A comparative study of the performances of joint RFE with machine learning algorithms for extracting Moso bamboo (Phyllostachys pubescens) forest based on UAV hyperspectral images

A comparative study of the performances of joint RFE with machine learning algorithms for extracting Moso bamboo (Phyllostachys pubescens) forest based on UAV hyperspectral images

Unmanned aerial vehicle (UAV) hyperspectral remote sensing technology has developed rapidly in recent years, providing a new scheme for intelligent monitoring of forest resources. This study aims to deeply mining the UAV hyperspectral information, and construct the best model for extracting Moso bam...

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Bibliographic Details
Main Authors: Yi-fan Li, Zhang-hua Xu, Zhen-bang Hao, Xiong Yao, Qi Zhang, Xu-ying Huang, Bin Li, An-qi He, Zeng-lu Li, Xiao-yu Guo
Format: Article
Language:English
Published: Taylor & Francis Group 2023-06-01
Series:Geocarto International
Subjects:
recursive feature elimination (rfe)
machine learning algorithms
moso bamboo forest
uav hyperspectral remote sensing
feature optimization
Online Access:http://dx.doi.org/10.1080/10106049.2023.2207550

Internet

http://dx.doi.org/10.1080/10106049.2023.2207550

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