Early cereal yield prediction using machine learning and Sentinel-1 & Sentinel-2 satellite data

Forecasting cereal production is crucial for food security, especially in southern Mediterranean countries like Tunisia that rely on cereal imports. While optical indices are commonly used for cereal yield forecasting, integrating radar data within Machine learning (ML) models for simultaneous grain...

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Autors principals:	A. Chahbi-Bellakanji, E. Shil, M. Khlif, M. Zribi, Z. Lili-Chabaane
Format:	Artigo
Idioma:	Inglês
Publicat:	Taylor & Francis Group 2025-12-01
Col·lecció:	European Journal of Remote Sensing
Matèries:	Crop yield forecasting regression model remote sensing indices radar polarization ratio machine learning cereal
Accés en línia:	https://www.tandfonline.com/doi/10.1080/22797254.2025.2558614
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