一种基于车载激光扫描点云数据的行道树识别方法

s an important method for acquiring close-range three-dimensional (3D) data of cities, Vehicle-borne Laser Scanning (VLS) has the ability to obtain 3D information of different objects on the two sides of urban streets. This paper presents a new layered extraction method for identifying laser scanning points that constitute an individual street tree using the grid points density information based on the laser scanning points cloud data. The characteristic information, including height and crown diameter, is derived after an individual tree has been identified. The original 3D points cloud data are processed by following steps: establishing regular grids, layering the points cloud based on elevation value, calculating grid points density for each layer, extracting laser points for each layer, identifying individual tree, and deriving characteristic information. The feasibility of the method is proved through a case study. The results show most of the laser points that constitute an individual tree are identified and extracted correctly. The derived characteristic information is estimated to be as fairly accurate as the in situ data. The proposed method will expand the application domain of VLS and provide a new approach to the urban green space development and management.