Generalizing and quantifying geohazards and Earth surface processes are challenging due to the stochastic nature of the environment. The unprecedented high-accuracy and high-resolution remote sensing and environmental datasets from the ground, air, and space empower the human to identify the natural or anthropogenic driving mechanisms of Earth processes and their responsiveness to environmental variabilities. As an active remote sensing tool, Synthetic Aperture Radar (SAR) has been widely used to monitor the spatiotemporal ground deformations and land alterations. A joint analysis of geodetic observations, hydroclimatic data, and geological records, together with hybrid data processing methods, cross-disciplinary statistical, analytical, and numerical models, as well as machine learning framework, allow us to rely on SAR-derived spatiotemporal displacements to explicitly quantify the kinematics and dynamics of our planet in various landscapes and geodynamic settings such as landslides, aquifers, coasts, earthquakes, and critical infrastructures.
Host: Jeff Catalano
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