Identification of Cotton Root Rot by Multifeature Selection from Sentinel-2 Images Using Random Forest

Identification of Cotton Root Rot by Multifeature Selection from Sentinel-2 Images Using Random Forest

Cotton root rot is a destructive cotton disease and significantly affects cotton quality and yield, and accurate identification of its distribution within fields is critical for cotton growers to control the disease effectively. In this study, Sentinel-2 images were used to explore the feasibility o...

Full description

Bibliographic Details
Main Authors: Xingrong Li, Chenghai Yang, Wenjiang Huang, Jia Tang, Yanqin Tian, Qing Zhang
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Remote Sensing
Subjects:
cotton root rot
Sentinel-2
random forest
binary logistic regression
spectral and texture analysis
airborne multispectral imagery
Online Access:https://www.mdpi.com/2072-4292/12/21/3504

Internet

https://www.mdpi.com/2072-4292/12/21/3504

Similar Items