Estimation and Error Analysis of Woody Canopy Leaf Area Density Profiles Using 3-D Airborne and Ground-Based Scanning Lidar Remote-Sensing Techniques
Estimation and Error Analysis of Woody Canopy Leaf Area Density Profiles Using 3-D Airborne and Ground-Based Scanning Lidar Remote-Sensing Techniques
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DOI：
10.1109/tgrs.2009.2038372
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发表时间：
2010-05-01
影响因子：
8.2
通讯作者：
Omasa, Kenji
中科院分区：
文献类型：
--
作者：
Hosoi, Fumiki;Nakai, Yohei;Omasa, Kenji
通过结合机载和便携式地面光探测和测距（激光雷达）数据，并使用基于体素的冠层剖面法，估算了日本榉树冠层叶面积密度（LAD）的垂直剖面。由两种类型的激光雷达获得的轮廓相互补充，消除了盲区，并产生比单独使用每种类型的激光雷达获得的更准确的LAD轮廓。在综合结果中，对于4 ~ 32 m（2）的地面面积，LAD的平均绝对误差（MAE）在0.20 ~ 0.42 m（2）m（-3）之间，叶面积指数（LAI）的平均绝对百分比误差（MAPE）在22.3%~ 27.2%之间。结合激光雷达的光束设置和光束衰减因子，提出了一种激光光束覆盖指数Ω。该指数具有普遍适用性，可以解释使用不同类型的激光雷达和不同波束设置的LAD测量的LAD估计误差。部分LAD配置文件被低估，即使从两个激光雷达的数据相结合的插值使用高斯函数。对于16 m2和32 m2的地面面积，插值得到了更好的结果; LAD的MAE分别为0.17和0.11 m2 m-3，LAI的MAE分别为8.0%和9.4%。该方法改进了激光雷达的LAD估计，并适用于阔叶林。指数欧米茄进行了测试，对一个实际的树冠情况下，可以用来确定适当的激光雷达测量设置时，从不同来源的激光雷达数据相结合，以估计LAD配置文件。
Vertical profiles of the leaf area density (LAD) of a Japanese zelkova canopy were estimated by combining airborne and portable ground-based light detection and ranging (lidar) data and using a voxel-based canopy profiling method. The profiles obtained by the two types of lidars complemented each other, eliminating blind regions and yielding more accurate LAD profiles than could be obtained by using each type of lidar alone. In the combined results, the mean absolute errors (MAEs) of LAD ranged from 0.20 to 0.42 m(2) m(-3), and the mean absolute percentage errors (MAPEs) of the leaf area index (LAI) ranged from 22.3% to 27.2%, for ground areas from 4 to 32 m(2), respectively. A laser beam coverage index Omega incorporating the lidar's beam settings and a beam attenuation factor was proposed. This index showed general applicability to explain the LAD estimation error for LAD measurements using different types of lidars and with different beam settings. Parts of the LAD profiles that were underestimated even when data from both lidars were combined were interpolated by using a Gaussian function. The interpolation yielded improved results for ground areas of 16 and 32 m2; the respective MAEs of LAD were 0.17 and 0.11 m(2) m(-3), and the respective MAPEs of LAI were 8.0% and 9.4%. The proposed method improves lidar-derived LAD estimation and is adapted to broadleaved canopies. The index Omega was tested against an actual canopy scenario and could be used to determine appropriate lidar measurement settings when data from different sources of lidar data are combined to estimate LAD profiles.