Agri-informatics and Eco-friendly Innovations for a Secure Food Future



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Éditeur :

Springer


Paru le : 2026-02-11



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Description

Food security is a critical global challenge, aiming to provide sufficient and healthy food for all. The United Nations has set Sustainable Development Goals (SDGs) to achieve global prosperity while ensuring environmental protection. Machine learning (ML) techniques play a crucial role in understanding and predicting food security. Key applications include cropland mapping, crop type identification, yield prediction, and field delineation. Challenges include handling complex data and ensuring rigorous evaluation. Looking ahead, advanced techniques such as AI and interdisciplinary collaborations will drive progress toward a hunger-free and sustainable future. 
This book concentrates on the fundamentals and uses of environment science perspective on Food security using cutting-edge methods of spatial information and artificial intelligence. Experts and researchers in the fields of agriculture, environmental science and engineering, disaster management, remote sensing, and geographic information systems have contributed to this volume. 
Pages
430 pages
Collection
n.c
Parution
2026-02-11
Marque
Springer
EAN papier
9783032021175
EAN PDF
9783032021182

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
33526 Ko
Prix
147,69 €
EAN EPUB
9783032021182

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
86794 Ko
Prix
147,69 €

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