Assessing and correcting topographic effects on forest canopy height retrieval using airborne LiDAR data.
Assessing and correcting topographic effects on forest canopy height retrieval using airborne LiDAR data.
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使用机载 LiDAR 数据评估和校正地形对森林冠层高度反演的影响
DOI：
10.3390/s150612133
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发表时间：
2015-05-26
期刊：
影响因子：
--
通讯作者：
Zhu J
中科院分区：
文献类型：
--
作者：
Duan Z;Zhao D;Zeng Y;Zhao Y;Wu B;Zhu J
地形对基于机载光探测和测距（LiDAR）数据的森林冠层高度检索有很大影响。本文提出了一种基于个体树冠分割的地形引起的偏差校正方法。根据数字正射影像图 (DOM) 中孤立的单棵树的树冠边界提取单棵树的点云。归一化冠层高度是通过从点云高程中减去重心高程来计算的。首先，通过对DOM进行分割获得个体树冠边界。其次，根据边界提取各个树木的点云。第三，通过多尺度曲率分类算法对点云进行分类，得到精确的DEM。最后，应用高度加权校正方法来校正拓扑效应。该方法应用于华南地区采集的LiDAR数据，并通过41个外业调查样地测试了其有效性。结果表明，地形对单株树木的树冠高度有影响，树干的下坡侧升高，上坡侧降低。这进一步影响了单棵树的位置和树冠的提取。坡度梯度与总回波中高差大于 0.3、0.5 和 0.8 m 的回波比例之间存在很强的相关性，决定系数 R2 分别为 0.83、0.76 和 0.60（n = 41）。
Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs). Normalized canopy height was calculated by subtracting the elevation of centres of gravity from the elevation of point cloud. First, individual tree crown boundaries are obtained by carrying out segmentation on the DOM. Second, point clouds of the individual trees are extracted based on the boundaries. Third, precise DEM is derived from the point cloud which is classified by a multi-scale curvature classification algorithm. Finally, a height weighted correction method is applied to correct the topological effects. The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots. The results show that the terrain impacts the canopy height of individual trees in that the downslope side of the tree trunk is elevated and the upslope side is depressed. This further affects the extraction of the location and crown of individual trees. A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively.