- Related Research Areas
- Earth Surface & Interior
Landslides are a significant natural hazard, yet the models that are used to assess landslide risk are limited by the fact that they model landslides as static, time invariant objects, they do not predict landslide movements, and they do not consider the external factors that trigger movements. The objective of this project is to advance the time domain modeling of landslides hazards through the use of remotely sensed observations of landslide movements. Observed landslide movements will be combined with finite element / finite difference modeling and empirical modeling to improve numerical predictions of landslide movements and their relation to external triggering factors. Ultimately, the results of this study will advance our ability to model the time evolution of landslide movements, lead to more accurate predictions of landslide occurrence, and reduce landslide risk. This project will involve using radar interferometry (InSAR) and optical imagery correlation to monitor landslide movements at landslide sites in California and integrating these data into detailed analytical models of landslides. X-, C- and L-band InSAR will be utilized in an effort to investigate trade-offs related to higher spatiotemporal resolution (X-band) versus minimizing sources of decorrelation (L- and C-band) in InSAR analyses. Movements from optical imagery correlation will complement movements derived from InSAR, particularly in cases where movements are large enough to cause decorrelation in the InSAR data. Understanding natural hazards represents a significant challenge that has been given high priority by the SESWG in its strategic plan for the Earth Surface and Interior focus area. This research responds directly to this challenge by integrating remote sensing-derived observations of landslide movements with detailed numerical modeling in an effort to develop models that can predict the future occurrence of landslides. Ultimately, the results of this study will lead to more accurate predictions of landslide movements and reduce landslide risk.
Project PI: Ellen Rathje/University of Texas
The University of Texas at Austin Civil, Architectural and Environmental Engineering Department-GEO 1 University Station C1792 Austin, TX 78712-0273
Phone: (512) 232-3683
Fax: (512) 471-6548
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