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Intergovernmental Panel on Climate Change (IPCC) Tier 1 forest biomass estimates from Earth Observation.

Authors :
Hunka, Neha
Duncanson, Laura
Armston, John
Dubayah, Ralph
Healey, Sean P.
Santoro, Maurizio
May, Paul
Araza, Arnan
Bourgoin, Clement
Montesano, Paul M.
Neigh, Christopher S. R.
Grantham, Hedley
Potapov, Peter
Turubanova, Svetlana
Tyukavina, Alexandra
Richter, Jessica
Harris, Nancy
Urbazaev, Mikhail
Pascual, Adrián
Suarez, Daniela Requena
Source :
Scientific Data; 10/14/2024, Vol. 11 Issue 1, p1-19, 19p
Publication Year :
2024

Abstract

Aboveground biomass density (AGBD) estimates from Earth Observation (EO) can be presented with the consistency standards mandated by United Nations Framework Convention on Climate Change (UNFCCC). This article delivers AGBD estimates, in the format of Intergovernmental Panel on Climate Change (IPCC) Tier 1 values for natural forests, sourced from National Aeronautics and Space Administration's (NASA's) Global Ecosystem Dynamics Investigation (GEDI) and Ice, Cloud and land Elevation Satellite (ICESat-2), and European Space Agency's (ESA's) Climate Change Initiative (CCI). It also provides the underlying classification used by the IPCC as geospatial layers, delineating global forests by ecozones, continents and status (primary, young (≤20 years) and old secondary (>20 years)). The approaches leverage complementary strengths of various EO-derived datasets that are compiled in an open-science framework through the Multi-mission Algorithm and Analysis Platform (MAAP). This transparency and flexibility enables the adoption of any new incoming datasets in the framework in the future. The EO-based AGBD estimates are expected to be an independent contribution to the IPCC Emission Factors Database in support of UNFCCC processes, and the forest classification expected to support the generation of other policy-relevant datasets while reflecting ongoing shifts in global forests with climate change. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20524463
Volume :
11
Issue :
1
Database :
Complementary Index
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
180253629
Full Text :
https://doi.org/10.1038/s41597-024-03930-9