从三维激光点云中快速统计树木信息的方法

Location distribution and diameter at breast height (DBH) of trees are important indicators for studying forest ecology and managing forest areas. Lidar have great potential for obtaining tree-related data. Therefore, a fast statistics method of tree information from three-dimensional laser point clouds obtained by hand-held mobile laser is proposed. The hand-held mobile laser can collect the tree information from close distance and obtain the detailed information of a single tree facade. In view of the characteristics of the above point cloud, a method based on hierarchical clustering is proposed. A group of cross-section slices of point cloud are formed at different heights, and the segmentation process of each slice is performed by cluster analysis. We use random sample consensus algorithm to fit the circle according to the result of segmentation and complete the tree point cloud extraction by comparing the fitting results of a set of slice sections. This method of sampling and recalculating greatly improves the processing speed. The results show that the accuracy of trunk extraction is 94.4%, the average calculation error of DBH is 3.4 cm. The proposed method can quickly statistic tree information.