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Monitoring landslide disturbances using distributed acoustic sensing under extreme weather conditions

Abstract:
Extreme weather significantly challenges the effective and timely monitoring of landslide disasters. Distributed acoustic sensing (DAS) offers unique capabilities for monitoring slope failures during extreme weather events such as typhoons by transforming pre-deployed optical fiber cables into high-resolution vibration-acoustic sensor arrays. This study documents sudden shifts in landslide disturbance signals during a super typhoon’s passage using DAS with 1 Hz downsampled modulated signals. By leveraging multi-domain analysis (time-frequency-space), we identify landslide disturbance micro-deformation signatures, revealing interconnected spatial responses and dynamic patterns. We introduce a spatiotemporal indicator evaluation framework to monitor landslide occurrence and evolution under extreme weather conditions. The monitoring of landslide occurrence correlates well with post-disaster incident records and meteorological data. These results demonstrate that DAS systems can enhance early detection and high-resolution monitoring of landslide disasters under extreme weather conditions, highlighting the potential for comprehensive natural disaster management.
Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Role:
Author


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Funder identifier:
https://ror.org/01h0zpd94
Grant:
U21A20478


Publisher:
Nature Research
Journal:
npj Natural Hazards More from this journal
Volume:
3
Issue:
1
Article number:
23
Publication date:
2026-02-27
Acceptance date:
2026-02-07
DOI:
EISSN:
2948-2100
ISSN:
2948-2100


Language:
English
Keywords:
Pubs id:
2390753
Local pid:
pubs:2390753
Source identifiers:
3808273
Deposit date:
2026-02-27
ARK identifier:
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