Multi-Mode Surface Wave Tomography of a Water-Rich Layer of the Jizhong Depression Using Beamforming at a Dense Array

Urban structure imaging using noise-based techniques has rapidly developed in recent years. Given the complexity of the cross-correlation function in high-frequency signals, here, the beamforming (BF) method was used to analyze one data set taken from a dense array in the Jizhong Depression and obta...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Vol. 15; no. 1; p. 40
Main Authors: Wu, Qingyu, Li, Qiusheng, Hu, Xiangyun, Lu, Zhanwu, Li, Wenhui, Wang, Xiaoran, Wang, Guangwen
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-01-2023
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Summary:Urban structure imaging using noise-based techniques has rapidly developed in recent years. Given the complexity of the cross-correlation function in high-frequency signals, here, the beamforming (BF) method was used to analyze one data set taken from a dense array in the Jizhong Depression and obtain multi-mode dispersion curves. Multi-mode surface waves improved inversion stability, reduced non-uniqueness, and yielded a one-dimensional shear wave (S-wave) velocity model. Interpolation yielded a high-resolution three-dimensional (3D) S-wave velocity model for the study area. The model shows that velocity gradually changed in the horizontal direction and greatly increased in the vertical direction, which is largely consistent with changes in the sedimentary environment related to the continuous subsidence of the Jizhong Depression since the Quaternary. A low-velocity anomaly at a depth of ~300–400 m was revealed and determined to be caused by either a deep-buried ancient river course or low-lying area. This study demonstrates the potential of the BF method for processing dense array data sets of urban exploration. The high-resolution 3D S-wave velocity model provides a new reference for studying the Quaternary structure of the Jizhong Depression, as well as groundwater resources, urban infrastructure, and underground spaces.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs15010040