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

Maja Pavlovic; Y Bi; Peter Nicholl

doi:10.1007/978-3-030-82147-0_32

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Knowledge Science, Engineering and Management - 14th International Conference, KSEM 2021, Proceedings
Subtitle of host publication	KSEM 2021
Publisher	Springer
Pages	394-405
Number of pages	12
Volume	12816
ISBN (Electronic)	978-3-030-82147-0
ISBN (Print)	978-3-030-82146-3
DOIs	https://doi.org/10.1007/978-3-030-82147-0_32
Publication status	Published (in print/issue) - 2021
Event	The 14th International Conference on Knowledge Science, Engineering and Management (KSEM 2021) - Tokyo, Japan Duration: 14 Aug 2021 → 16 Aug 2021 http://www.cloud-conf.net/ksem21/index.html

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	12816
ISSN (Print)	0302-9743

Conference

Conference	The 14th International Conference on Knowledge Science, Engineering and Management (KSEM 2021)
Abbreviated title	KSEM 2021
Country/Territory	Japan
City	Tokyo
Period	14/08/21 → 16/08/21
Internet address	http://www.cloud-conf.net/ksem21/index.html

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-82147-0_32

Cite this

Pavlovic, M., Bi, Y., & Nicholl, P. (2021). Extracting Anomalous Pre-earthquake Signatures from Swarm Satellite Data Using EOF and PC Analysis. In Knowledge Science, Engineering and Management - 14th International Conference, KSEM 2021, Proceedings: KSEM 2021 (Vol. 12816, pp. 394-405). (Lecture Notes in Computer Science; Vol. 12816). Springer. https://doi.org/10.1007/978-3-030-82147-0_32

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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{\textquoteright}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.",

keywords = "Empirical orthogonal function, Principal components, Geomagnetism precursors, Anomaly detection, SWARM data, Earthquakes",

author = "Maja Pavlovic and Y Bi and Peter Nicholl",

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: {\textcopyright} 2021, Springer Nature Switzerland AG.; The 14th International Conference on Knowledge Science, Engineering and Management (KSEM 2021), KSEM 2021 ; Conference date: 14-08-2021 Through 16-08-2021",

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Pavlovic, M, Bi, Y & Nicholl, P 2021, Extracting Anomalous Pre-earthquake Signatures from Swarm Satellite Data Using EOF and PC Analysis. in Knowledge Science, Engineering and Management - 14th International Conference, KSEM 2021, Proceedings: KSEM 2021. vol. 12816, Lecture Notes in Computer Science, vol. 12816, Springer, pp. 394-405, The 14th International Conference on Knowledge Science, Engineering and Management (KSEM 2021), Tokyo, Japan, 14/08/21. https://doi.org/10.1007/978-3-030-82147-0_32

Extracting Anomalous Pre-earthquake Signatures from Swarm Satellite Data Using EOF and PC Analysis. / Pavlovic, Maja; Bi, Y ; Nicholl, Peter.
Knowledge Science, Engineering and Management - 14th International Conference, KSEM 2021, Proceedings: KSEM 2021. Vol. 12816 Springer, 2021. p. 394-405 (Lecture Notes in Computer Science; Vol. 12816).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Bi, Y

AU - Nicholl, Peter

N1 - 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.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

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KW - Geomagnetism precursors

KW - Anomaly detection

KW - SWARM data

KW - Earthquakes

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DO - 10.1007/978-3-030-82147-0_32

M3 - Conference contribution

SN - 978-3-030-82146-3

VL - 12816

T3 - Lecture Notes in Computer Science

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Pavlovic M, Bi Y , Nicholl P. Extracting Anomalous Pre-earthquake Signatures from Swarm Satellite Data Using EOF and PC Analysis. In Knowledge Science, Engineering and Management - 14th International Conference, KSEM 2021, Proceedings: KSEM 2021. Vol. 12816. Springer. 2021. p. 394-405. (Lecture Notes in Computer Science). Epub 2021 Aug 7. doi: 10.1007/978-3-030-82147-0_32

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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