Dr. Sartajvir Singh is an accomplished academician at Chandigarh University, specializing in Electronics and Communication Engineering. He is practicing as Registered Patent Agent (IN/PA 5806) Registered Trade Mark Agent (TMA 2646). So far, he has filed 75 innovations/patents at the Indian Patent Office (IPO) with 35 Granted/Awarded. With expertise in the filed of Remote Sensing, Computing Algorithms, and Electronics, he has published 81 in SCI/Scopus Index Journals. An active IEEE member, he engages with IEEE Young Professionals, IEEE GRSS, IEEE Sensors Council, and ISPRS. His research focuses on Remote Sensing, Machine Learning, Deep Learning, and Computer Vision. He has served as a keynote speaker and resource person for numerous workshops and webinars. He also edited 2 conference proceedings, 10 books and Special Issues with publishers like Wiley, Nature, De Gruyter, Bentham Science, Springer, Elsevier, CRC, and Apple Academic Press.
Multisensor Remote Sensing Data Fusion for Enhanced Earth Observation
Publisher: Wiley-Scrivener
Editors: Neelam Dahiya, Narayan Vyas, Sartajvir Singh, Ankit Tyagi
The book “Multisensor Remote Sensing Data Fusion for Enhanced Earth Observation” presents a comprehensive exploration of the principles, methodologies, and applications of integrating data from multiple remote sensing sensors. As Earth observation evolves, the demand for accurate, high-resolution, and timely geospatial information has increased. This has led to the adoption of advanced data fusion techniques that combine complementary strengths of diverse sensors such as optical, microwave, LiDAR, and hyperspectral systems. The book is intended to serve as a valuable reference for researchers, professionals, and students working in the field of geospatial intelligence, Earth observation, environmental monitoring, and sensor integration.
| Important Dates | |
|---|---|
| Abstract Submission Deadline | 15 August 2025 |
| Abstract Acceptance Notification | 30 August 2025 |
| Full Chapter Submission Deadline | 30 October 2025 |
| Chapter Acceptance Notification | 30 November 2025 |
| Projected Book Release Date | October 2026 |
| Important Guidelines | |
|---|---|
| Citation Style | HARVARD |
| Originality | Plagiarism Under 10%, 0% AI Generated Content |
| Text Style | 11 pt Times New Roman, 1.5 line spacing |
| Headings | 3 numbered headings (e.g. 1, 1.1, 1.1.1), one unnumbered heading |
| Figures | High-quality, original figures, 300 dpi |
Chapter 1: Fundamentals of Multisensor Remote Sensing & Earth Observation
Chapter 2: Core Principles of Sensor Fusion: Pixel-level, Feature-Level, and Decision-Level Approaches
Chapter 3: Remote Sensing Modalities and Platforms: Optical, Microwave, and Hyperspectral Sensors
Chapter 4: Preprocessing Techniques for Multisensor Geospatial Data Fusion
Chapter 5: Comparative Analysis of Single-Sensor and Multisensor Data Fusion Approaches
Chapter 6: Fusion of Optical and Microwave Data: Case Studies Using Sentinel-1 and Sentinel-2
Chapter 7: Hyperspectral–Multispectral Data Fusion for Enhanced Land Cover Classification
Chapter 8: SAR–Optical Synergy for Land Surface Mapping: Principles, Methods, and Applications
Chapter 9: Machine Learning Techniques for Multisensor Fusion: Applications in Land Cover Classification and Change Detection
Chapter 10: Deep Learning Techniques in Multisensor Fusion: Applications in Feature Extraction and Environmental Monitoring
Chapter 11: Agricultural Land Classification and Crop Monitoring Using Multisensor Remote Sensing Data
Chapter 12: Multisensor Fusion in Cryosphere: Monitoring Snow Cover, Glacial Extent, and Permafrost
Chapter 13: Urban Growth Analysis and Infrastructure Mapping Through Fusion-Based Approaches Using Google Earth Engine Remote Sensing
Chapter 14: Multisensor Data Based Land Use Land Cover Classification and Change Detection
Chapter 15: Future Perspectives and Emerging Trends in Multisensor Data Fusion for Remote Sensing
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