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 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.

Crop production varies spatially and temporally within the field boundaries depending on soil and environmental conditions. The major concern of variability for agronomic inputs addresses how best to intervene in the right place, at the right time and in the right quantity to improve the potential yield of crops and feedstock. 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. Agronomy is local, which brings the challenges to the remote optimisation of agricultural machinery operations for seeding, fertilising, crop protecting, and harvesting in the field level to adopt precise agriculture technologies. Cloud computing and big data analytics bring the potential about in machine optimisation and agronomy to enable the site-specific management. Understanding bioproduction engineering and development can help improve the efficiency of a sustainable agriculture system. With the aim of understanding this process, this book focuses on bioproduction and sustainability issues, covering sensors, agricultural decision-making systems and the relationship between bioproduction and sustainable practices of agriculture. The chapters are organised as follows: 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. The crop growth monitoring parameters like LAI and NDVI points were clarified in the pre-processing stage of images. The decisions and logistics that influence the market prices of agricultural products is emphasised within the revised edition of this book.

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 provides a sound understanding for creating new knowledge, which takes three main forms: Exploratory research, which structures and identifies new problems; constructive research, which develops solutions to a problem; and empirical research, which tests the feasibility of a solution using empirical evidence. This book encompasses both qualitative and quantitative research and analysis. The reader should gain an understanding of the skills needed to design and undertake a research project, including legal and ethical requirements in planning research projects, choosing the best experimental design and analytical methods, and how to present data for extension to the wider community and establish the knowledge. Hands-on exercises are provided to improve reasoning skills, emphasising agricultural problems and issues to solve and interpret the experimental data to knowledge. The book covers research methods within these three forms with basic knowledge of research methodology. Design of experiments and significant results are interpreted through the scientific organisation and information in each of the chapters. The inherent discussion should help interdisciplinary graduate students and researchers accomplish their scientific experiments and write research articles. The cognitive writing style to interpret the observed data from experiments and surveys is emphasised in this book. The cognitive summary for each of the chapters is provided in the form of wording and graphics to focus on the chapter highlights as well as the use of analytical tools in the research. The utmost care is taken to present a varied range of research problems along with their solutions in agriculture and its allied fields, which should be of immense use to the readers interested in this topic.

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.