Accessing and using data cubes: spatial overlay, visualization and modeling – Python tutorial
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| Title | Accessing and using data cubes: spatial overlay, visualization and modeling – Python tutorial |
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| Number of Parts | 17 |
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| License | 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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| Production Place | Wageningen |
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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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