期刊
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
卷 82, 期 4, 页码 271-281出版社
AMER SOC PHOTOGRAMMETRY
DOI: 10.14358/PERS.82.4.271
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资金
- USGS Mendenhall, Land Remote Sensing and Land Change Science programs
Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R-2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14 Mg ha(-1) across all woodland and forest species. Land-sat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha(-1). Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States.
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