Accurate crown detection and delineation of dominant and subdominant trees is crucial for accurate inventorying of forests at the individual tree level. State-of-the-art tree detection and crown delineation methods have good performance mostly with dominant trees, whereas exibits a reduced accuracy when dealing with subdominant trees. In this paper, we propose a novel approach to accurately detect and delineate both dominant and subdominant tree crowns in conifer dominated multistoried forests using small footprint high density airborne LiDAR data.
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LiDAR in Forestry
The Airborne light detection and ranging (LiDAR) is a popular active remote sensing technique that over-samples the remote study area using a highly directed laser beam, resulting in the generation of a very dense georeferenced elevation points called as the LiDAR point cloud. Unlike other visible remote sensing techniques, the data aquired using high sampling-density small-footprint muti-return LiDAR can record a huge amount of structural information about the forest vertical profile.