Institute of Electrical and Electronics Engineers, IEEE Geoscience and Remote Sensing Letters, 6(11), p. 1056-1060, 2014
DOI: 10.1109/lgrs.2013.2285471
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High-density airborne light detection and ranging (LiDAR) data with point densities over 50 points/m 2 provide new opportunities, because previously inaccessible quantities of an individual tree can be derived directly from the data. We introduce a skeleton measurement methodology to extract the diameter at breast height (DBH) from airborne point clouds of trees. The esti-mates for the DBH are derived by analyzing the point distances to a suitable tree skeleton. The method is validated in three scenarios: 1) on a synthetic point cloud, simulating the point cloud acquisition over a forest; 2) on examples of free-standing and partly occluded trees; and 3) on automatically extracted trees from a sampled forest. The proposed diameter estimation performed well in all three scenarios, although influences of the tree extraction method and the field validation could not be fully excluded.