基于点云数据的单木三维绿量估算方法

针对不同树种的树叶疏密及空间结构不同，提出基于激光点云数据，顾及冠层叶面积密度的树木三维绿量（Living Vegetation Volume， LVV）计算方法。该方法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，剔除非光合作用成分，提取树叶点云；然后建立体元模型，引入Graham算法确定分层树冠边界，获取激光接触频率，从而基于体元冠层分析（Voxel-based Canopy Profiling， VCP）方法求出冠层叶面积密度（Leaf Area Density， LAD）；最后分层棱柱体积乘以叶面积密度，累加得到树木的三维绿量。利用Riegl VZ-400地面激光扫描仪获取13棵不同形状和树种的树木点云数据，利用该方法估算各树木三维绿量，并与传统的凸包法和台积法的结果对比。实验结果表明，台积法计算的三维绿量值最大，凸包法计算的三维绿量次之，顾及冠层叶面积密度的树木三维绿量方法计算的三维绿量值最小，为台积法的36.69%，为凸包法的47.80%。相比传统方法，顾及冠层叶面积密度的树木三维绿量计算方法侧重光合作用组分叶片点云的统计，并考虑了树冠内部树叶分布情况，更符合树木的实际情况，能充分利用三维点云数据特性，反映树冠内部三维绿量分布。

A Method for Estimating Living Vegetation Volume of Urban Trees based on Point Cloud Data

A method for Living Vegetation Volume （LVV） calculation based on laser-scanned point cloud data was proposed， by taking into consideration the differences of leaf density and spatial structure among various trees. The procedure is as follows： firstly， according to the main direction similarity and the axial distribution density of the local point cloud of the tree， the branches （non-photosynthetic components） and leaves are separated， and the leaf point cloud is extracted； then the voxel model of leaves is created. The Graham algorithm was utilized to determine the boundary of the layered tree canopy and the laser contact frequency， the Leaf Area Density （LAD） of the canopy was obtained based on the Voxel-based Canopy Profiling （VCP） method； finally， the living vegetation volume of the tree is accumulated by adding up the layered prism volume multiplied by the leaf area density. We used a Riegl VZ-400 ground-based laser scanner to obtain point cloud data of 13 trees of different shapes and species. The results show that the living vegetation volume calculated by our algorithm is 36.69% of that of the platform method and 47.80% of that of the convex hull method. Compared with traditional methods， this approach focuses on the statistics of the leaf point cloud of photosynthesis components distribution of the tree canopy by taking into account leaf area density， and the living vegetation volume estimation is more in line with the actual situation of the tree.