Journal of Engineering, Technology, and Applied Science (JETAS)
Vol 7 No 3: December 2025

Multi-Station ULF Geomagnetic Analysis for Enhanced Earthquake Precursor Identification

Winata, Eresia Nindia (Unknown)
Syamsu Rosid, Mohammad (Unknown)
Febriani, Febty (Unknown)



Article Info

Publish Date
28 Dec 2025

Abstract

Western Java’s ongoing seismic hazard highlights the need for understanding earthquake precursor mechanisms. Recent studies have increasingly focused on ultra-low-frequency (ULF) signals that may carry information related to pre-seismic phases. However, a key difficulty persists: isolating faint, localized lithospheric signals from the stronger ionospheric activity. Most previous investigations in Western Java have relied on single-sensor measurements, a limitation that complicates the detection of true anomalies. This study addresses this limitation by examining daily ULF variations before the 2023 Banten earthquake sequence (M5.4 and M5.1), using a multi-point setup to distinguish lithospheric signals from stronger background ionospheric noise. Continuous three-component geomagnetic data from two primary stations near the epicenter, Serang (SRG) and Sukabumi (SKB), and a distant reference station (TRD) in East Kalimantan were analyzed. The Z/G spectral density ratio was calculated in the 0.01–0.09 Hz range, using only data from quiet nighttime intervals (15:00–21:00 UTC) and magnetic storm-free days (Dst > -50 nT). The results identified and filtered false positive anomalies by correlating them with signals at the TRD reference station. Two distinct, validated pre-seismic anomalies were identified, concentrated in the 0.04–0.08 Hz band: a multi-station anomaly at H-20 (at SRG and SKB) and a localized, broadband anomaly at H-15 (at SRG). Both emissions were absent at TRD, confirming their lithospheric origin. These results highlight the importance of a multi-station approach for reliably identifying lithospheric ULF anomalies. However, this study is limited to a specific event sequence. Future investigations should focus on integrating broader sensor networks and ionospheric models across multiple seismic events to validate these findings globally and enhance false positive rejection methods.

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Journal Info

Abbrev

jetas

Publisher

Subject

Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Physics

Description

The aim of this journal is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of Engineering, Technology and Applied Science. Subject areas cover, but not limited to Physics, Chemistry, Biology, Environmental Sciences, Geology, Engineering, ...