Urban Subsurface Seismic Imaging Using Ambient Noise and Dark Fiber Distributed Acoustic Sensing in Istanbul

Urban areas are highly vulnerable to geohazards due to their dense populations and infrastructure, often resulting in severe consequences for human life and economic stability. Improving our understanding of near-surface and shallow subsurface structures in urban environments is therefore essential for effective seismic hazard assessment and risk mitigation. However, conventional geophysical surveys in cities are frequently limited by logistical constraints. In this context, repurposing existing telecommunication optical fibers (so-called dark fibers) as dense seismic sensing arrays using Distributed Acoustic Sensing (DAS) offers a powerful alternative for urban subsurface investigations.The megacity of Istanbul (Turkey) is located in one of the most tectonically active regions worldwide and is exposed to significant seismic hazard. Since May 2024, we have been continuously recording passive seismic data using DAS along an amphibious fiber-optic cable deployed in the urban district of Kartal (eastern Istanbul) and extending offshore. In this study, we focus on one month of data acquired along a 3 km-long urban segment of the fiber.
Here, we exploit high-frequency urban noise for passive seismic interferometry. We analyze ambient seismic noise primarily generated by anthropogenic sources, such as urban traffic, in a frequency range up to 12Hz. We adapt ambient noise interferometry processing strategies to address the challenges posed by dense urban environments and DAS array geometries, including the selection of suitable fiber sections, channels, and source–receiver configurations. First, we retrieve high-frequency surface waves along different segments of the fiber. Then, we use these arrivals within an Eikonal tomography framework to map local phase velocities. Finally, we invert the surface-wave dispersion to constrain the shallow subsurface velocity structure, contributing to a better understanding of shallow structures and material properties relevant to seismic hazard assessment. Ultimately, this work aims to establish efficient methodologies for imaging the urban subsurface using existing infrastructure.