Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms
Volcanic tremor signals are usually observed before or during volcanic eruptions andmust be monitored to evaluate the volcanic activity. A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating trans...
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ftgfzpotsdam:oai:gfzpublic.gfz-potsdam.de:item_5008179 2023-10-09T21:52:50+02:00 Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms Zali, Z. Ohrnberger, M. Scherbaum, F. Cotton, F. Eibl, E. 2021 application/pdf https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008179 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008179_3/component/file_5022679/5008179.pdf eng eng info:eu-repo/semantics/altIdentifier/doi/10.1785/0220210016 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008179 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008179_3/component/file_5022679/5008179.pdf info:eu-repo/semantics/openAccess Seismological Research Letters info:eu-repo/semantics/article 2021 ftgfzpotsdam https://doi.org/10.1785/0220210016 2023-09-24T23:43:20Z Volcanic tremor signals are usually observed before or during volcanic eruptions andmust be monitored to evaluate the volcanic activity. A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating transient events fromvolcanic tremors can, therefore, contribute to improving upon our understanding of the underlying physical processes. Exploiting the idea of harmonic–percussive separation in musical signal processing, we develop a method to extract the harmonic volcanic tremor signals and to detect transient events from seismic recordings. Based on the similarity properties of spectrogram frames in the time–frequency domain, we decompose the signal into two separate spectrograms representing repeating (harmonic) and nonrepeating (transient) patterns, which correspond to volcanic tremor signals and earthquake signals, respectively. We reconstruct the harmonic tremor signal in the time domain from the complex spectrogram of the repeating pattern by only considering the phase components for the frequency range in which the tremor amplitude spectrum is significantly contributing to the energy of the signal. The reconstructed signal is, therefore, clean tremor signal without transient events. Furthermore, we derive a characteristic function suitable for the detection of transient events (e.g., earthquakes) by integrating amplitudes of the nonrepeating spectrogram over frequency at each time frame. Considering transient events like earthquakes, 78% of the events are detected for signal-to-noise ratio = 0.1 in our semisynthetic tests. In addition, we compared the number of detected earthquakes using our method for one month of continuous data recorded during the Holuhraun 2014–2015 eruption in Iceland with the bulletin presented in Ágústsdóttir et al. (2019). Our single station event detection algorithm identified 84% of the bulletin events. Moreover, we detected a total of 12,619 events, which is more than twice the number ... Article in Journal/Newspaper Iceland GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam) Holuhraun ENVELOPE(-16.831,-16.831,64.852,64.852) Seismological Research Letters |
institution |
Open Polar |
collection |
GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam) |
op_collection_id |
ftgfzpotsdam |
language |
English |
description |
Volcanic tremor signals are usually observed before or during volcanic eruptions andmust be monitored to evaluate the volcanic activity. A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating transient events fromvolcanic tremors can, therefore, contribute to improving upon our understanding of the underlying physical processes. Exploiting the idea of harmonic–percussive separation in musical signal processing, we develop a method to extract the harmonic volcanic tremor signals and to detect transient events from seismic recordings. Based on the similarity properties of spectrogram frames in the time–frequency domain, we decompose the signal into two separate spectrograms representing repeating (harmonic) and nonrepeating (transient) patterns, which correspond to volcanic tremor signals and earthquake signals, respectively. We reconstruct the harmonic tremor signal in the time domain from the complex spectrogram of the repeating pattern by only considering the phase components for the frequency range in which the tremor amplitude spectrum is significantly contributing to the energy of the signal. The reconstructed signal is, therefore, clean tremor signal without transient events. Furthermore, we derive a characteristic function suitable for the detection of transient events (e.g., earthquakes) by integrating amplitudes of the nonrepeating spectrogram over frequency at each time frame. Considering transient events like earthquakes, 78% of the events are detected for signal-to-noise ratio = 0.1 in our semisynthetic tests. In addition, we compared the number of detected earthquakes using our method for one month of continuous data recorded during the Holuhraun 2014–2015 eruption in Iceland with the bulletin presented in Ágústsdóttir et al. (2019). Our single station event detection algorithm identified 84% of the bulletin events. Moreover, we detected a total of 12,619 events, which is more than twice the number ... |
format |
Article in Journal/Newspaper |
author |
Zali, Z. Ohrnberger, M. Scherbaum, F. Cotton, F. Eibl, E. |
spellingShingle |
Zali, Z. Ohrnberger, M. Scherbaum, F. Cotton, F. Eibl, E. Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms |
author_facet |
Zali, Z. Ohrnberger, M. Scherbaum, F. Cotton, F. Eibl, E. |
author_sort |
Zali, Z. |
title |
Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms |
title_short |
Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms |
title_full |
Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms |
title_fullStr |
Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms |
title_full_unstemmed |
Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms |
title_sort |
volcanic tremor extraction and earthquake detection using music information retrieval algorithms |
publishDate |
2021 |
url |
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008179 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008179_3/component/file_5022679/5008179.pdf |
long_lat |
ENVELOPE(-16.831,-16.831,64.852,64.852) |
geographic |
Holuhraun |
geographic_facet |
Holuhraun |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
Seismological Research Letters |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1785/0220210016 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008179 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008179_3/component/file_5022679/5008179.pdf |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1785/0220210016 |
container_title |
Seismological Research Letters |
_version_ |
1779316028961980416 |