Geospatial Intelligence in Precision Agriculture

To secure the future of global food systems in an era of climate disruption, this comprehensive, hands-on reference equips you with the cutting-edge geospatial intelligence and AI tools needed to build highly profitable, sustainable, and climate-resilient farms.

With a growing population, rising demand for food, and accelerating climate change, geospatial intelligence is reshaping how the world farms. This book delivers a comprehensive, hands-on guide to modern precision agriculture, bringing together the core enabling technologies of remote sensing, GIS, IoT, artificial intelligence, and cloud-based earth-observation platforms into one practical, decision-focused reference. From planting to harvest, readers see how location-aware data and smart sensors are used to monitor crops, manage irrigation, assess soil health, classify land use, and quantify environmental impact with a resolution and speed that traditional methods cannot match.

Across eighteen carefully sequenced chapters, the book moves from foundations to frontier applications. Each chapter is grounded in real-world case studies that show how these tools are already being deployed across emerging agricultural economies. The book ends with a forward look at AI-driven analytics, multisensor fusion, and cloud technologies that will define the next decade. The result is a single, authoritative volume for students, researchers, agri-tech innovators, and policy professionals who want to understand and apply geospatial intelligence to build farming systems that are productive, profitable, and sustainable.

Gurwinder Singh, PhD works with the School of Advanced Computing and the Advanced Centre of Research and Innovation at Chandigarh Group of Colleges University, Mohali, Punjab, India. He is a recipient of the Young Scientist Award and a member of the International Society for Photogrammetry and Remote Sensing. His research focuses on remote sensing, agricultural land-use classification, machine learning, and deep learning.

Vishakha Sood, PhD is a Project Scientist in the Centre of Excellence SEnSRS at the Indian Institute of Technology Ropar. She holds a PhD from Chitkara University and is the founder of Aiotronics Automation Pvt. Ltd. Her research focuses on satellite sensors, remote sensing, and digital image analysis.

Narayan Vyas is with the Department of Computer Science and Engineering at Vivekananda Global University. He has authored more than 60 research publications and edited more than ten books. His research focuses on remote sensing, IoT, machine learning, deep learning, and computer vision.

Surendra Yadav, PhD is with the Department of Computer Science and Engineering at Vivekananda Global University, Jaipur, Rajasthan, India with more than 20 years of experience. He has led GIS-based projects for the Karnataka and Delhi Agricultural Marketing Boards and the National Institute of Agriculture Marketing. He has more than 50 publications spanning remote sensing, GIS, cloud computing, and data mining.

Dankan Gowda V., PhD is an Assistant Professor in the Department of Electronics and Communication Engineering at the BMS Institute of Technology and Management, Bangalore, India. He brings 15 years of teaching and industry experience, including roles at ADA-DRDO and Robert Bosch. His research focuses on IoT and signal processing, with more than 100 international publications and six granted patents.