Data Science in Agriculture and Natural Resource Management

This book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.

Auteur

G.P. Obi Reddy holds Ph.D. and is working as Principal Scientist in the field of remote sensing and GIS applications at Division of Remote Sensing Applications, ICAR-National Bureau of Soil Survey and Land Use Planning, Nagpur, India. He has significantly contributed in the field of remote sensing along with GIS applications in digital terrain modelling, landforms mapping, soil-landscape modelling, land degradation assessment, agro-ecology and development of soil information systems. He is instrumental in the design and development of the Land Resource Information System (LRIS) of India and BHOOMI Geoportal. On ICAR deputation, he visited Sri Lanka, The Netherlands, Nepal and South Africa. He has published 102 research articles in reputed national/international journals, 4 books, 49 book chapters and 10 technical bulletins. Currently he is acting as a Chairman, Data Content Standards of DST-NSDI and Member, ISO/TC 211/WG 04 Geospatial Services. He is Recipient of Indian National Geospatial Award-2007 and National Geospatial Award for Excellence-2013 from Indian Society of Remote Sensing, Dehradun, Outstanding Scientist Award-201617 from ICAR-NBSS&LUP, Nagpur and Fellow of Indian Society of Soil Survey Land Use Planning, Nagpur.

Mehul S Raval holds Ph.D. and is Associate DeanExperiential Learning and Professor at Ahmedabad University, India. His research interest includes computer vision, and he has contributed to problems in surveillance, medical imaging, biometrics and agriculture. His academic pursuits involve visits to under Sakura Science Fellowship (2015) to Okayama University, Japan, Argosy visiting Associate Professor at Olin College of Engineering, MA, the USA (2016), and Sacred Heart University, the USA (2019). He serves as Member, technical program committee, for leading national and international conferences, workshops and symposiums. Currently, he chairs IEEE Computational Intelligence SocietyGujarat Chapter and served in IEEE Gujarat section under various capacities. He has received research grants from Board of Research in Nuclear Science and DSTGovt. of India. He has published 79 scholarly works in journals, magazines, conferences, workshops at the national and international stage. He reviews IEEE, ACM, Springer, Elsevier, IET and other leading publishers and has supervised three Ph.D. students.

J. Adinarayana holds Ph.D. and is working as Teaching/Research Faculty Member from 1986 and currently Institute Chair Professor of Centre of Studies in Resources Engineering (CSRE), IIT Bombay, India. His areas of expertise include agro-informatics in contemporary agriculture. As a Team Leader, he led various interdisciplinary national and international R&D projects on digital agriculture. He is the Immediate Past President of Asia-Pacific Federation for Information Technology in Agriculture (APFITA) Board and the Current President of INSAIT. He served as an Editorial Board Member of 'Regional Geoderma' (Elsevier) & CIGR journals. Currently, he is a Member, CIGR Board on Technical Section VII (IT Systems); Vice-Chair of Agriculture and Open & Sharing Data Working Groups of the Asia-Pacific Advanced Network (APAN), Expert Committee Member in various national organizations, including ICAR, ISRO, MoA&FW and DST. He is Recipient of JSPS Invitation Fellowship, DST Young Scientist Project, INSA Visiting Scientist/Faculty awards, Visiting and Adjunct Faculty/Scientist at Univ. of Tokyo (2013), Univ. of Bonn (2007), Univ. of Aston/UK (1991); Edith Cowan Univ./Perth (2010-17). He guided about 12 Ph.D.s and more than 30 M.Techs and presented research results in more than 100 research papers/book chapters in International Journals/publishers.

Sanjay Chaudhary holds Ph.D. and is Professor at the School of Engineering and Applied Science and Dean of Students of Ahmedabad University. During 2001 to 2013, he was Professor as well as Dean (Academic Programs) at Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT), Gandhinagar, India. His research areas are cloud computing, blockchain technology, big data analytics and ICT applications in agriculture and rural development. He has authored eight books and nine book chapters. He has published more than 125 research papers in international conferences, workshops and journals. He has received research grants from leading organizations including IBM, Microsoft and Department of Science and Technology, Govt. of India. He is Vice President of INSAIT. He has guided seven Ph.D. students and more than 32 M.Tech. students. He holds a doctorate degree in computer science from Gujarat Vidyapith.

Contenu
Data Science: Principles and Concepts in Data Analysis and Modelling.- Data Science: Tools, Techniques and Potential Applications in Earth Observation Studies.- Data Science in Agriculture and Natural Resource Management: An Overview.- Applications of Reinforcement Learning and Recurrent Neural Network Based Deep Learning Frameworks in Agriculture.- Precision Farming Using Emerging Technologies.- An Architecture for Quality Centric Crop Production.- Integrating UAV and Field Sensor Data for Better Decision Making in Broadacre Cropping Systems.- Object Based Crop Classification for Precision Farming.- Disruptive Innovations in Precision Agriculture - Towards BD Analytics for Better GeoFarmatics.- A Paradigm-shift in Global Cropland Maps and Products for Food and Water Security in the Twenty-first Century: Petabyte Scale Satellite Big-data Analytics, Machine Learning, and Cloud Computing.- Big Data Analytics for Climate Resilient Supply Chains: Opportunities and Way Forward.- Mapping Croplands Using Machine Learning Algorithms and Spectral Matching Techniques.- Applications of Computer Vision in Precision Agriculture.- Innovative Geoportal Platforms for Sustainable Management of Natural Resources.