Cotton Classification Method at the County Scale Based on Multi-Features and Random Forest Feature Selection Algorithm and Classifier

Accurate cotton maps are crucial for monitoring cotton growth and precision management. The paper proposed a county-scale cotton mapping method by using random forest (RF) feature selection algorithm and classifier based on selecting multi-features, including spectral, vegetation indices, and textur...

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Bibliographic Details

Published in:	Remote Sensing
Main Authors:	Hao Fei, Zehua Fan, Chengkun Wang, Nannan Zhang, Tao Wang, Rengu Chen, Tiecheng Bai
Format:	Article
Language:	English
Published:	MDPI AG 2022-02-01
Subjects:	remote sensing classification multi-feature feature selection random forest
Online Access:	https://www.mdpi.com/2072-4292/14/4/829