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This study is concerned with biomassinduced elevation bias of the digital elevation model (DEM) derived using Synthetic Aperture Radar Interferometry. A linear dependency between this bias and biomass density allows for its use to assess the degree of depletion of forest stands. The advantage of this measure is its sensitivity to both the horizontal distribution of forest and vertical properties of forest including canopy density. This bias may be estimated by subtracting the bareground DEM from the vegetationincluded DEM. Tests were conducted using the C and Xband SRTM DEMs. It was found that both the C and Xband DEMs represent similar surfaces within the vegetation layer. With this discovery in mind, one may infer that gaps in the canopy cover are the major contributor to the magnitude of the vegetationinduced elevation bias. Also, experiments on the sensitivity of the Lband PALSAR data to biomass are presented. The book may be useful to remote sensing students, forest ecologists and other professionals interested in forest studies as well as decision makers.
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birth defects, or other reproductive harm.
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