TY - GEN T1 - CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013 AU - Duncanson, L. AU - Dubayah, R.O. AU - Armston, J. AU - Liang, M. AU - Arthur, A. AU - Minor, D. DO - 10.3334/ORNLDAAC/1764 UR - https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1764 AB - This data set provides estimates of above-ground woody biomass and uncertainty at 30-m spatial resolution for Sonoma County, California, USA, for the nominal year 2013. Biomass estimates, megagrams of biomass per hectare (Mg/ha), were generated using a combination of airborne LiDAR data and field plot measurements with a parametric modeling approach. The relationship between field estimated and airborne LiDAR estimated aboveground biomass density is represented as a parametric model that predicts biomass as a function of canopy cover and 50th percentile and 90th percentile LiDAR heights at a 30-m resolution. To estimate uncertainty, the biomass model was re-fit 1,000 times through a sampling of the variance-covariance matrix of the fitted parametric model. This produced 1,000 estimates of biomass per pixel. The 5th and 95th percentiles, and the standard deviation of these pixel biomass estimates, were calculated. KW - BIOSPHERE > VEGETATION > BIOMASS KW - BIOSPHERE > VEGETATION > CANOPY CHARACTERISTICS KW - BIOSPHERE > VEGETATION > VEGETATION COVER KW - FIELD SURVEYS > STEEL MEASURING TAPE KW - CESSNA SINGLE-ENGINE AIRCRAFT > BACKSCATTER LIDAR KW - aboveground biomass KW - canopy cover KW - FIA plots KW - parametric model KW - tall forest PY - 2020 PB - ORNL Distributed Active Archive Center LA - en SN - https://daac.ornl.gov/cgi-bin/dataset_lister.pl?p=33 ER -