Multistage deep clustering of urban ambient noise for seismic imaging—a case study for train-induced seismic noise

DOI number:10.1093/gji/ggaf273

Affiliation of Author(s):中国科学技术大学地球和空间科学学院

Journal:Geophysical Journal International

Place of Publication:英国

Abstract:Passive surface wave method is increasingly being applied to urban subsurface exploration due to its non-invasiveness, low cost and high efficiency. However, its imaging quality is often influenced by limited data acquisition time and the heterogeneous distribution of seismic ambient fields in complex urban environments. To extract coherent surface wave signals for seismic imaging in such challenging setting, we developed a multistage urban ambient noise deep clustering framework based on a convolutional autoencoder and deep embedded clustering algorithm. The initial clustering characterizes t

First Author:Ke Zhao

Co-author:Feng Cheng, Jianghai Xia, Jianbo Guan,Zefeng Li

Indexed by:Journal paper

Correspondence Author:Feng Cheng

Document Code:42

Discipline:Natural Science

First-Level Discipline:Geophysics

Document Type:SCI

Volume:242

Issue:3

Page Number:ggaf273

ISSN No.:0956-540X

Translation or Not:no

Date of Publication:2025-07-18

Links to published journals:https://doi.org/10.1093/gji/ggaf273