Song Shu

Song Shu is a Senior Professor at Appalachian State University. His research centers on remote sensing, earth observation, and environmental monitoring, with a specific focus on integrating geographic information systems, hydrology, and planetary sciences. His latest work includes developing the RS-WaterQuality Mapper, an open-source QGIS toolbox for water quality assessment, and the DeepSAR Flood Mapper, which employs deep learning on Google Earth Engine for global flood mapping. He has also pioneered methods for continuous shallow water bathymetry using Kriged Kalman Filters and for predicting daily lake surface topography by integrating SWOT swath data with multi-mission satellite altimetry. His recent publications also explore snow's impact on vegetation green-up dynamics on the Tibetan Plateau and the spatial transferability of water quality inversion models for inland lakes.