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Extracting above-ground biomass in areas corresponding to FAO’s definition of 'Forest' using open geospatial data: Results for ASEAN

Authors :
B. A. Johnson
C. Umemiya
T. Tadono
M. Harada
O. Ochiai
K. Hamamoto
Source :
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-5-2024, Pp 89-94 (2024)
Publication Year :
2024
Publisher :
Copernicus Publications, 2024.

Abstract

In this study, we extracted above-ground biomass (AGB) information for forests in different ecological zones of ASEAN (Association of Southeast Asian Nations) by integrating freely-available global AGB, forest, and ecological zone map products. Our objective was to assess the suitability of the data and proposed approach for national reporting of forest carbon stocks. We compared the satellite-derived AGB values of forests in ASEAN countries with the corresponding AGB values provided by the Intergovernmental Panel for Climate Change (IPCC) in their Guidelines for National Greenhouse Gas Inventories (which are derived from ground-based measurements of forest AGB). For this, we used a map integration approach that ensures that AGB data is extracted from areas corresponding to the Food and Agricultural Association (FAO) of the UN’s definitions of “forest” and “ecological zones”, as recommended by the relevant IPCC Guidelines. We found that the average satellite-derived AGB values extracted for each ecological zone were generally lower than the values for natural forests (but higher than the values for plantation forests) provided in the IPCC Guidelines. Further investigation showed that this was partly due to the presence of many erroneously low AGB values for forests in the extracted results, caused by errors in the data masks applied to the original global AGB map, including masks of cropland, urban areas, bare soil, and water bodies. Our findings suggest that further processing is necessary before using satellite-derived data for national reporting of forest carbon stocks in ASEAN countries, and we give a few possible options for this.

Details

Language :
English
ISSN :
21949042 and 21949050
Volume :
X-5-2024
Database :
Directory of Open Access Journals
Journal :
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.77e6846bf1bf442ead46e907537acb2a
Document Type :
article
Full Text :
https://doi.org/10.5194/isprs-annals-X-5-2024-89-2024