Remote Sensing of Permafrost Thaw and Carbon Dynamics

This project aims to develop remote sensing and data-driven approaches for monitoring permafrost thaw and quantifying its impacts on carbon dynamics, with a primary focus on the Qinghai–Tibet Plateau. Advanced machine learning methods will be employed to generate long-term, large-scale products describing permafrost disturbance and associated environmental changes. The resulting datasets and analytical framework will provide new insights into the interactions among permafrost degradation, hydrology, vegetation recovery, and carbon cycling.