The Remote Sensing-Earth Surface Processes group at Universität Potsdam investigates the physical, climatic, and environmental controls that shape our world. We work across a range of spatial and temporal scales, running from examining sub-annual, sub-centimeter deformation with Synthetic Aperture Radar, to regional controls on continental-scale topography over decades using satellite climate data and digital elevation models, to millennial estimations of sediment transport and erosion from cosmogenic-radio nuclides (CRN). Likewise, in our research, we employ a broad range of datasets, including space-based optical, multi-spectral, synthetic aperture radar, and passive microwave data; point-could data collected from ground and airborne LiDAR and structure-from-motion; and field data collected from around the world.
Our research methods emphasize data-driven approaches, particularly those which take advantage of the rapidly increasing array of earth remote sensing datasets. Some recent publications exploiting advances in remotely sensed observations have focused on error propagation and quantification in high-resolution topographic datasets, extreme hydro-meteorological event analysis, long-term trend analysis in snow time series, and natural hazard damage detection. In addition to our state-of-the-art computing infrastructure, our group hosts a clean lab for the extraction of cosmogenic radio nuclides (CRN, Be-10 and Al-26 on quartz) for long-term estimation of surface transport rates and precise exposure dating. Current and past members of our group have employed terrestrial and meteoric Be-10, He-3, Cl-36, and Al-26 to quantify how complex systems such as monsoons and glaciations shape mountain ranges.
Our group is diverse and international, with PhD students and researchers from several countries, and scientific backgrounds ranging from network physics, to meteorology, to tectonic geomorphology. We are always interested in research collaborations, both from within the geosciences and from neighboring disciplines.