Extraction of multilayer vegetation coverage using airborne LiDAR discrete points with intensity information in urban areas: A case study in Nanjing City, China

Urban vegetation is of a strategic importance for the life quality in the increasing urbanized societies. However, it is still difficult to extract accurately urban vegetation vertical distribution with remote sensing images. This paper presented an effective method to extract multilayer vegetation coverage in urban areas using airborne Light Detection and Ranging (LiDAR) discrete points with intensity information. It was applied in Nanjing City, one of the ecological cities in China. Firstly, a median filtering algorithm based on discrete points was used to restrain high-frequency noise. The airborne LiDAR data intensities of different urban objects were analyzed and obtained three rules, which can distinguish between vegetation and non-vegetation in urban areas, after removing the influence of topography. According to the footprint size and principles of distribution of the point cloud, multilayer vegetation coverage, including trees, shrubs and grass, was achieved by the inverse distance weighting (IDW) interpolation method. The results show that the overall accuracy of the vegetation point classification is 94.57%, which is much accurate than that of the methods in TerraSolid software, through comparing with the investigation in the field and Digital Orthophoto Maps (DOM). This method proposed in our work can be applied to in the extraction of multilayer vegetation coverage in urban area.