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Room: Exhibit Hall

Date: 5/2/2024

Session Time: 8:00 AM to 5:45 PM (local time)

In light of evolving climate patterns and land-use changes, coupled with improved monitoring capabilities, we are witnessing a notable increase in detections of mass movements, such as landslides, debris and snow avalanches, lahars and glacial events. These events can pose significant hazards, and there is a pressing need to better understand, characterize and mitigate them. While these sources are not routinely monitored in real-time like earthquakes, recent advancements in seismoacoustic data and ground-based, airborne and satellite imagery offer opportunities for rapid early warning and post-event detection and analysis. These improved data sources and techniques can also help search for reliable precursors to catastrophic failure and can be used to characterize existing unstable slope instabilities. 
 
This session aims to explore innovative methods to improve our comprehension of these non-earthquake seismic sources and enhance our ability to characterize and monitor them and mitigate associated hazards. We invite presentations that investigate various types of mass movements by leveraging seismoacoustic, geodetic, and remote sensing techniques along with the application of machine learning. Topics of interest encompass but are not limited to: source detection, location, characterization, modeling and classification, precursory signal analysis, monitoring and hazard mitigation. 

Conveners:
Kate Allstadt, U.S. Geological Survey (kallstadt@usgs.gov)
Clément Hibert, University of Strasbourg (hibert@unistra.fr)
Ezgi Karasozen, Alaska Earthquake Center (ekarasozen@alaska.edu)
Liam Toney, U.S. Geological Survey (ltoney@usgs.gov)

Poster Presentations