TY - JOUR
T1 - An above-ground biomass map of African savannahs and woodlands at 25 m resolution derived from ALOS PALSAR
AU - Bouvet, Alexandre
AU - Mermoz, Stéphane
AU - Le Toan, Thuy
AU - Villard, Ludovic
AU - Mathieu, Renaud
AU - Naidoo, Laven
AU - Asner, Gregory P.
N1 - Funding Information:
The authors gratefully acknowledge financial support from CNES (TOSCA program, purchase order BCT_71SC), from ESA (DUE GlobBiomass project, ESA Contract No. 4000113100/14/I-NB) and from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 685761 (EOMonDis project).
Funding Information:
The authors gratefully acknowledge financial support from CNES (TOSCA program, purchase order BCT_71SC), from ESA (DUE GlobBiomass project, ESA Contract No. 4000113100/14/I-NB ) and from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 685761 (EOMonDis project).
Publisher Copyright:
© 2017 The Authors
PY - 2018/3/1
Y1 - 2018/3/1
N2 - Savannahs and woodlands are among the most important biomes in Africa: they cover half of sub-Saharan Africa, provide vital ecosystem services to the rural communities, and play a major part in the carbon budget. Despite their importance and their fragility, they are much less studied than other ecosystems like rainforests. In particular, the distribution and amount of the above-ground woody biomass (AGB) is largely unknown. In this paper, we produce the first continental map of the AGB of African savannahs and woodlands at a resolution of 25 m. The map is built from the 2010 L-band PALSAR mosaic produced by JAXA, along the following steps: a) stratification into wet/dry season areas in order to account for seasonal effects, b) development of a direct model relating the PALSAR backscatter to AGB, with the help of in situ and ancillary data, c) Bayesian inversion of the direct model. A value of AGB and its uncertainty has been assigned to each pixel. This approach allows estimating AGB until 85 Mg·ha− 1 approximately, while dense forests and non-vegetated areas are masked out using the ESA CCI Land Cover dataset. The resulting map is visually compared with existing AGB maps and is validated using a cross-validation approach and a comparison with AGB estimates obtained from LiDAR datasets, leading to an RMSD of 8 to 17 Mg·ha− 1. Finally, carbon stocks for savannahs in Africa and in 50 countries are estimated and compared with estimates by FAO and from AGB maps available over Africa.
AB - Savannahs and woodlands are among the most important biomes in Africa: they cover half of sub-Saharan Africa, provide vital ecosystem services to the rural communities, and play a major part in the carbon budget. Despite their importance and their fragility, they are much less studied than other ecosystems like rainforests. In particular, the distribution and amount of the above-ground woody biomass (AGB) is largely unknown. In this paper, we produce the first continental map of the AGB of African savannahs and woodlands at a resolution of 25 m. The map is built from the 2010 L-band PALSAR mosaic produced by JAXA, along the following steps: a) stratification into wet/dry season areas in order to account for seasonal effects, b) development of a direct model relating the PALSAR backscatter to AGB, with the help of in situ and ancillary data, c) Bayesian inversion of the direct model. A value of AGB and its uncertainty has been assigned to each pixel. This approach allows estimating AGB until 85 Mg·ha− 1 approximately, while dense forests and non-vegetated areas are masked out using the ESA CCI Land Cover dataset. The resulting map is visually compared with existing AGB maps and is validated using a cross-validation approach and a comparison with AGB estimates obtained from LiDAR datasets, leading to an RMSD of 8 to 17 Mg·ha− 1. Finally, carbon stocks for savannahs in Africa and in 50 countries are estimated and compared with estimates by FAO and from AGB maps available over Africa.
KW - Above-ground biomass
KW - Africa
KW - PALSAR
KW - Savannahs
KW - Woodlands
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U2 - 10.1016/j.rse.2017.12.030
DO - 10.1016/j.rse.2017.12.030
M3 - Article
AN - SCOPUS:85039752181
SN - 0034-4257
VL - 206
SP - 156
EP - 173
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
ER -