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Classification of Global Forests for IPCC Aboveground Biomass Tier 1 Estimates, 2020

Overview

DOIhttps://doi.org/10.3334/ORNLDAAC/2345
Version1
Project
Published2024-06-12
Usage26 downloads

Description

This dataset provides classes of global forests delineated by status/condition in 2020 at approximately 30-m resolution. The data support generating Tier 1 estimates for Aboveground dry woody Biomass Density (AGBD) in natural forests in the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Forest classes include primary, young secondary (<=20 years), and old secondary forests (>20 years). Classification was based on a Boolean combination of a suite of existing Earth Observation (EO) products of forest tree cover, height, age, and land use classification layers representing years 2000 to 2020. This forest status/condition classification prioritizes the reduction of potential errors of commission in the delineations by minimizing the inclusion of ambiguous pixels. Hence, it provides a conservative estimate of global forest area, identifying approximately 3.26 billion ha of forests worldwide. The classification was created on the collaborative open-science cloud-computing system, the ESA-NASA Multi-mission Analysis and Algorithm Platform (MAAP). The data are provided in cloud-optimized GeoTIFF format.

Science Keywords

  • BIOSPHERE
  • VEGETATION
  • BIOMASS
  • BIOSPHERE
  • ECOSYSTEMS
  • TERRESTRIAL ECOSYSTEMS
  • FORESTS
  • LAND SURFACE
  • LAND USE/LAND COVER
  • LAND USE/LAND COVER CLASSIFICATION

Data Use and Citation

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Crosscite Citation Formatter
Hunka, N., L. Duncanson, J. Armston, R.O. Dubayah, S.P. Healey, M. Santoro, P. May, A. Araza, C. Bourgain, P.M. Montesano, C.S. Neigh, H. Grantham, V. Potapov, S. Turubanova, A. Tyukavina, J. Richter, N. Harris, M. Urbazaev, A. Pascual, D. Requena Suarez, M. Herold, B. Poulter, S.N. Wilson, G. Grassi, S. Federici, M.J. Sanz Sanchez, and J. Melo. 2024. Classification of Global Forests for IPCC Aboveground Biomass Tier 1 Estimates, 2020. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2345

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_Global_Forest_Age.pdf