Shi Qiu (邱实), Ph.D.

I am an Assistant Research Professor in the Department of Natural Resources and the Environment at the University of Connecticut.

My research focuses on land change science and remote sensing algorithm development, with the broader goal of understanding how human activities and natural processes interact to shape Earth’s surface. To achieve this, I develop physics-informed AI methods and time-series approaches in three main directions: (1) enhancing cloud and shadow detection to improve the reliability of optical satellite imagery, (2) advancing multi-sensor integration and compositing for consistent long-term monitoring, and (3) developing retrospective methods and products to detect and characterize land disturbances and their causal agents. By quantifying and characterizing human-driven and natural disturbances across spatial and temporal scales, my work provides a framework for understanding the coupled dynamics of socio-ecological systems under global change. I have published more than 25 peer-reviewed articles in journals such as Nature Geoscience and Remote Sensing of Environment, with over 2,000 citations (Google Scholar, August 2025). Several of my algorithms and reports, including Fmask V4/5 and the Landsat 7 orbit analysis, have been operationally adopted or highlighted by NASA HLS, USGS, and Google Earth Engine.