Unsupervised Deep Clustering of Microseismic Signals from the Dalk Glacier in East Antarctica

DOI number:10.1785/0220250052

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

Journal:Seismological Research Letters

Place of Publication:美国

Abstract:In Antarctica, seismic monitoring and detection is significant for understanding long-term glacier activity, glacial melting, and other related scientific issues. We deployed 8 three-component short-period seismometers near the grounding line of the Dalk Glacier ice tongue in Southeast Antarctica, collecting seismic signals from 19 October 2022 to 28 February 2023. We applied unsupervised deep learning, using an autoencoder to encode the features of the input spectrograms into low-dimensional latent vectors, which were then input into a Gaussian mixture model for clustering. We ultimately iden

First Author:Lei Zhao

Co-author:Lei Fu, Jingxue Guo, Yanlan Hu,Zefeng Li, Kai Lu, Ruijia Wang, Xiangyun Hu

Indexed by:Journal paper

Correspondence Author:Lei Fu

Document Code:45

Discipline:Natural Science

First-Level Discipline:Geophysics

Document Type:SCI

Volume:97

Issue:1

Page Number:425-438

ISSN No.:0895-0695

Translation or Not:no

Date of Publication:2025-08-27

Links to published journals:https://doi.org/10.1785/0220250052