Mapping 3d Structure of Urban Trees Using AIrborne Lidar Data for Topographic Survey

Abstract. The designing of urban spaces utilizing trees is a promising approach to alleviate the severe thermal environment. Three-dimensional (3D) information on individual trees is important for their maintenance and for evaluating their microclimatic effects. Methods have been developed for estimating the 3D distribution of leaf area density (LAD) using high-density airborne light detection and ranging (LiDAR) point cloud. However, the coverage of high-density data is limited. This study sought to develop a method for estimating LAD distribution using existing low-density LiDAR data that was obtained for the nationwide topographic survey. A point cloud with the same density as the existing data was generated from the high-density data. LAD was estimated using the generated point cloud and was compared with LAD derived from the high-density data and terrestrial LiDAR to clarify the spatial scale of information obtained from the existing data. A method to improve the spatial scale was also examined. These methods were applied to the actual existing LiDAR data to generate a 3D information map at an urban scale.