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CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013

Overview

DOIhttps://doi.org/10.3334/ORNLDAAC/1764
Version1
Project
Published2020-06-26
Updated2020-06-26
Usage3 downloads

Description

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.

Science Keywords

  • BIOSPHERE
  • VEGETATION
  • VEGETATION COVER
  • BIOSPHERE
  • VEGETATION
  • CANOPY CHARACTERISTICS
  • BIOSPHERE
  • VEGETATION
  • BIOMASS

Data Use and Citation

This dataset is openly shared, without restriction, in accordance with the NASA Data and Information Policy.

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Crosscite Citation Formatter
Duncanson, L., R.O. Dubayah, J. Armston, M. Liang, A. Arthur, and D. Minor. 2020. CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1764

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Dataset has 1 companion files.

  • Sonoma_County_Forest_AGB.pdf