Assessment of Vegetation Landscape Index in Urban Areas from Terrestrial LiDAR Data

摘要

In this paper, we estimate green space ratio (GSR), that is a landscape index representing a proportion of green area to a whole view area, by using terrestrial LiDAR data, and assess the performance. Originally, the GSR estimation method is designed to use the airborne light detection and ranging (LiDAR) data and aerial images (Susaki and Komiya, 2014). However, it was found that the extraction of vegetation using airborne data may omit small populations of vegetation. Therefore, we examined the terrestrial LiDAR for estimating GSR. Before estimating GSR, we extracted vegetation points out of the observed point clouds by following the method proposed by (Wakita and Susaki, 2015). The method uses a voxel-based approach and focuses on the surface roughness calculated by using point clouds. We applied the method to a data set collected in a residential area in Kyoto, Japan. We compared the results with the ground truth data and obtained RMSE of approximately 2.6 %. Although the estimated GSRs tend to be overestimated, it is reasonable to suppose that our method shows great improvement in the accuracy. In future, after we improve the accuracy of extracting vegetation points, we will apply the method to mobile LiDAR data.