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Room: Ballroom F

Date: 4/16/2026

Session Time: 8:00 AM to 9:15 AM (local time)

Data-Driven and Computational Characterization of Non-Earthquake Seismoacoustic Sources

Non-earthquake seismoacoustic sources, such as landslides, avalanches, volcanoes, glacial calving, utilities and industrial blasts, bolide airburst and their impacts on Earth, are commonly recorded by seismoacoustic monitoring networks. This session focuses on data-driven and computational methods and algorithms that aim to better understand and characterize these non-earthquake sources, and to ultimately better monitor and mitigate their associated hazards. We encourage contributions from studies that include, but are not limited to, seismoacoustic, geodetic and remote sensing techniques at all relevant spatiotemporal scales with emphasis on multisensors Bayesian & Dempster-Shafer statistical data integration and fusion, high-performance deterministic and stochastic computational modeling and simulation, and AI-driven and physics-informed ML techniques. We solicit studies that include, but are not limited to, source detection, location, characterization, modeling, classification, monitoring and hazard mitigation.

Conveners

Souheil M. Ezzedine, Lawrence Livermore National Laboratory (ezzedine1@llnl.gov)
Keehoon Kim, Lawrence Livermore National Laboratory (kim84@llnl.gov)
Benjamin L. Moyer, University of Maryland (blmoyer@umd.edu)

Oral Presentations