期刊
REMOTE SENSING OF ENVIRONMENT
卷 115, 期 12, 页码 3770-3774出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2011.07.019
关键词
Aboveground biomass; Crown radius; Light detection and ranging; Tree allometry; Tropical forest carbon stocks; Spatial autocorrelation
资金
- Gordon and Betty Moore Foundation
- John D. and Catherine T. MacArthur Foundation
- HSBC Climate Partnership
- National Science Foundation [DEB-0640386, DEB-0425651, DEB-0346488, DEB-0129874, DEB-00753102, DEB-9909347, DEB-9615226, DEB-9405933, DEB-9221033, DEB-9100058, DEB-8906869, DEB-8605042, DEB-8206992, DEB-7922197]
- Center for Tropical Forest Science
- Smithsonian Tropical Research Institute
- Mellon Foundation
- Celera Foundation
Airborne LiDAR is increasingly used to map carbon stocks in tropical forests, but our understanding of mapping errors is constrained by the spatial resolution (i.e., plot size) used to calibrate LiDAR with field data (typically 0.1-0.36 ha). Reported LiDAR errors range from 17 to 40 Mg C ha(-1), but should be lower at coarser resolutions because relative errors are expected to scale with (plot area)(-1/2). We tested this prediction empirically using a 50-ha plot with mapped trees, allowing an assessment of LiDAR prediction errors at multiple spatial resolutions. We found that errors scaled approximately as expected, declining by 38% (compared to 40% predicted from theory) from 0.36- to 1-ha resolution. We further reduced errors at all spatial resolutions by accounting for tree crowns that are bisected by plot edges (not typically done in forestry), and collectively show that airborne LiDAR can map carbon stocks with 10% error at 1-ha resolution a level comparable to the use of field plots alone. (C) 2011 Elsevier Inc. All rights reserved.
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