Modeling within our group includes analog experiments and geophysical simulations of geologic processes, ranging from the flow of lava, impact melts, and glaciers to stuctural and tectonic modeling of fault systems within planetary bodies.
Machine learning provides a powerful framework for cluster analysis and computer vision, which we employ to quantify the spatial organization of geological features on terrestrial bodies and enable automated landform identification and change detection.
The remote sensing focus within our group includes ground-, aerial-, and satallite-based imaging systems, which are used to establish precision topogaphic measurements using photogrammety and Geographic Information Systems (GIS). In addition to the use of visible imagery fo geomorphological studies and planetary analog research, our group utlizies ground-based Forward Looking Infrared Imager (FLIR) data and near-Infrared satellite imagery to quanitfy the thermodynamics of active volcanic processes.
Field observations provide vital information about the geologic processes operating on the Earth and other planetary bodies through time. Our field work combines classical approaches with geodetic measurements and state-of-the-art imaging systems to inform and constrain geophysical models for planetary analog research.
