A Lidar Point Cloud Based Procedure for Vertical Canopy Structure Analysis And 3D Single Tree Modelling in Forest.
A Lidar Point Cloud Based Procedure for Vertical Canopy Structure Analysis And 3D Single Tree Modelling in Forest.
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DOI：
10.3390/s8063938
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发表时间：
2008-06-12
期刊：
影响因子：
--
通讯作者：
Koch B
中科院分区：
文献类型：
--
作者：
Wang Y;Weinacker H;Koch B
本文提出了一种基于激光雷达点云的垂直冠层结构分析和单木三维建模方法。整个研究区域被光栅网分割成小的研究单元。对于每个单元，从原始激光雷达原始点云生成其点高度表示地面对象的绝对高度的归一化点云。通过对归一化原始点高度分布概率的统计分析，检测出主要树冠层及其高度范围。对于单个树木的3D建模，不仅从顶部冠层而且从子冠层检测和描绘单个树木。归一化点被重新采样到局部体素空间中。然后相对于体素空间生成在不同高度水平处的一系列水平2D投影图像。从投影图像中检测树冠区域。然后，通过在不同高度水平上的所有树冠区域的前序森林遍历过程来提取单个树木。最后，三维树冠模型的提取的个体树木重建。通过对树冠三维模型的进一步分析，可以得到不同高度层次的树冠高度范围、树冠体积和树冠轮廓等重要参数。
A procedure for both vertical canopy structure analysis and 3D single tree modelling based on Lidar point cloud is presented in this paper. The whole area of research is segmented into small study cells by a raster net. For each cell, a normalized point cloud whose point heights represent the absolute heights of the ground objects is generated from the original Lidar raw point cloud. The main tree canopy layers and the height ranges of the layers are detected according to a statistical analysis of the height distribution probability of the normalized raw points. For the 3D modelling of individual trees, individual trees are detected and delineated not only from the top canopy layer but also from the sub canopy layer. The normalized points are resampled into a local voxel space. A series of horizontal 2D projection images at the different height levels are then generated respect to the voxel space. Tree crown regions are detected from the projection images. Individual trees are then extracted by means of a pre-order forest traversal process through all the tree crown regions at the different height levels. Finally, 3D tree crown models of the extracted individual trees are reconstructed. With further analyses on the 3D models of individual tree crowns, important parameters such as crown height range, crown volume and crown contours at the different height levels can be derived.
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影响因子：
2.6
作者：
Lim, K;Treitz, P;Green, J
通讯作者：
Green, J
影响因子：
13.5
作者：
Lefsky, MA;Cohen, WB;Harding, D
通讯作者：
Harding, D
影响因子：
13.5
作者：
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通讯作者：
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影响因子：
13.5
作者：
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通讯作者：
Næsset, E
影响因子：
1.3
作者：
Koch, B;Heyder, U;Weinacker, H
通讯作者：
Weinacker, H