基于点云骨架的单木分枝参数提取研究

地面激光扫描技术在获取树木参数的应用中发挥了重要作用,而图形学算法为实现单木结构参数自动提取提供了可行的方法。本文提出一种基于地面激光扫描数据来获取单木分枝结构参数的方法,应用SkelTre算法对激光扫描仪获取的单木点云数据进行处理得到单木的骨架模型;根据骨架模型邻边的拓扑关系搜索与各个分枝相连接的节点提取分枝结构,计算枝长;在分枝着枝点处以骨架线为轴作横切面,应用凸包算法提取横切面点云外包多边形并计算分枝直径;对枝长和分枝直径的实测值和模型的估计值进行回归分析分别得到二者的对比分析结果,枝长的实测与估计值回归分析结果为Y=1.006X+1.335,显著性值为0.001,分枝直径的回归分析结果为Y=0.923X+0.105,显著性值为0.000。实验结果表明,基于地面激光扫描数据提取骨架模型以获取单木的分枝结构和提取分枝结构参数(如枝长、分枝直径)的方法具有很好的适用性和应用前景。 

Extraction of individual tree branch parameters from skeleton model based on point cloud data

Terrestrial laser scanning technology plays an important role in extracting individual tree parameters. Meanwhile, graphics algorithms provides feasible methods for evaluating structural parameters. In this paper, a method of extracting individual tree structural parameters has been put forward. We extracted individual tree’s skeleton model by SkelTre algorithm. Then branch structure was identified by topological feature of the skeleton model from searching the connection nodes among different branches. We calculated branch length and made the cross-section through the skeleton model at branch connection points. Moreover, convex hull algorithm was used for extracting a plane polygon and calculating branch diameter through the point cloud outsourcing. From the regression analysis between field measurement and model estimated measurement, we acquired the compared branch length and diameters. Branch length’s regression of filed measurement and model estimation performed with Y = 1. 006 X+1. 335 , significant value of 0. 001. Meanwhile, branch diameter’s regression of filed measurement and model estimation performed with Y =0. 923 X +0. 105 , significant value of 0. 000 . The experiment results demonstrate that extracting skeleton model to identify individual tree’s branch structure and acquire structure parameters, such as branch length and branch diameter is applicable and promising.