FOSS4G-Asia 2023 Seoul

This workshop will provide an introduction to performing common GIS/geospatial tasks using Python geospatial tools such as OWSLib, Shapely, Fiona/Rasterio, and common geospatial libraries like GDAL, PROJ, pycsw, as well as other tools from the geopython toolchain.

In this talk we discover various aspects of styling in Geoserver. It allows us to style using various languages such as SLD, YSLD, CSS, etc. along with ability to create style using no-code way ( Geostyler ) .
In this talk we explore how to style Point, LineString, Polygon, Rasters. We'll cover following tasks
1. Attribute based Styling
2. Zoom based Styling
3. Variable Styling
4. Labelling and it's optimisation
5. Legends

OpenLayers makes it easy to put a dynamic map in any web page. In this talk we'll discover how Openlayers works, what is the methodology behind adding new data to it. We'll understand how to spin up new openlayers map under 5 minutes using React.

Openlayers allows us to put data on map, interact with it depending upon whether you use it on computer or mobile, export data with map, etc. We'll explore examples few examples from https://openlayers.org/en/latest/examples/ .

Apart from this we'll also take a look at https://viglino.github.io/ol-ext/ this is extension to the openlayers using which we can add more types of interactions, visualisations, controls, etc.

We're living in the world of APIs. CRUD operations are base of lot of operations. Many smart frameworks such as Django, Flask, Laravel provides out of the box solutions to filter the data, which covers almost all needs to separate data based on column values.
When it comes to Geospatial data, we expect to filter data based on their location property instead of metadata. This is where things get complicated, if you are using framework that doesn't have package, library built to handle such use cases, you are likely to be dependent on either database or any external package to handle it.

Fortunately Geodjango[https://docs.djangoproject.com/en/4.0/ref/contrib/gis/] (Django's extension) allows us to create databases which understands geometry and can process it[https://docs.djangoproject.com/en/4.0/ref/contrib/gis/geoquerysets/#gis-queryset-api-reference]. It also provides support to write APIs using Rest Framework extension [https://pypi.org/project/djangorestframework-gis/] which takes this to next level allowing user to output the data in various formats, creating paginations inside geojson, create TMSTileFilters, etc.

In this talk we'll scratch the surface of this python package and see how to build basic CRUD APIs to push, pull GIS data along with filtering it to the PostgreSQL database