Agri-Informatics and Eco-Friendly Innovations for a Secure Food Future
Singh, Suraj Kumar (EDT); Kanga, Shruti (EDT); Gupta, Saurabh Kumar (EDT); Sajan, Bhartendu (EDT); Sharma, D. D. (EDT)
Language: English
Published by Springer, 2026
- Hardcover
- New
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- Title
- Agri-Informatics and Eco-Friendly Innovations for a Secure Food Future
- Author
- Singh, Suraj Kumar (EDT); Kanga, Shruti (EDT); Gupta, Saurabh Kumar (EDT); Sajan, Bhartendu (EDT); Sharma, D. D. (EDT)
- Publisher
- Springer
- Publication year
- 2026
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3032021170
- ISBN 13
- 9783032021175
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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