Due to the increasing use of the Terrestrial LiDAR Scanning (TLS also called T-LiDAR) technology in the forestry domain, many researchers and forest management organizations have developed several algorithms for the automatic measurement of forest inventory attributes. However, to the best of our knowledge not much has been done regarding single tree species recognition based on T-LiDAR data despite its importance for the assessment of the forestry resource. In this paper, we propose to put the light on the few works reported in the literature. The various algorithms presented in this paper uses the bark texture criteria and can be categorized into three families of approaches: those how combine T-LiDAR technology and photogrammetry, those based on depth images generated from T-LiDAR data and those based on raw 3D point cloud.
Hybrid segmentation of depth images using a watershed and region merging based method for tree species recognition