Year: 2025
Type: article
Abstract: With the continuous development of cities and the increasing utilization of underground space, ambient noise seismic imaging has become an essential approach for exploring and monitoring the urban subsurface. The integration of Distributed Acoustic Sensing (DAS) with ambient noise imaging offers a more convenient and effective solution for investigating shallow subsurface structures in urban environments. To overcome the limitations of conventional ambient noise seismic nodes, which are costly and incapable of achieving high-density data acquisition, this work makes use of existing urban telecommunication fibers to record ambient noise and perform sliding-window cross-correlation on it. Then the Phase-Weighted Stack (PWS) technique is applied to enhance the quality and stability of the cross-correlation signals, and fundamental-mode Rayleigh wave dispersion curves are extracted from the cross-correlation functions through the High-Resolution Linear Radon Transform (HRLRT). In the inversion stage, an adaptive regularization strategy based on automatic L-curve corner detection is introduced, which, in combination with the Preconditioned Steepest Descent (PSD) method, enables efficient and automated dispersion inversion, resulting in a well-resolved near-surface S-wave velocity structure. The results indicate that the proposed workflow can extract useful surface-wave dispersion information under typical urban noise conditions, achieving a feasible level of subsurface velocity imaging and providing a practical technical means for urban underground space exploration and utilization.
Source: Applied Sciences
DOI: 10.3390/app152413145
Authors: Yanzhe Zhang, Cai Liu, Jing Li, Qi Lu
Institution: Jilin University
Language: English
Topic: Seismic Waves and Analysis
Subfield: Geophysics
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Award: G813177705
OpenAlex ID: W7115177226
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