This book focuses solely on the issues of agriculture and forest productivity analysis with advanced modeling approaches to bring solutions to food-insecure regions of South and Southeast Asia. Advanced modeling tools and their use in regional planning provide an outstanding opportunity to contribute toward food production and environments. In this book, leading-edge research methodologies related to remote sensing and geospatial variability of soil, water, and regional agricultural production indicators and their applications are introduced together-a unique feature of the book is the domain of regional policy perspectives and allied fields. In regional policy planning, agriculture and forestry have a key role in food security and environmental conservation that depends on the geo-spatial variability of these factors. Over the years, nature and climate have determined the variability of soil type, soil quality, geographical deviation for habitat, water quality, water sources, urban influences, population growth, carbon stock levels, and water resources with rain-fed or irrigated land use practices. In addition, human nutritional values and dietary habits have brought cultural adaptation of either mono- or multi-cropping patterns in the region. To encompass all these above mentioned factors and classify regional variability for policy planning, satellite remote sensing and geographical information systems have the immense potential to increase agricultural and forest productivity to ensure the resilience of its sustainability. Therefore, the 13 chapters presented in this book introduce modeling techniques using the signatures of vegetation and water indices, land use and land change dynamics, climatic, and socioeconomic criteria through spatial, temporal, and statistical analysis. As well, remote sensing and in-depth GIS analysis are integrated with machine and deep learning algorithms to address natural uncertainties such as flash floods, droughts, and cyclones in agricultural production management.

This book focuses solely on the issues of agriculture and forest productivity analysis with advanced modeling approaches to bring solutions to food-insecure regions of South and Southeast Asia. Advanced modeling tools and their use in regional planning provide an outstanding opportunity to contribute toward food production and environments. In this book, leading-edge research methodologies related to remote sensing and geospatial variability of soil, water, and regional agricultural production indicators and their applications are introduced together—a unique feature of the book is the domain of regional policy perspectives and allied fields. In regional policy planning, agriculture and forestry have a key role in food security and environmental conservation that depends on the geo-spatial variability of these factors.  Over the years, nature and climate have determined the variability of soil type, soil quality, geographical deviation for habitat, water quality, water sources, urban influences, population growth, carbon stock levels, and water resources with rain-fed or irrigated land use practices.  In addition, human nutritional values and dietary habits have brought cultural adaptation of either mono- or multi-cropping patterns in the region. To encompass all these above mentioned factors and classify regional variability for policy planning, satellite remote sensing and geographical information systems have the immense potential to increase agricultural and forest productivity to ensure the resilience of its sustainability. Therefore, the 13 chapters presented in this book introduce modeling techniques using the signatures of vegetation and water indices, land use and land change dynamics, climatic, and socioeconomic criteria through spatial, temporal, and statistical analysis. As well, remote sensing and in-depth GIS analysis are integrated with machine and deep learning algorithms to address natural uncertainties such as flash floods, droughts, and cyclones in agricultural production management.

This book has the ambition of presenting sustainability issues in a simple way to students in the field of agriculture and the environment. There is much diversity in the viewpoints on the meaning of sustainability. Sustainability must be made operational in each specific context and scaled, and appropriate methods must be designed to achieve long-term goals for the environment, agriculture, energy and food security. The ultimate goal of the environment and agriculture is protecting soil and water to ensure food security for the growing population. This book discusses the integration of views pertaining to the sustainability of agriculture, the environment, renewable energy and food security.

This book addresses the important question of how large a role bioproduction and renewable energy can play in achieving sustainable agricultural practices in the present system of agricultural production. Understanding bioproduction engineering and development can help improve the efficiency of sustainable agriculture and future renewable energy resources. With the aim of understanding this question, this book focuses on bioproduction and sustainability issues, covering sensors, agricultural decision making systems and the relationship between bioproduction and sustainable practices of agriculture. Topics discussed include information oriented technology that can be implemented to address the variability of bioproduction systems; sensors and control systems; precision agricultural technology; decision support systems in agriculture; renewable energy resources; and analytical hierarchy processes for agricultural management. This material will appeal to a wide range of readers and is designed as a resource for graduate and undergraduate students working in any area of agricultural engineering, crop sciences, or environmental science disciplines. The book also includes questions and sample model problems to allow readers to practice implementing the modelling tools.

This book reviews recent innovations in the smart agriculture space that use the Internet of Things (IoT) and sensing to deliver Artificial Intelligence (AI) solutionsto agricultural productivity in the agricultural production hubs. In this regard, South and Southeast Asia are one of the major agricultural hubs of the world, facing challenges of climate change and feeding the fast-growing population. To address such challenges, a transboundary approach along with AI and BIG data for bioinformatics are required to increase yield and minimize pre- and post-harvest losses in intangible climates to drive the sustainable development goal (SDG) for feeding a major part of the 9 billion population by 2050 (Society 5.0 SDG 1 & 2). Therefore, this book focuses on the solution through smart IoT and AI-based agriculture including pest infestation and minimizing agricultural inputs for in-house and fields production such as light, water, fertilizer and pesticides to ensure food security aligns with environmental sustainability. It provides a sound understanding for creating new knowledge in line with comprehensive research and education orientation on how the deployment of tiny sensors, AI/Machine Learning (ML), controlled UAVs, and IoT setups for sensing, tracking, collection, processing, and storing information over cloud platforms for nurturing and driving the pace of smart agriculture in this current time.  The book will appeal to several audiences and the contents are designed for researchers, graduates, and undergraduate students working in any area of machine learning, deep learning in agricultural engineering, smart agriculture, and environmental science disciplines. Utmost care has been taken to present a varied range of resource areas along with immense insights into the impact and scope of IoT, AI and ML in the growth of intelligent digital farming and smart agriculture which will give comprehensive information to the targeted readers.