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CMS: Forest Carbon Stocks, Emissions, and Net Flux for the Conterminous US: 2005-2010

Overview

DOIhttps://doi.org/10.3334/ORNLDAAC/1313
Version1
Projects
Published2016-05-11
Usage3265 downloads
Citations5 publications cited this dataset

Description

This data set provides maps of estimated carbon in forests of the 48 continental states of the US for the years 2005-2010. Carbon (termed committed carbon) stocks were estimated for forest aboveground biomass, belowground biomass, standing dead stems, and litter for the year 2005. Carbon emissions were estimated from land use conversion to agriculture, insect damage, logging, wind, and weather events in the forests for the years 2006 - 2010. Committed net carbon flux was estimated as the sum of carbon emissions and sequestration. The maps are provided at 100-m spatial resolution in GeoTIFF format. Average annual carbon estimates, by US county, for (1) emissions for the multiple disturbance sources, (2) sequestration, and (3) the committed net carbon flux are provided in an ESRI shapefile.

Science Keywords

  • HUMAN DIMENSIONS
  • NATURAL HAZARDS
  • DROUGHTS
  • LAND SURFACE
  • LAND USE/LAND COVER
  • BIOSPHERE
  • VEGETATION
  • BIOMASS
  • BIOSPHERE
  • VEGETATION
  • LITTER CHARACTERISTICS
  • BIOSPHERE
  • ECOSYSTEMS
  • TERRESTRIAL ECOSYSTEMS
  • FORESTS
  • BIOSPHERE
  • VEGETATION
  • CARBON

Data Use and Citation

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Crosscite Citation Formatter
Hagen, S., N. Harris, S.S. Saatchi, T. Pearson, C.W. Woodall, S. Ganguly, G.M. Domke, B.H. Braswell, B.F. Walters, J.C. Jenkins, S. Brown, W.A. Salas, A. Fore, Y. Yu, R.R. Nemani, C. Ipsan, and K.R. Brown. 2016. CMS: Forest Carbon Stocks, Emissions, and Net Flux for the Conterminous US: 2005-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1313

This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use Policy. See our Data Use and Citation Policy for more information.

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Companion Files

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Dataset has 1 companion files.

  • CMS_Forest_Carbon_Fluxes.pdf

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Additional Resources

TypeTitle
WebinarIntroduction to Geospatial Analysis in R