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Global Ecosystem Dynamics Investigation (GEDI) Canopy Height Maps
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My GEDI Map Jobs
Workflow estimates canopy height using Machine Learning and fusion of GEDI L2A Elevation and Height Metrics Data (Training Labels), Sentinel-2 L2A (Optical Imagery), Sentinel-1 Radiometrically Terrain Corrected (SAR Imagery) and Digital Elevation Model datasets (e.g. Copernicus GLO-30).
GEDI Footprints Collection Temporal Extents:
Start Date
End Date
Sentinel-1, Sentinel-2 Temporal Extents:
Start Date
End Date
Sentinel-2 L2A Cloud Threshold:
10%
15%
20% (Default)
50%
DEM Dataset:
Copernicus GLO-30
Machine Learning Algorithm:
Random Forest Regression
Histogram Gradient Boosting
Generate Additional Source Data Visualizations (optional)
Generate Canopy maps:
2022 (Default)
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Process