关键词: 车载LiDAR, 行道树, 信息提取, 安全风险评价

Abstract:

Rapid and accurate acquisition of the structural characteristics and safety risk status of urban street trees based on LiDAR point cloud data is of great significance to assist smart city management.In order to solve the problem that LiDAR point cloud data is difficult to segment regions with unclear morphological characteristics in street tree parameter acquisition,a individual tree extraction method based on circular index of trunk center point was proposed.Firstly,it obtained the sliced point cloud of the trunk layer according to the elevation information,then,segmented the sliced data based on the improved DBSCAN clustering algorithm.Secondly,it identified the trunk through the morphological characteristics of the ground features and obtained the central point,so as to complete the extraction through the circular index method based on the central point.Finally,it combined with the risk matrix method to evaluate the safety risk of the stability and traffic impact of the street trees in the study area.The results showed that the proposed individual tree extraction method could effectively improve the segmentation accuracy of individual trees of street trees in areas with unclear morphological characteristics,and accurately obtain the structural parameter information such as the number,shape and position of street trees;The safety risk assessment found that the stability of most street trees and the risk of traffic impact in the study area werein a level I negligible risk state,but there were some street trees whose stability and risk of traffic impact were level II and level III.These trees were mainly distributed in the area with dense and interlaced roadside trees in the study area.The results can provid corresponding decision support for relevant departments to monitor street trees in a timely and effective manner.

Key words: vehicle-borne LiDAR, extraction of information, street trees, security risk assessment