Research >> Mapping and Characterizing Landslides after Extreme Events
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Mapping and Characterizing Landslides after Extreme Events
Brief Description:
We conducted a one-week reconnaissance in Puerto Rico in November 2022 as part of a GEER (Geotechnical Extreme Event Reconnaissance) deployment to investigate landslides triggered by Hurricane Fiona. In collaboration with colleagues from the University of Puerto Rico and the University of Michigan, we documented over 800 precipitation-induced landslides across the island.
Our team collected a range of data, including UAV-based optical and infrared imagery to generate high-resolution 3D models of selected landslides. We also assessed rock strength at multiple sites using Schmidt hammer testing and the Geologic Strength Index (GSI), enhancing our understanding of how different geologic units influence slope failure.
These data will directly support our ongoing research, including the calibration of predictive regional landslide models. This expedition also strengthens our ability to assist local partners in improving future landslide hazard prediction and mitigation efforts.
Stratis Karantanellis taking Schmidt hammer measurements
Massive deep-seated rainfall-induced landslide
Drew Gomberg flying the Phantom RTK drone to map a landslide in Ponce
Spheroidal Weathering
A classical landslide, illustrating typical features such as a scarp, distinct failure surface, and displaced mass.
Weathered bedrock outcropping at the surface (Photo taken by drone).
A similar one-week field deployment, sponsored by NASA, was carried out in May 2022 to collect data on landslides triggered by Hurricane Maria in 2017 and the 2020 Puerto Rico earthquake.
Conducting MASW survey in the field to measure shear wave velocity.
Prof. Stephen Hughes taking Scmidt hammer measurements
GPS unit used during the Electromagnetic (EM) survey conducted by Parker Blunts
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