Dando, Ben D. E. and Goertz-Allmann, Bettina P. and Brissaud, Quentin and Köhler, Andreas and Schweitzer, Johannes and Kværna, Tormod and Liashchuk, Alexander (2023) Identifying attacks in the Russia–Ukraine conflict using seismic array data. Nature, 621 (7980). pp. 767-772. ISSN 0028-0836
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Abstract
Seismometers are generally used by the research community to study local or distant earthquakes, but seismograms also contain critical observations from regional1,2 and global explosions3, which can be used to better understand conflicts and identify potential breaches of international law. Although seismic, infrasound and hydroacoustic technology is used by the International Monitoring System4 to monitor nuclear explosions as part of the Comprehensive Nuclear-Test-Ban Treaty, the detection and location of lower-yield military attacks requires a network of sensors much closer to the source of the explosions. Obtaining comprehensive and objective data that can be used to effectively monitor an active conflict zone therefore remains a substantial challenge. Here we show how seismic waves generated by explosions in northern Ukraine and recorded by a local network of seismometers can be used to automatically identify individual attacks in close to real time, providing an unprecedented view of an active conflict zone. Between February and November 2022, we observed more than 1,200 explosions from the Kyiv, Zhytomyr and Chernihiv provinces, providing accurate origin times, locations and magnitudes. We identify a range of seismoacoustic signals associated with various types of military attack, with the resulting catalogue of explosions far exceeding the number of publicly reported attacks. Our results demonstrate that seismic data can be an effective tool for objective monitoring of a continuing conflict, providing invaluable information about potential breaches of international law.
Item Type: | Article |
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Subjects: | STM Academic > Multidisciplinary |
Depositing User: | Unnamed user with email support@stmacademic.com |
Date Deposited: | 14 Nov 2023 07:38 |
Last Modified: | 14 Nov 2023 07:38 |
URI: | http://article.researchpromo.com/id/eprint/1794 |