolocated traces were r
ecorded by the application. 47 participants also agreed to wear an eye-tra
cking device that captured their gaze direction in order to measure for ho
w long they interacted with the screen versus nature. Directly after the t
est\, participants answered an online survey containing a demographic ques
tionnaire\, an open question\, and three different usability questionnaire
s:\nSystem Usability Scale (SUS)\, for a generic evaluation of the system.
\nUser Experience Questionnaire (UEQ)\, for a comprehensive measure of use
r experience in terms of attractiveness\, efficiency\, reliability\, stimu
lation\, and novelty.\nHandheld Augmented Reality Usability Scale (HARUS)\
, a mobile AR-specific questionnaire.\n\nThe in-app events and geolocated
traces also allowed us to compute variables such as the total distance tra
veled\, the time spent visualizing medias\, or how long users have been us
ing the interactive 2D map for navigation while in AR mode. Some of these
results are still undergoing thorough analysis so that the role of each of
these independent variables (interaction time\, total distance\, amount o
f POIs visited\, etc.) on user-reported usability can be investigated by m
eans of multiple linear regression. For example\, encoding eye-tracking da
ta to measure interaction with screen versus nature is particularly challe
nging and time-consuming. Thanks to this process\, we expect to be able to
further observe the impact of geolocation data on usability. will allow u
s to compare how much time users interacted with the screen versus nature
within each group. Finally\, thanks to unstructured feedback gathered thro
ugh open questions\, we shall be able to further improve the BiodivAR appl
ication before it is tested on the field\, in the context of an educative
field trip with pupils. \n\n\nThe collected data allowed us to get an over
all evaluation of the system as well as more specific observations on the
impact of the different geolocation data. While we expected the RTK group
to give a better usability score\, the exact opposite happened. We initial
ly noticed that the using the RTK kit caused the CPU to crash more often t
han usual\, because it required an additional NTRIP client application to
run in the background. We therefore assumed that these crashes pejorated t
he usability. But when looking at the events logged\, the RTK group actual
ly suffered less crashes than the control group. It is by observing the ge
olocated traces’ shapes that we noticed the RTK group’s were star-shap
ed\, revealing numerous outlying points in the data. The GNSS control grou
p’s traces did not feature such outliers\, which we found out was due to
an embedded filter. It turns out this filter cannot be applied when using
RTK positioning systems\, because they also obliterate measurement times\
, which are typically required by professionals. Using our system in combi
nation with RTK kits made the initial positioning of the augmented objects
more accurate\, but it also brought a new source of jittering\, which we
presume resulted in the lower reported usability score. \n\nFrom the resul
ts of our comparative test\, we draw the following conclusions: While we h
ave failed to better the usability of our location-based AR system by comb
ining it with RTK data\, our test has however demonstrated a significant n
egative impact of varying geolocation data source on usability. This reinf
orced our intention to keep researching hardware and software solutions fo
r efficient improvement of geolocation data.
DTSTAMP:20240328T234514Z
LOCATION:UBT E / N209 - Floor 3
SUMMARY:Impact of Geolocation Data on Usability in Augmented Reality: A Com
parative User Test - Julien Mercier
URL:http://talks.osgeo.org/foss4g-2023/talk/ZPFBDA/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-KH9SCG@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T160000
DTEND;TZID=Europe/Tirane:20230630T163000
DESCRIPTION:Imagine a future where entire communities can harness the power
of the sun to fuel their homes and businesses\, reducing their dependence
on traditional energy sources and helping to build a more sustainable wor
ld. At FOSS4G\, I am excited to share with you a groundbreaking project th
at is making this vision a reality in Kosovo\, using the latest geospatial
technology.\n\nThrough the USAID funded Kosovo Energy Security of Supply
(KESS) activity\, DT global is working to promote sustainable energy solut
ions in Kosovo. A partnership between DT Global and DevGlobal\, are levera
ging the power of drones\, GIS software\, and open-source machine learning
models to revolutionize the way we evaluate the solar potential of indivi
dual structures. By accurately delineating the boundaries of rooftops usin
g drone imagery\, we can then apply cutting-edge photogrammetry analytics
to determine the optimal placement of solar panels.\n\nBut we're not stopp
ing there. By training the Ramp* open buildings model to successfully iden
tify and delineate rooftops in Kosovo\, using data obtained from the Kosov
o Cadastral Agency's 2023 high-resolution aerial survey campaign\, we are
laying the groundwork for a national-level approach to mapping building fo
otprints that can be utilized for a range of applications beyond evaluatin
g rooftop solar potential.\n\n*Ramp is an open-source machine learning mod
el and toolset for extracting building footprints from high-resolution sat
ellite imagery at scale.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Revolutionizing Solar Potential Assessments in Kosovo Using Drones
and Machine Learning - Lorik Haxhiu
URL:http://talks.osgeo.org/foss4g-2023/talk/KH9SCG/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-GQUNFZ@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T163000
DTEND;TZID=Europe/Tirane:20230630T173000
DESCRIPTION:FOSS4G 2023 conference closing session.\nAnnouncement of the 20
23 Sol Katz Award recipient.
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:Closing session -
URL:http://talks.osgeo.org/foss4g-2023/talk/GQUNFZ/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2023-9NNK8Z@talks.osgeo.org
DTSTART;TZID=Europe/Tirane:20230630T173000
DTEND;TZID=Europe/Tirane:20230630T183000
DESCRIPTION:OSGeo Foundation Annual General Meeting
DTSTAMP:20240328T234514Z
LOCATION:Outdoor Stage
SUMMARY:OSGeo AGM -
URL:http://talks.osgeo.org/foss4g-2023/talk/9NNK8Z/
END:VEVENT
END:VCALENDAR