A hierarchical approach to the segmentation of single dominant and dominated trees in forest areas by using high-density LiDAR data

In this paper we present a hierarchical approach to the segmentation of high-density LiDAR data which aims to automatically detect and delineate the single tree crowns of both the dominant and the dominated layers of the forest. First, we detect the dominant tree crowns by using both the image derived from the LiDAR data and the LiDAR point cloud. Hence, the detected crowns are delineated directly in the LiDAR point cloud by means of a radial angular analysis. Second, the dominated crowns are detected by analyzing the vertical profile of the dominant trees. Finally, we extract the dominated trees, thus reconstructing the structure of the forest. Experiments carried out in a forest area located in the Southern Italian Alps by using very high density LiDAR data (up to 50 points/m²) point out the effectiveness of the proposed approach.