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Estimation of clumping index and LAI from Terrestrial LiDAR data

机译:从地面LiDAR数据估算聚集指数和LAI

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In this study, clumping index and effective leaf area index (LAI) are estimated from Terrestrial Laser Scanner (TLS) data. Integrating vertical and tilt scanning from Terrestrial laser scanner, accounting zenith angle and path length two factors, discrete directional canopy gap fraction could be calculated and effective LAI could be estimated from canopy gap fraction. Finally, the clumping index and effective LAI are estimated from Terrestrial LiDAR and the results are validated with digital hemispherical photography (DHP). The results show that the regression value R2 of the clumping index, effective LAI and LAI from TLS and DHP is 0.863, 0.741 and 0.563, respectively. This experiment highlights the potential Terrestrial LiDAR for measuring forest structure parameters in plot and could be as a new tool for validating retrieval of these parameters.
机译:在这项研究中,丛集指数和有效叶面积指数(LAI)是根据陆地激光扫描仪(TLS)数据估算的。结合地面激光扫描仪的垂直和倾斜扫描,考虑天顶角和光程长度两个因素,可以计算出离散的定向冠层间隙分数,并可以根据冠层间隙分数估算有效的LAI。最后,从地面LiDAR估计了聚集指数和有效LAI,并用数字半球摄影(DHP)验证了结果。结果表明,聚集指数,有效LAI和LAI分别来自TLS和DHP的回归值R2分别为0.863、0.741和0.563。该实验突出了潜在的地面LiDAR,可用于测量样地中的森林结构参数,并且可以作为验证这些参数检索的新工具。

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