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Accessing and using data cubes: spatial overlay, visualization and modeling – Python tutorial

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Logo of OpenGeoHub FoundationOpenGeoHub Foundation
 Parente, Leandro

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Title
Accessing and using data cubes: spatial overlay, visualization and modeling – Python tutorial
Title of Series
Number of Parts
17
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License
CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Release Date2022
LanguageEnglish
Producer
Production PlaceWageningen

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Abstract
In this training session you will learn about the main concepts / aspects related to raster data cubes, cloud-optimized geotiff (COG) and SpatioTemporal Asset Catalog (STAC), working with a practical example in Python. Using the eumap library and the training samples provided in the hackathon, you will perform a complete workflow for spatial predictive mapping, including:  Spacetime overlay (through STAC + COG),  Train a Random Forest classifier (with hyper-parameter optimization),  produce a classification output (also through STAC + COG). All the steps were executed in Google Colab and all the data (points and rasters) accessed directly from the cloud (http://stac.ecodatacube.eu).
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