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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Strengths and limitations of assessing forest density and spatial configuration with aerial LiDAR
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Strengths and limitations of assessing forest density and spatial configuration with aerial LiDAR

机译:空中LiDAR评估森林密度和空间配置的优缺点

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摘要

Changes in the structural state of forests of the semi-arid U.S.A., such as an increase in tree density, are widely believed to be leading to an ecological crisis, but accurate methods of quantifying forest density and configuration are lacking at landscape scales. An individual tree canopy (ITC) method based on aerial LiDAR has been developed to assess forest structure by estimating the density and spatial configuration of trees in four different height classes. The method has been tested against field measured forest inventory data from two geographically distinct forests with independent LiDAR acquisitions. The results show two distinct patterns: accurate, unbiased density estimates for trees taller than 20. m, and underestimation of density in trees less than 20. m tall. The underestimation of smaller trees is suggested to be a limitation of LiDAR remote sensing. Ecological applications of the method are demonstrated through landscape metrics analysis of density and configuration rasters.
机译:人们普遍认为,半干旱的美国森林结构状态的变化(例如树木密度的增加)会导致生态危机,但是在景观尺度上缺乏准确的量化森林密度和形态的方法。已经开发了一种基于空中LiDAR的个体树冠(ITC)方法,通过估算四种不同高度级别的树木的密度和空间配置来评估森林结构。已针对来自具有独立LiDAR采集的两个地理上不同的森林的实地测得的森林清单数据测试了该方法。结果显示了两种不同的模式:对高于20 m的树木进行准确,无偏的密度估计,以及对小于20 m的树木进行低密度估计。较小树木的低估被认为是LiDAR遥感的局限性。通过对密度和配置栅格进行景观度量分析,证明了该方法的生态应用。

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