Title

Interpreting Landslide Kinematics and Failure Transitions Using Geotechnical Modeling and Remote Sensing

Speaker

Dr. Xiang Li, Assistant Professor, Department of Geological and Mining Engineering Science, Michigan Technological University

Abstract

In recent years, severe storms driven by climate change have become more frequent globally, exacerbating natural hazards and threatening infrastructure safety. Meanwhile, remote sensing techniques such as Interferometric Synthetic Aperture Radar (InSAR) have been developed to a stage where they are capable of effectively measuring ground deformation with high precision, down to millimeter-scale. This advancement offers valuable opportunities to interpret the hydromechanics of earth materials, thereby aiding in the prediction of landslide catastrophic failures. In this talk, I will present a modelling framework to investigate the interaction between the hydraulic and mechanical behaviors of earth materials and their impact on geosystems. Emphasis will be placed on the integration of geotechnical modelling and InSAR remote sensing techniques to simulate the velocity changes in slow-moving landslides, and to further explore their potential to exhibit catastrophic acceleration.

Bio

Xiang Li is an Assistant Professor in the Department of Geological and Mining Engineering and Science at Michigan Technological University, In recent years, severe storms driven by climate change have become more frequent globally, exacerbating natural hazards and threatening infrastructure safety. Meanwhile, remote sensing techniques such as Interferometric Synthetic Aperture Radar (InSAR) have been developed to a stage where they are capable of effectively which he joined in 2024. He received his PhD in 2022 in Civil Engineering from Northwestern University. His primary research interest is Geological/Geotechnical modeling, with emphasis on the study of landslide dynamics triggered by precipitation. Before joining Michigan Tech, he was a Postdoctoral Scholar at University of California, Los Angeles. At UCLA, he has broadened his expertise by guiding his expertise by guiding the development of geomechanics models on the basis of large datasets acquired via InSAR remote sensing. This approach not only allows him to obtain large-scale ground deformation data to train and improve the models, but also offers opportunities for future applications in soil-structure interaction and coastal infrastructure resilience.