Rice yield prediction through integration of biophysical parameters with SAR and optical remote sensing data using machine learning models

Abstract In an era marked by growing global population and climate variability, ensuring food security has become a paramount concern. Rice, being a staple crop for billions of people, requires accurate and timely yield prediction to ensure global food security. This study was undertaken across two...

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Hlavní autoři:	Sonam Sah, Dipanwita Haldar, RN Singh, B. Das, Ajeet Singh Nain
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2024-09-01
Edice:	Scientific Reports
Témata:	Remote sensing LAI Biomass Moisture content XGB Cubist
On-line přístup:	https://doi.org/10.1038/s41598-024-72624-4
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