Gridded GEDI-Fusion Forest Structure Metrics across Six Western US States, 2016-2020

The metrics characterize canopy height, strata densities, and canopy cover. The data were derived using random forest modeling and prediction frameworks.

The models created were also hindcasted using 2019 and 2020 GEDI footprints back to 2016 on annual time steps leveraging continuous Landsat spectral and disturbance information, Sentinel-1 backscatter metrics and ratios, topographic information, and bioclimatic variables. Machine learning data fusion approaches were used to scale-up structure information provided by the novel space-borne Global Ecosystems Dynamics Investigation (GEDI) waveform lidar sensor to continuous extents using additional satellite-based continuous earth observation data.