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Room: Exhibit Hall

Date: 4/15/2025

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

Fiber-optic Sensing Applications in Seismology

Fiber-optic sensing methods, such as Distributed Acoustic Sensing (DAS), Distributed Temperature Sensing (DTS), and Distributed Strain Sensing (DSS), are transforming seismology by advancing our understanding of seismic sources and Earth's structure. These innovative technologies convert fiber-optic cables into dense sensor arrays capable of capturing seismic and deformation signals across the solid Earth, oceans, and glaciers with unprecedented resolution. We invite contributions on recent developments in fiber-optic seismology applications, including but not limited to the detection and characterization of various seismic sources (e.g., earthquakes, icequakes, volcanic activities, ocean processes, atmospheric phenomena, energy extraction and storage activities, and anthropogenic signals), Earth's structure imaging (e.g., urban setting, offshore, and cryosphere), environmental monitoring (e.g., the dynamics of oceans, rivers, lakes, critical zones, soil moisture, groundwater, permafrost, and glaciers), and natural hazard mitigation (e.g., earthquake, tsunami, and volcanic eruption monitoring and early warning). We also welcome recent engineering advancements in the theoretical, methodological, and instrumental aspects of fiber-optic sensing for future Earth and planetary applications. Contributions from the computational and data science communities focused on exploring fiber-optic data are encouraged, including areas such as machine learning, advanced signal processing techniques, data compression, high-performance computing, and cloud computing and storage. We aim to bring together researchers from diverse fields, including Earth science, computational and data science, and fiber-optic sensing engineering to open a discussion on the future opportunities enabled by these new technologies.

Conveners 

Ettore Biondi, Stanford University, California Institute of Technology (ebiondi@caltech.edu)
Xiaowei Chen, Texas A&M University (xiaowei.chen@tamu.edu)
Jiaxuan Li, University of Houston (jli74@uh.edu) 
Yan Yang, University of California San Diego (yanyang@ucsd.edu) 
Qiushi Zhai, California Institute of Technology (qzhai@caltech.edu) 

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