Python and Jupyter notebooks implementing workflows to generate wall-to-wall forest attribute maps (e.g., above ground biomass, canopy height and cover) at 30-meter resolution derived from spaceborne remote sensing data.
canopy_height_maps_GEDI_Sentinel_workflow.ipynb - This jupyter notebook builds a wall-to-wall forest canopy height map by fusing NASA GEDI, Sentinel-1 RTC SAR, Sentinel-2 L2A Optical and COP30 DEM.
OpenForest4D is funded by NSF awards 2409885, 2409886 & 2409887.