Transforming Agricultural Management for a Sustainable Future (eBook, PDF)

Climate Change and Machine Learning Perspectives
Redaktion: Kanga, Shruti; Sajan, Bhartendu; Pathak, Vamdev; Shevkani, Khetan; Singh, Suraj Kumar

• Format: PDF

Produktbeschreibung

"Transforming Agricultural Management for a Sustainable Future: Climate Change and Machine Learning Perspectives" is an essential read for anyone interested in the future of agriculture and the role that technology can play in mitigating the impact of climate change. The book delves into the challenges facing agriculture today, such as climate change, soil degradation, and water scarcity. It then explores how machine learning can be used to overcome these challenges and promote sustainable agricultural practices.

One of the key takeaways from the book is the importance of data-driven decision-making in agriculture. With the help of machine learning algorithms, farmers can analyze vast amounts of data, such as weather patterns, soil quality, and crop yields, to make informed decisions about planting, irrigation, and fertilizer use. By using this data, farmers can optimize their yields while minimizing their impact on the environment.

Another important aspect of the book is its focus on climate change. Agriculture is one of the largest contributors to greenhouse gas emissions, and farmers are already feeling the impact of climate change through droughts, floods, and other extreme weather events. The book provides a comprehensive overview of the ways in which machine learning can be used to reduce the impact of agriculture on the environment, such as by optimizing irrigation and reducing fertilizer use.

The book also explores the role of technology in promoting sustainable agriculture practices. For example, precision agriculture techniques, such as GPS-guided tractors and drones, can help farmers reduce waste and improve crop yields. The book provides examples of how these techniques are already being used in practice, and how they can be further developed to promote sustainability.

Overall, "Transforming Agricultural Management for a Sustainable Future: Climate Change and Machine Learning Perspectives" is an insightful and informative read for anyone interested in the future of agriculture. The book provides a comprehensive overview of the challenges facing agriculture today and the ways in which technology can be used to overcome these challenges and promote sustainable practices. It is a must-read for farmers, policymakers, and anyone interested in the future of our planet.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 301
• Erscheinungstermin: 6. August 2024
• Englisch
• ISBN-13: 9783031634307
• Artikelnr.: 71379280

Autorenporträt

Dr. Shruti Kanga, M.Sc., Ph.D. is currently working as Associate Professor and Head in the Department of Geography, School of Earth and Environmental Science, Central University of Punjab, India. Previously she worked as Associate Professor at, the Centre for Climate Change and Water Research, Suresh Gyan Vihar University, Jaipur, India. She has also worked as an Assistant Professor in the Centre for Land Resource Management, Central University of Jharkhand (CUJ), Ranchi, and also served as a Research Associate in the Ministry of Environment, Forest and Climate Change (MoEF) sponsored research project. She received her PhD in 2013 from the Department of Remote Sensing, Birla Institute of Technology, Ranchi. She has worked in the areas of forest fire risk modeling and management, tourism, resource management, etc. She has published 130 journal articles, 15 edited and authored books, and 32 book chapters. Her numerous research interests include geographic information science in forest fire modeling, natural hazards, natural resource management, geographic information systems, land use management, risk assessment, fire ecology, satellite image analysis, satellite image processing, land use modeling, land degradation, and desertification. Dr. Suraj Kumar Singh, M.Sc., Ph.D. is an Associate professor and coordinator, at the Centre for Climate Change & water Research, Suresh Gyan Vihar University, Jaipur. Previously he worked as an Assistant Professor at the Central University of Jharkhand (CUJ), Ranchi. He has also served as a Research Associate at the National Remote Sensing Center (NRSC), an Indian Space Research Organization (ISRO) sponsored research project. He earned his Ph.D. degree in 2012 from the Department of Remote Sensing, Birla Institute of Technology, Ranchi. He has experience in the area of waterlogging and flood hazards, geospatial applications in water resources, disaster management, hydro-geomorphology, urban planning, and wasteland mapping. He has published nearly 145 articles in peer-reviewed journals, 18 books, and 35 book chapters. He has also organized and attended various workshops, seminars, and international conferences. Dr. Khetan Shevkani is an Assistant Professor of Food Science and Technology at the Department of Applied Agriculture, Central University of Punjab, India. He completed his doctorate in 2015 from Guru Nanak Dev University, India. His research interests include chemistry and technology of alternative proteins and starches, value-added product development, and food by-product utilisation. His research output includes 32 journal articles and 10 book chapters. Dr Vamdev Pathak is an assistant professor of geology at the Central University of Punjab, Bathinda, with a PhD from the University of Delhi (2016). Previously, he spent nine years as a scientist at the Ministry of Earth Sciences, New Delhi, and served various ministerial responsibilities in the Seismology and Geosciences division. His expertise spans Paleomagnetism, environmental magnetism, lava flow dynamics, and CO2 sequestration in basaltic lava flows. Dr. Pathak's notable achievements include establishing the magnetostratigraphy of the Mandla lobe in the eastern DVP and being the sole Indian scientist selected for the International Ocean Discovery Program for Expedition 399, April-June, 2023 at Atlantis Massif (30°N; Mid-Atlantic Ridge). Dr. Bhartendu Sajan currently working as an Assistant Professor at, the Centre for Climate Change and Water Research, Suresh Gyan Vihar University, Jaipur. He is an accomplished professional in Remote Sensing & Geographic Information Systems (GIS). He did his Ph.D. degree in Geography from SGVU, Jaipur; he brings a wealth of experience from roles such as GIS Engineer, GIS Analyst, and positions in government departments. His expertise extends to diverse projects including glacier mapping, geological survey, and forest boundary mapping, reflecting his proficiency in remote sensing and GIS applications. Actively engaged in continuous learning, he participates in various training programs, conferences, and webinars while contributing significantly through authored papers. Beyond his professional endeavors, Dr. Sajan enjoys music, travel, and internet exploration, showcasing a multifaceted personality dedicated to excellence in his field.

Inhaltsangabe

Chapter1. Understanding the Challenges of Climate Change for Agricultural Management.- Chapter2. Machine Learning Approaches for Crop Yield Prediction.- Chapter3. Data-Driven Decision Making in Agricultural Resource Allocation.- Chapter4. Remote Sensing and Precision Agriculture: A Sustainable Future.- Chapter5. Managing Water Resources for Sustainable Agricultural Production.- Chapter6. Integrating Agroforestry Practices for Climate Change Mitigation and Adaptation.- Chapter7. Exploring the Role of Blockchain in Sustainable Agricultural Management.- Chapter8. Sustainable Soil Management through Advanced Technologies.- Chapter9. Climate-Smart Agricultural Policies for a Sustainable Future.- Chapter10. Promoting Sustainable Agricultural Practices through Farmer-Driven Innovation.- Chapter11. Climate Change Impacts on Crop Productivity and Food Security: An Overview.- Chapter12. Climate change impacts on water resources and implications for agricultural management.- Chapter13. Advanced technologies for sustainable soil management in a changing climate.- Chapter14. Machine learning approaches for improving water management and irrigation efficiency in agriculture.- Chapter15. Machine learning applications for crop disease and pest monitoring and management.- Chapter16. Climate-resilient agroforestry systems for sustainable land use and livelihoods.