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...

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Detalhes bibliográficos

Principais autores:	Guang Yang, Jun Wang, Zhengyuan Qi
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2025-07-01
Colecção:	Agronomy
Assuntos:	GEE maize feature optimization random forest recursive feature elimination (RF-RFE)
Acesso em linha:	https://www.mdpi.com/2073-4395/15/7/1667
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