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

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 understan...

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Yhteisötekijä: SpringerLink (Online service)
Muut tekijät: Singh, Suraj Kumar (Toimittaja), Kanga, Shruti (Toimittaja), Gupta, Saurabh Kumar (Toimittaja), Sajan, Bhartendu (Toimittaja), Sharma, D. D. (Toimittaja)
Aineistotyyppi: Elektroninen E-kirja
Kieli:englanti
Julkaistu: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Painos:1st ed. 2025.
Sarja:Smart Agriculture, 14
Aiheet:
Linkit:https://doi.org/10.1007/978-3-032-02118-2
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505 0 |a Advanced Remote Sensing Techniques for Cropland Monitoring using the AquaCrop Model -- Enhancing Phosphorus Sustainability in Mungbean via PROM and Microbial Inoculants -- Biparjoy Cyclone Assessment -- Crop Acreage and Yield Estimation Using Remote Sensing -- Multi Criteria Land Suitability Analysis for Agriculture in Jalpaiguri District West Bengal Using AHP and GIS Techniques. 
520 |a 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. . 
532 8 |a Accessibility summary: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub. 
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650 0 |a Environmental geography. 
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700 1 |a Sharma, D. D.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
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