Filters: Tags: wetlands (X) > partyWithName: Ecosystems (X) > Categories: Data Release - Revised (X)
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for Suisun marsh using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (6912 points, collected across public and private land in 2018), Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image (June 2018), a 1 m lidar DEM from September 2018, and a 1 m canopy surface model were used to generate models of predicted bias across the...
Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). To meet this objective we developed the first national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA....
Categories: Data,
Data Release - Revised;
Tags: C-band synthetic aperture radar,
Cape Cod,
Carbon sequestration,
Chesapeake Bay,
Everglades National Park,
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