Maize Classification in Arid Regions via Spatiotemporal Feature Optimization and Multi-Source Remote Sensing Integration

Maize Classification in Arid Regions via Spatiotemporal Feature Optimization and Multi-Source Remote Sensing Integration

This study addresses the challenges of redundant crop identification features and low computational efficiency in complex agricultural environments, particularly in arid regions. Focusing on the Hexi region of Gansu Province, we utilized the Google Earth Engine (GEE) to integrate Sentinel-2 optical...

Full description

Saved in:
Bibliographic Details
Main Authors: Guang Yang, Jun Wang, Zhengyuan Qi
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Agronomy
Subjects:
GEE
maize
feature optimization
random forest
recursive feature elimination (RF-RFE)
Online Access:https://www.mdpi.com/2073-4395/15/7/1667
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items