Remote sensing technology and machine learning algorithms for crop yield prediction in Bambara groundnut and grapevines

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Remote sensing technology and machine learning algorithms for crop yield prediction in Bambara groundnut and grapevines

Accurate and timely crop yield prediction (CYP) is important for ensuring food security, optimising agricultural practices and ensuring sustainable agriculture. Remote sensing technology (RS) utilises satellites, unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and several platforms...

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Bibliographic Details
Main Author:	Jewan, Shaikh Yassir Yousouf
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2024
Subjects:	yield prediction remote sensing machine learning multimodal data vegetation indices thermal indices weather data modelling
Online Access:	https://eprints.nottingham.ac.uk/79839/

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