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LiDAR in Forestry

Main activity

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.

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.