Description
This dataset provides estimates of aboveground biomass (AGB) and salt marsh extent in the contiguous United States for 2020 and includes all coastal watersheds across the contiguous United States at 10-m resolution. Estimates were generated by XGBoost machine learning regression. Salt marsh extent was classified using an ensemble of XGBoost, random forests, and support vector machines, trained with salt marsh location identified with the National Wetland Inventory (NWI). The data are organized by Hydrologic Unit Code (HUC) 6-digit basin. Within each HUC, the spatial extent of salt marsh and its uncertainty were estimated by machine learning and input data from NWI maps, the National Elevation Dataset, along with Sentinel-1 and Sentinel-2 imagery. Estimates were compared to in situ biomass data from salt marshes in Georgia and Massachusetts. The data are provided in cloud-optimized GeoTIFF format.
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| Get a related visualization | PNG | A visualization from the Chesapeake Bay displaying aboveground biomass and the upper and lower levels of salt marsh extent. Upper extent includes all areas within the lower extent. Background is Sentinel-2 imagery (NIR, G, B) for a section of Deal Island, Maryland. | Open resource |
| View documentation related to this dataset | HTML | ORNL DAAC Data Set Documentation | Open resource |
| Download this dataset | HTML | This link allows direct data access via Earthdata login | Open resource |
| View documentation related to this dataset | Aboveground Biomass Estimates for Salt Marsh for the Contiguous United States, 2020: Salt_Marsh_Biomass_CONUS.pdf | Open resource | |
| This dataset's landing page | HTML | Data set Landing Page DOI URL | Open resource |
| Google Scholar search results | HTML | Search results for publications that cite this dataset by its DOI. | Open resource |