a macroecological analysis of sera derived forest heights and implications for forest volume remote sensingmacroecological分析血清中森林高度和体积影响森林遥感.pdfVIP

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing 1 2 3 4 Matthew Brolly *, Iain H. Woodhouse , Karl J. Niklas , Sean T. Hammond 1 Department of Geographical Sciences, University of Maryland, College Park, Maryland, United States of America, 2 School of GeoSciences, The University of Edinburgh, Edinburgh, United Kingdom, 3 Department of Plant Biology, Cornell University, Ithaca, New York, United States of America, 4 Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, United States of America Abstract Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey’s height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey’s, exhibit little consistent correlation with forest volume across modeled conditions. The implic