Adaptive Mean Shift-Based Identification of Individual Trees Using Airborne LiDAR Data

Abstract

Identifying individual trees and delineating their canopy structures from the forest point cloud data acquired by an airborne LiDAR (Light Detection And Ranging) has significant implications in forestry inventory. Once accurately identified, tree structural attributes such as tree height, crown diameter, canopy based height and diameter at breast height can… (More)
DOI: 10.3390/rs9020148

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Cite this paper

@article{Hu2017AdaptiveMS, title={Adaptive Mean Shift-Based Identification of Individual Trees Using Airborne LiDAR Data}, author={Xingbo Hu and Wei Chen and Weiyang Xu}, journal={Remote Sensing}, year={2017}, volume={9}, pages={148} }