Agri-informatics and Eco-friendly Innovations for a Secure Food Future
Language: English
Published by Springer, 2026
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 185.11
Quantity: 1 available
Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - 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. …
Seller Inventory # 9783032021175
- Title
- Agri-informatics and Eco-friendly Innovations for a Secure Food Future
- Author
- Suraj Kumar Singh
- Publisher
- Springer
- Publication year
- 2026
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3032021170
- ISBN 13
- 9783032021175
- Item weight
- 820 grams
- Dimensions
- 241x160x30 mm
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
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