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UID:pretalx-foss4g-2023-QUBWB8@talks.osgeo.org
DTSTART;TZID=CET:20230628T151000
DTEND;TZID=CET: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:20260517T144432Z
LOCATION:UBT D / N113 - Second Floor
SUMMARY:OpenDataCube Fast Deploy using Docker (Fast Cubing) - J. R. Cedeno 
 Jimenez
URL:https://talks.osgeo.org/foss4g-2023/talk/QUBWB8/
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