中文摘要：

激光点云数据以其详尽、高精度的三维信息,在森林参数估算、精确重建植物形态结构三维模型方面具有特殊优势。为进一步提高三维模型精度,综合集成多种算法,在改进现有PC2Tree软件基础上,基于点云数据进行树木三维重建。首先根据树木局部点云的主方向相似度和局部点云轴向分布密度分离枝干与树叶;其次采取水平集和最小二乘法提取枝干部分的骨架点,通过下采样方法提取冠层部分的特征点;最后根据骨架点和特征点拓扑结构重构树木三维模型。以樟树为例,分析枝叶分割精度,自动分割与手动分割结果相近;以无叶的鸡蛋花树为例,分析重建模型精度,模型主枝长度相对误差范围集中在0~8.0%,半径相对误差范围集中在0~10%;枝条重建过程避免了噪声点的干扰,对噪声点具有一定的不敏感性;重建三维模型与原始点云吻合度高,基本解决了冠层内部枝干遮挡严重带来的三维建模困难的问题;依据模型提取树高、冠幅、胸径、体积等参数,增加了重建模型的应用范围。

英文摘要：

Point cloud obtained from terrestrial laser scanner contains detailed,high precision threedimensional（ 3D） surface coordinates,which is of special importance for forest parameter estimation and accurate reconstruction of plant model. An improved method for tree branching structure reconstruction was proposed based on the fact that a clean partition of branches and leaves form tree point cloud was very difficult if it was not impossible. Firstly,principal direction at each point was estimated with chord and normal vectors（ CAN）,and point cloud from the branches and leaves was separated by using both the similarity of principal direction between neighboring points and distribution density of points. Secondly,skeleton nodes and corresponding radii were computed from main branches by using level sets and least square method. For the leaves,the crown volume was divided into equal-sized voxels,all the points in a voxel were represented by the voxel ＇s centroid,and all centroid points formed feature points of the crown. Finally,tree model was reconstructed by cylinder fitting based on the topology of skeleton nodes and feature points. Segmentation results accuracy analysis and four different tree species model reconstruction examples were introduced. Segmentation accuracy analysis and model reconstruction quality evaluation showed that the approach was robust and insensitive to noise; the reconstructed tree models were in good agreement with the point cloud. The method was also able to extract structural parameters,including tree height,diameter at breast height（ DBH） and volume parameters.