Distributed Acoustic Sensing (DAS) effectively transforms tens of kilometers of standard fiber-optic cable into continuous, large-scale seismic sensors for the Earth and built infrastructures, delivering meter-scale spatial resolution across a broad frequency band. Emerging and rapidly maturing technologies—DAS, FBG-qDAS, DSS, and DTS—enable diverse applications in geophysical engineering, including monitoring high-rise buildings, reservoirs, bridges, tunnels, highways, railways, pipelines, power cables, nuclear plants, and AI data centers, as well as detecting subsurface subsidence, sinkholes, underground collapses, and extreme weather hazards—thereby enhancing safety, security, maintenance, and infrastructure innovation. Artificial intelligence (AI) and machine learning (ML) are essential for processing and analyzing DAS big data in geophysical engineering, enabling actionable insights and predictive models. This session invites contributions addressing all of the aspects outlined above. The outcomes are expected to significantly advance DAS applications in geophysical engineering, improving infrastructure safety and resilience while supporting the mitigation of potential geohazards.

• NH - Natural Hazards
• NS - Near Surface Geophysics
• SY - Science and Society