0000-0001-6560-8621 About
Dr. Rakesh Sahu is a dedicated academician and researcher with expertise in Geographic Information Systems (GIS), remote sensing, and climate change studies, particularly focusing on Himalayan glacier dynamics. His academic journey includes a Ph.D. in GIS from Motilal Nehru National Institute of Technology (MNNIT), Allahabad, an M.Tech. in Geoinformatics from Maulana Azad National Institute of Technology (MANIT), Bhopal, and a B.E. in Computer Science from Technocrats Institute of Technology, Bhopal. With over a decade of professional experience, He has made significant contributions as a Post-Doctoral Scholar at IIT Bombay and as a faculty member at esteemed institutions such as Chandigarh University, Galgotias University, Amity University, and ITM University. His research focuses on glacier mapping, modelling, and climate change. His Ph.D. work on mapping and monitoring glaciers in the Chandra Basin of the Western Himalayas has been pivotal in understanding the region's cryosphere.
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Publications (16)
- Towards Frequent Flood Inundation Monitoring Using AI and EO Save
- Deep-learning-based streamflow prediction in monsoon rainfall-dominated catchment under projected climate scenarios for water resource management Save
- Conventional and deep learning approaches for glacial lake mapping using remote sensing data: a comprehensive review Save
- Multi-parametrical analysis of Haptal glacier, lower Chenab basin, Jammu and Kashmir, India: A remote sensing approach Save
- Two Decades of Glacier and Glacial Lake Change in the Dhauladhar Mountain Range, Himachal Himalayas, India (2000–2020) Save
- Four decades of Glacier and Glacial Lake dynamics in Kishtwar high altitude National Park, Chenab Basin, Jammu and Kashmir, India Save
- Long-term annual and seasonal mass balance reconstruction and sensitivity analysis of Chhota Shigri Glacier in Western Himalaya Save
- Evolution of Supraglacial Lakes from 1990 to 2020 in the Himalaya–Karakoram Region Using Cloud-Based Google Earth Engine Platform Save
- Machine-learning- and deep-learning-based streamflow prediction in a hilly catchment for future scenarios using CMIP6 GCM data Save
- Challenges in Understanding the Variability of the Cryosphere in the Himalaya and Its Impact on Regional Water Resources Save