G. P. Obi Reddy - Data Science in Agriculture and Natural Resource Management

The series Studies in Big Data (SBD) publishes new developments and advances in the various areas of Big Data- quickly and with a high quality. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer science, physics, economics and life sciences. The books of the series refer to the analysis and understanding of large, complex, and/or distributed data sets generated from recent digital sources coming from sensors or other physical instruments as well as simulations, crowd sourcing, social networks or other internet transactions, such as emails or video click streams and other. The series contains monographs, lecture notes and edited volumes in Big Data spanning the areas of computational intelligence including neural networks, evolutionary computation, soft computing, fuzzy systems, as well as artificial intelligence, data mining, modern statistics and Operations research, as well as self-organizing systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.

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The world of Data Science is rapidly changing due to fast-emerging technology changes in the fields of computers, data acquisition systems, and digital technologies. The last two decades witnessed tremendous developments in Information and Communication Technologies (ICT), including the Internet, cloud computing, sensors technology, computer processing, and storage and dissemination systems, which opens new avenues in digital data acquisition, processing, visualization, and disseminating valuable information of the planet earth to the general users, planners, and policy makers. This digital revolution, accompanied by the fast emerging of remote sensing platforms, provides an unprecedented amount of geospatial data on the status of planet earth resources, especially on natural resources, agriculture, and their dynamics, to develop various Earth Observation (EO) applications.

The edited volume on Data Science in Agriculture and Natural Resource Management addressed the principles and applications of data science and emerging challenges in agriculture and natural resource management. The volume contains three important sections, namely, Data Science-Principles, Concepts and Applications, Data ScienceApplications in Agriculture, and Data ScienceApplications in Natural Resources Management. The chapters in these sections dealt with specialized areas contributed by eminent experts from research institutes and universities of India and abroad with suitable illustrations and tables. The edited book is unique in the field of Data Science Applications in Agriculture and Natural Resource Management. The book provides advanced knowledge on data science and added the latest knowledge in the field to benefit the global readers. The authors from renowned international organizations/Universities/Industries like International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), International Center for Agricultural Research in the Dry Areas (ICARDA), national organizations like ICAR-National Bureau of Soil Survey and Land Use Planning (ICAR-NBSS&LUP), Indian Institute of Technology Bombay (IITB), Ahmedabad University, Pandit Deendayal Energy University, University of Agricultural Science, Bangalore; and industrial entities such as NTT Data, International Business Machines (IBM) Corporation and Amnex Infotechnologies contributed the chapters to the edited volume with suitable case studies.

This book explored various facets of data science, the big data revolution, and EO applications in agriculture and natural resource management. It stimulates new ideas in data-driven research, new applications by integrating emerging data science techniques and robust prediction models in the emerging fields of cloud computing, artificial intelligence (AI), and deep learning, and ICT applications for geo-smart agriculture and sustainable natural resource management. I am sure the book realizes the aspirations and needs of geospatial, data science, agricultural, natural resources, and environmental scientists/faculty/students from traditional universities, agricultural universities, technological universities, research institutes, and academic colleges worldwide. It also helps planners, policymakers, and extension scientists plan and sustain natural resources for climate-resilient agriculture.