Abstract: 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 cloud data of the laser scanning points. The characteristic information, including the height and crown diameter, were derived after an individual tree was identified. The original 3D points cloud data were processed by the following steps: establishing regular grids, layering the points cloud based on elevation value, calculating grid points density for each layer, extracting laser scanning points for each layer, identifying individual tree, and deriving characteristic information. The feasibility of the method was proved through case studies. The results show most of the laser scanning points that constitute an individual tree are extracted correctly. And the derived characteristic information was 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.

Key words: vehicle-borne laser scanning, points cloud data, street trees, layer, grid points density