Shaurya Bajaj

Papers

1

Total Citations

70

H-Index

1

About

Shaurya Bajaj is a leading researcher in geospatial data science, with a primary focus on advancing forest inventory and management through cutting-edge remote sensing technologies. His work centers on the integration of unmanned aerial vehicle (UAV) platforms, including UAV-lidar and UAV structure-from-motion (SfM) data, to develop accessible and scalable methods for individual tree detection. Bajaj’s most influential contribution is his 2021 tutorial paper, which has garnered 70 citations, providing a comprehensive, beginner-friendly guide that demystifies the complex workflows of UAV-based forest analysis. This work has become a foundational resource for students and practitioners, bridging the gap between technological innovation and practical application. Beyond this, his research explores the synergy between machine learning and robotics to enhance the accuracy and efficiency of ecological monitoring. By democratizing advanced geospatial techniques, Bajaj has significantly impacted the field, empowering a new generation of researchers to leverage UAV data for sustainable forest management and biodiversity conservation.

Research Focus

Key Achievements

1
H-Index
1
Papers
70
Total Citations
70
Avg Citations/Paper
🏆 Most Cited Paper
Individual tree detection using UAV-lidar and UAV-SfM data: A tutorial for beginners
70 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 17

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago