Biography
Shagun Garg is a PhD researcher at the University of Cambridge, where he works at the intersection of satellite remote sensing and water management. His research focuses on applying Earth observation data and machine learning to tackle water-related challenges, including groundwater depletion, flooding, and the monitoring of nature-based solutions.
His interest in satellite applications began at IIT Bombay and Leibniz University Hannover (supported by a DAAD fellowship), where he studied land subsidence in Delhi linked to excessive groundwater extraction. This work sparked a lasting curiosity about how satellite data can help track human impacts on the environment.
Shagun later joined GFZ Potsdam, where he developed new methods to improve flood detection using radar imagery. His work aimed to enhance flood mapping in areas where conventional approaches often struggle, especially in complex or data-scarce regions.
At Cambridge, Shagun’s current research centres on using satellite data to monitor the long-term effectiveness of nature-based solutions such as ponds, lakes, and wetlands. By combining EO data with hydrological insights, he hopes to support more resilient and sustainable approaches to water management.
In addition to his research, Shagun contributes as a peer reviewer for journals including Nature Communications Earth & Environment, Remote Sensing of Environment, and ISPRS Journal of Photogrammetry and Remote Sensing. He is also part of the United Nations University’s NEXUS AID initiative, contributing to educational efforts on landslides and land subsidence.
Driven by a commitment to open science and practical impact, Shagun is particularly interested in making satellite-based tools more accessible for researchers, practitioners, and communities working to solve pressing water challenges
