David Shean Research Group

University of Washington

How can satellite, airborne, UAV, and terrestrial remote sensing be combined to quantify glacier and snow dynamics across mountain and polar regions? The group develops SlideRule Earth, a cloud-based on-demand framework to process ICESat-2 laser altimetry data into high-level elevation point-cloud products for rapid algorithm development. Researchers design and evaluate stereo+lidar fusion algorithms and on-board pointing/information systems to improve precision of stereo and lidar datasets for NASA STV mission requirements. The lab applies multi-sensor deep learning fusion, radiative transfer simulations (DART), and joint optimization routines to increase vertical accuracy and uncertainty characterization in stereo+lidar products. The group evaluates commercial smallsat, Planet, SkySat, BlackSky, and Capella datasets to capture high-resolution cryosphere dynamics and map snow and glacier changes.