Tree Species Classification Using Optimized Features Derived from Light Detection and Ranging Point Clouds Based on Fractal Geometry and Quantitative Structure Model

Tree Species Classification Using Optimized Features Derived from Light Detection and Ranging Point Clouds Based on Fractal Geometry and Quantitative Structure Model

Tree species classification is a ubiquitous task in the forest inventory field. Only directly measured feature vectors have been applied to most existing methods that use LiDAR technology for tree species classification. As a result, it is difficult to obtain a satisfactory tree species classificati...

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Bibliographic Details
Main Authors: Zhenyang Hui, Zhaochen Cai, Peng Xu, Yuanping Xia, Penggen Cheng
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Forests
Subjects:
tree species
LiDAR point cloud
feature vectors
fractal geometry
quantitative structure model
Online Access:https://www.mdpi.com/1999-4907/14/6/1265

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https://www.mdpi.com/1999-4907/14/6/1265

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