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

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.

Resources

Name Format Description Link
21 Search results for publications that cite this dataset by its DOI. https://scholar.google.com/scholar?q=10.3334%2FORNLDAAC%2F1764
21 ORNL DAAC Data Set Documentation https://daac.ornl.gov/CMS/guides/Sonoma_County_Forest_AGB.html
21 This link allows direct data access via Earthdata login https://daac.ornl.gov/cms/Sonoma_County_Forest_AGB/
21 Data set Landing Page DOI URL https://doi.org/10.3334/ORNLDAAC/1764
33 CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013: Sonoma_County_Forest_AGB.pdf https://data.ornldaac.earthdata.nasa.gov/public/cms/Sonoma_County_Forest_AGB/comp/Sonoma_County_Forest_AGB.pdf
34 Estimated aboveground biomass (Mg/ha) for Sonoma County at 30-m spatial resolution with the 5th-95th percentile range and the standard deviation (SD) of per-pixel biomass estimates shown in the top left and bottom left, respectively. https://daac.ornl.gov/CMS/guides/Sonoma_County_Forest_AGB_Fig1.png

Tags

  • biosphere
  • vegetation
  • earth-science

Topics

Categories