Satiprasad Sahoo – författare

Feeding a growing global population with a changing climate, shrinking arable land, and increasingly strained water resources is a challenge with no single solution. Machine Learning and AI Technology in Agricultural Applications recasts agriculture as fundamentally a problem of data acquisition, integration, and analysis. Drawing on concrete methods and case studies, the book shows how advanced technologies turn scattered sensor readings, satellite imagery, and field records into decision-making tools that enable more precise, more resilient, and more sustainable farming practices.The chapters cover the full agricultural cycle: crop and weather indicators feeding models that predict yield before harvest; satellites and drones replacing manual field-monitoring surveys across the growing season; and image-based algorithms supporting targeted interventions, from detecting a diseased plant to directing a sprayer to apply treatment only where it is required. The same reliance on remote sensing and predictive modeling carries into aquaculture and water management, where artificial intelligence (AI) and machine learning (ML) are used to estimate groundwater recharge, track fish growth, and monitor water quality. A dedicated set of chapters also examines the economic dimensions of this shift, assessing the viability, market impact, and costs of adopting these innovations, and clarifying where they are most likely to reshape how these sectors operate.Together, these technical perspectives make the book a valuable resource for students building a foundation in this field, as well as for researchers and practitioners looking to apply its findings and insights to their own work.Bridges theory and practice by distilling complex analytical approaches into practical, implementation-ready workflows.Surveys established ML models - such as random forests, support vector machines, and decision trees - alongside newer deep learning architectures, helping readers match the right tool to the task at hand.Demonstrates the value of real- or near-real-time monitoring, from continuous field analytics to automated control systems that respond to conditions as they change.

This book provides a multidisciplinary synthesis of the sustainable management of natural resources. The book presents applicable knowledge of land, water, and forest resources along with in-depth investigations of multiple management pathways. This book also demonstrated the contemporary applications of geospatial technology in data mining techniques, data analysis, modeling, assessment, and visualization, and appropriate management strategies in different aspects of natural resources. The book explores the latest state-of-the-art techniques using open-source software, statistical programming, and modeling platforms, including artificial intelligence techniques in natural resource management. It is a valuable resource for students, researchers, and practitioners in geography, geospatial sciences, and environmental sciences, especially those interested in land, water, and forest resources.

This book provides a multidisciplinary synthesis of the sustainable management of natural resources. The book presents applicable knowledge of land, water, and forest resources along with in-depth investigations of multiple management pathways. This book also demonstrated the contemporary applications of geospatial technology in data mining techniques, data analysis, modeling, assessment, and visualization, and appropriate management strategies in different aspects of natural resources. The book explores the latest state-of-the-art techniques using open-source software, statistical programming, and modeling platforms, including artificial intelligence techniques in natural resource management. It is a valuable resource for students, researchers, and practitioners in geography, geospatial sciences, and environmental sciences, especially those interested in land, water, and forest resources.  

This book provides a multidisciplinary synthesis of the sustainable management of natural resources. The book presents applicable knowledge of land, water, and forest resources along with in-depth investigations of multiple management pathways. This book also demonstrated the contemporary applications of geospatial technology in data mining techniques, data analysis, modeling, assessment, and visualization, and appropriate management strategies in different aspects of natural resources. The book explores the latest state-of-the-art techniques using open-source software, statistical programming, and modeling platforms, including artificial intelligence techniques in natural resource management. It is a valuable resource for students, researchers, and practitioners in geography, geospatial sciences, and environmental sciences, especially those interested in land, water, and forest resources.

This book bridges the gap between research, practice, and policy by offering practical insights and evidence-based solutions. It provides a comprehensive guide to addressing the pressing challenges posed by climate change and extensive anthropogenic activities on the health of global delta ecosystems. Through in-depth analysis, the book examines delta ecosystem resiliency, sustainable practices, and strategies for restoring and safeguarding natural resources. The book underscores the critical importance of studying rivers for their resilience, emphasizing the biophysical aspects of riverine landscapes and their interactions with ecosystems. It highlights how urbanization, groundwater extraction, agricultural intensification, channel regulation, and upstream activities like water withdrawals, diversion, and sediment trapping combine with coastal hazards - such as sea level rise, salinity intrusion, and hurricanes - to jeopardize delta social-ecological systems. Modern geospatial technologies play a prominent role, with discussions on data mining, analysis, modeling, assessment, and visualization techniques. The book explores appropriate management strategies and cutting-edge approaches to delta health management, leveraging open-source software, statistical programming, modeling platforms, and artificial intelligence. These strategies aim to address the multifaceted challenges of delta management while contributing to multiple Sustainable Development Goals (SDGs), including SDG2, SDG6, SDG13, SDG14, SDG15, and SDG17. Organized into thematic chapters, the book combines theoretical frameworks, empirical research, and actionable recommendations. It integrates data from diverse delta regions to provide a holistic perspective, enhanced by diagrams, charts, maps, and case studies for improved understanding and practical application. This approach ensures the book serves as both a foundational reference and an inspirational guide for fostering resilient and sustainable delta ecosystems capable of withstanding climate uncertainties and human-induced pressures. The book is a valuable resource for researchers, policymakers, administrators, educators, local communities, farmers, and practitioners. It offers innovative practices and adaptive strategies to promote sustainable delta ecosystem resilience in the face of climate challenges and extensive anthropogenic activities.