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摘要： 针对亚热带环境条件下森林树高、胸径自动化提取精度较低、单木形态模拟较为困难的问题，提出基于地面激光雷达点云数据提取森林树高、胸径及重建森林场景三维模型的方法。首先采用变尺度地面点识别法获取地面点并构建DEM。然后根据树木主干点云主方向相似度及轴向分布密度分割主干与其他植物器官点云。接着以主干点云为基础，采用迭代最小二乘拟合圆柱的方法自动提取树木位置、胸径；构建点云的八叉树结构，利用体素的空间邻接性实现点云分割，自动提取树高。最后，结合单株植物建模技术，以树根节点为纽带构建样地尺度上的森林场景三维模型。实验结果显示，胸径估测R2为0.996，平均相对误差为2.09%，RMSE为0.66 cm；树高估测R2为0.972，平均相对误差为2.16%，RMSE为0.92 m；所重建的森林场景三维模型可表达森林样地的真实形态。 关键词： 地面激光雷达;  树高;  胸径;  点云分割;  三维重建     Abstract: In view of the low accuracy of Tree Height(TH) and Diameter at Breast Height(DBH) estimation，as well as the difficulty of individual tree modeling in dense forest，a method to extract forest structure parameters(TH and DBH) and reconstruct a Three-Dimensional(3D) model of forest in subtropical environment based on TLS point cloud data is proposed.The first step is to apply a multi-scale method to extract the ground points for the generation of Digital Elevation Model(DEM).Secondly，using similarity of principal direction between neighboring points and distribution density of points，trunk and other plant organs are separated.Next the trunk points are processed to automatically estimate the tree position and DBH by iterative least squares cylinder fitting;the tree height is automatically estimated by using the octree segmentation.Finally，by combining with the technology of individual tree modeling，a plot-scale 3D forest scene has been reconstructed by planting individual tree model on the terrain model iteratively.The results showed that the correlation coefficient of DBH is R2=0.996，and the average relative error was 2.09%，RMSE was 0.66 cm;the correlation coefficient of tree height is R2=0.972，and the average relative error was 2.16% with RMSE of 0.92 m.The plot-scale reconstructed 3D model of the forest can express the true shape of forest.

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