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

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
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
Series:Remote Sensing
Subjects:
remote sensing
classification
multi-feature
feature selection
random forest
Online Access:https://www.mdpi.com/2072-4292/14/4/829

Internet

https://www.mdpi.com/2072-4292/14/4/829

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