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Biomass/Remote Sensing dataset: 30m resolution tidal marsh biomass samples and remote sensing data for six regions in the conterminous United States


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Byrd, K.B., Ballanti, L.R., Thomas, N.M., Nguyen, D.K., Holmquist, J.R., Simard, M., Windham-Myers, L., Schile, L.M., Parker, V.T., Callaway, J.C., Vasey, M.C., Herbert, E.R., Davis, M.J., Woo, I., De La Cruz, S., Kroeger, K.D., Gonneea, M.E., O'Keefe Suttles, J., Megonigal, J.P., Lu, M., McFarland, E.K., Brooks, H.E.A., Drake, B.G., Peresta, G., Peresta, A., Troxler, T., and Castaneda-Moya, E., 2017, Tidal marsh biomass field plot and remote sensing datasets for six regions in the conterminous United States (ver. 2.0, June, 2020): U.S. Geological Survey data release,


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. We tested how plant [...]


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Biomass_RemoteSensingDataset_Final_version2.csv 1.27 MB text/csv


Data were obtained in order to assess how plant community composition and vegetation structure differences across estuaries influence model development, and whether data from multiple sensors, in particular Sentinel-1 C-band synthetic aperture radar and Landsat, can improve model performance.

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