Narayan Vyas, an academician at Vivekananda Global University, specializes in computer science, focusing on IoT and Mobile App Development. He has trained over 1000 students globally and published extensively in Scopus journals. An active IEEE member, his research interests include Remote Sensing, Machine Learning, and Computer Vision.
Geospatial Intelligence in Precision Agriculture: Sustainable Practices, Technologies and Business Models
Publisher: Wiley-Scrivener
Editors: Gurwinder Singh, Vishakha Sood, Narayan Vyas, Surendra Yadav, Dankan Dowda V
This book delves into the transformative role of geospatial intelligence in modern agriculture, covering key technologies like remote sensing, GIS, IoT, and AI. It highlights their applications in crop monitoring, irrigation management, soil health assessment, and environmental impact, supported by real-world case studies. With a focus on sustainability and economic benefits, the book explores data acquisition challenges, market dynamics, and future trends in precision agriculture, offering valuable insights for students, researchers, and professionals in agricultural technology and geospatial solutions.
| Important Dates | |
|---|---|
| Abstract Submission Deadline | 30 October 2024 |
| Abstract Acceptance Notification | 30 November 2024 |
| Full Chapter Submission Deadline | 30 December 2024 |
| Chapter Acceptance Notification | February 2025 |
| Projected Book Release Date | July 2025 |
| Important Guidelines | |
|---|---|
| Citation Style | IEEE |
| Formatting | 11 pt Times Roman, 1.5 line spacing |
| Originality | Plagiarism Under 10%, 0% AI Generated Content |
| Headings |
|
Chapter 1: Introduction to Geospatial Intelligence and Precision Agriculture
Chapter 2: The Role of Geospatial Intelligence in Agricultural Innovations
Chapter 3: Data Acquisition and Sensing Technologies in Geospatial Intelligence
Chapter 4: Integrating Satellite Imaging with Geospatial Intelligence for Sustainable Agriculture
Chapter 5: Optimizing Irrigation Efficiency through GIS and Precision Mapping
Chapter 6: Real-Time Crop Management with IoT Sensors and Geospatial Technologies
Chapter 7: Advancements in Agricultural Classification Using Geospatial Intelligence
Chapter 8: Geospatial Intelligence-Based Environmental Impact Assessment
Chapter 9: LiDAR Technology in Precision Agriculture: Applications and Benefits
Chapter 10: Multi-Sensor Data Fusion for Enhanced Agricultural Decision-Making
Chapter 11: Land Use and Land Cover Mapping for Sustainable Agriculture
Chapter 12: Global Market Dynamics in Geospatial Intelligence-Enabled Farming
Chapter 13: Economic Impacts of Geospatial Intelligence on Sustainable Farming
Chapter 14: Innovative Business Models for Geospatial-Enabled Agricultural Solutions
Chapter 15: Future Directions and Challenges for Geospatial Intelligence-Based Precision Agriculture
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