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

Description

This dataset provides eight GEDI forest structure metrics relevant to wildlife habitat modeling and biodiversity assessments at 30-m resolutions across Washington, Oregon, Idaho, Montana, Wyoming, and Colorado. 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. GEDI provides a consistent sample of forest structure information at 25-m diameter footprints at near-global extents, providing a valuable source of reference information to drive continuous mapping efforts.

Resources

Name Format Description Link
Download this dataset HTML This link allows direct data access via Earthdata login Open resource
Get a related visualization PNG The browse image displays the 2020 GEDI-fusion relative height 98 (RH98) predicted map product which represents a canopy height measure across the six-state study area at a 30-m spatial resolution. Open resource
View documentation related to this dataset HTML ORNL DAAC Data Set Documentation Open resource
View documentation related to this dataset PDF Gridded GEDI-Fusion Forest Structure Metrics across Six Western US States, 2016-2020: GEDI_Fusion_Structure.pdf Open resource
This dataset's landing page HTML Data set Landing Page DOI URL Open resource
The dataset's project home page HTML GEDI Project Site Open resource
Google Scholar search results HTML Search results for publications that cite this dataset by its DOI. Open resource

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