Extracting Anomalous Pre-earthquake Signatures from Swarm Satellite Data Using EOF and PC Analysis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The goal of this work is to utilize the General Empirical Orthogonal Function (EOF) and Principal Component Analysis (PCA) to detect potential earthquake pre-cursory variations in Earth’s ionosphere-lithosphere geomagnetic system and observe their spatial-temporal signatures along seismotectonic fault lines. Two major earthquake episodes in China have been selected for this study: an M6.0 earthquake, which occurred on 19th January 2020 at ENE of Arzak, and another M6.3 earthquake, occurring on 22nd July 2020 in western Xizang. The spatial-temporal variability patterns in an ~ 800 km radius of earthquake epicentres were calculated from geomagnetic data recorded by SWARM satellites A, B and C. The results of EOF spatial components and associated time-series principal components (PCs) revealed anomalous patterns along and on borders of the local tectonic fault lines and around earthquake epicentres. The Planetary A and K geomagnetic storm indices did not show abnormal activities around the same time periods. This could suggest a pre-cursory connection between the detected geomagnetic anomalies and these earthquakes.
Original languageEnglish
Title of host publicationKnowledge Science, Engineering and Management - 14th International Conference, KSEM 2021, Proceedings
Subtitle of host publicationKSEM 2021
PublisherSpringer
Pages394-405
Number of pages12
Volume12816
ISBN (Electronic)978-3-030-82147-0
ISBN (Print)978-3-030-82146-3
DOIs
Publication statusPublished (in print/issue) - 2021
EventThe 14th International Conference on Knowledge Science, Engineering and Management (KSEM 2021) - Tokyo, Japan
Duration: 14 Aug 202116 Aug 2021
http://www.cloud-conf.net/ksem21/index.html

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume12816
ISSN (Print)0302-9743

Conference

ConferenceThe 14th International Conference on Knowledge Science, Engineering and Management (KSEM 2021)
Abbreviated titleKSEM 2021
Country/TerritoryJapan
CityTokyo
Period14/08/2116/08/21
Internet address

Bibliographical note

Funding Information:
Acknowledgment. This work is partially supported by the project of “Seismic Deformation Monitoring and Electromagnetism Anomaly Detection by Big Satellite Data Analytics with Parallel Computing” (ID: 59308) under the Dragon 5 program, a largest cooperation between European Space Agency and Ministry of Science and Technology of China.

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

  • Empirical orthogonal function
  • Principal components
  • Geomagnetism precursors
  • Anomaly detection
  • SWARM data
  • Earthquakes

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