Wheat yield prediction using integrated optical and radar remote sensing with machine learning across key phenological stages

Abstract Precise and timely prediction of wheat yield is pivotal for ensuring global food security and optimizing agricultural management practices, particularly through advanced remote sensing and machine learning techniques. In this study, wheat yield was accurately estimated by leveraging remote...

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מידע ביבליוגרפי

Principais autores:	Mir Naser Navidi, Erfan Fazli, Rasoul Kharazmi, Javad Seyedmohammadi
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Nature Portfolio 2026-02-01
סדרה:	Scientific Reports
נושאים:	Crop phenology Vegetation indices Remote sensing integration Sentinel MLR SVM
גישה מקוונת:	https://doi.org/10.1038/s41598-026-41501-7
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!