期刊
ENVIRONMENTAL RESEARCH LETTERS
卷 6, 期 4, 页码 -出版社
IOP Publishing Ltd
DOI: 10.1088/1748-9326/6/4/049001
关键词
aboveground biomass; Africa; AGB; carbon; GLAS; LiDAR; MODIS; random forest; regression tree; remote sensing; savanna; tropical forest
资金
- Natural Environment Research Council [NE/D005035/1, NE/I021217/1, NE/D005469/1, NE/D000300/1, ceh010023] Funding Source: researchfish
- NERC [NE/I021217/1, NE/D005035/1, NE/D005469/1] Funding Source: UKRI
We present a critical evaluation of the above-ground biomass (AGB) map of Africa published in this journal by Baccini et al (2008 Environ. Res. Lett. 3 045011). We first test their map against an independent dataset of 1154 scientific inventory plots from 16 African countries, and find only weak correspondence between our field plots and the AGB value given for the surrounding 1 km pixel by Baccini et al. Separating our field data using a continental landcover classification suggests that the Baccini et al map underestimates the AGB of forests and woodlands, while overestimating the AGB of savannas and grasslands. Secondly, we compare their map to 216 000 x 0.25 ha spaceborne LiDAR footprints. A comparison between Lorey's height (basal-area-weighted average height) derived from the LiDAR data for 1 km pixels containing at least five LiDAR footprints again does not support the hypothesis that the Baccini et al map is accurate, and suggests that it significantly underestimates the AGB of higher AGB areas. We conclude that this is due to the unsuitability of some of the field data used by Baccini et al to create their map, and overfitting in their model, resulting in low accuracies outside the small areas from which their field data are drawn.
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