Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen
Retreating glaciers are a consequence of a warming climate. Thus, numerous monitoring campaigns are being carried out to increase understanding of this on-going process. One phenomenon related to dynamic glacial changes is glacier-induced seismicity; however, weak seismic events are difficult to rec...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2017-08-01
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| Series: | Journal of Glaciology |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S0022143017000259/type/journal_article |
| _version_ | 1811155843921477632 |
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| author | W. GAJEK J. TROJANOWSKI M. MALINOWSKI |
| author_facet | W. GAJEK J. TROJANOWSKI M. MALINOWSKI |
| author_sort | W. GAJEK |
| collection | DOAJ |
| description | Retreating glaciers are a consequence of a warming climate. Thus, numerous monitoring campaigns are being carried out to increase understanding of this on-going process. One phenomenon related to dynamic glacial changes is glacier-induced seismicity; however, weak seismic events are difficult to record due to the sparse seismological network in arctic areas. We have developed an automatic procedure capable of detecting glacier-induced seismic events using records from a single permanent seismological station. To distinguish between glacial and non-glacial signals, we developed a fuzzy logic algorithm based on the signal frequency and energy flow analysis. We studied the long-term changes in glacier-induced seismicity in Hornsund (southern Spitsbergen) and in Kongsfjorden (western Spitsbergen). We found that the number of detected glacial-origin events in the Hornsund dataset over the years 2013-14 has doubled. In the Kongsfjorden dataset, we observed a steady increase in the number of glacier-induced events with each year. We also observed that the seasonal event distribution correlates best with 1 month lagged temperatures, and that extreme rain events can intensify seismic emissions. Our study demonstrates the possibility of using long-term seismological observations from a single permanent station to automatically monitor the dynamic activity of nearby glaciers and retrieve its characteristic features. |
| first_indexed | 2024-04-10T04:41:29Z |
| format | Article |
| id | doaj.art-21f89129387c41d3a64e9f1999101f05 |
| institution | Directory Open Access Journal |
| issn | 0022-1430 1727-5652 |
| language | English |
| last_indexed | 2024-04-10T04:41:29Z |
| publishDate | 2017-08-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Journal of Glaciology |
| spelling | doaj.art-21f89129387c41d3a64e9f1999101f052023-03-09T12:40:27ZengCambridge University PressJournal of Glaciology0022-14301727-56522017-08-016358159210.1017/jog.2017.25Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from SpitsbergenW. GAJEK0https://orcid.org/0000-0002-8754-3440J. TROJANOWSKI1M. MALINOWSKI2Institute of Geophysics, Polish Academy of Sciences, Warsaw, PolandInstitute of Geophysics, Polish Academy of Sciences, Warsaw, PolandInstitute of Geophysics, Polish Academy of Sciences, Warsaw, PolandRetreating glaciers are a consequence of a warming climate. Thus, numerous monitoring campaigns are being carried out to increase understanding of this on-going process. One phenomenon related to dynamic glacial changes is glacier-induced seismicity; however, weak seismic events are difficult to record due to the sparse seismological network in arctic areas. We have developed an automatic procedure capable of detecting glacier-induced seismic events using records from a single permanent seismological station. To distinguish between glacial and non-glacial signals, we developed a fuzzy logic algorithm based on the signal frequency and energy flow analysis. We studied the long-term changes in glacier-induced seismicity in Hornsund (southern Spitsbergen) and in Kongsfjorden (western Spitsbergen). We found that the number of detected glacial-origin events in the Hornsund dataset over the years 2013-14 has doubled. In the Kongsfjorden dataset, we observed a steady increase in the number of glacier-induced events with each year. We also observed that the seasonal event distribution correlates best with 1 month lagged temperatures, and that extreme rain events can intensify seismic emissions. Our study demonstrates the possibility of using long-term seismological observations from a single permanent station to automatically monitor the dynamic activity of nearby glaciers and retrieve its characteristic features.https://www.cambridge.org/core/product/identifier/S0022143017000259/type/journal_articlecalvingglacier geophysicsglacier monitoringseismology |
| spellingShingle | W. GAJEK J. TROJANOWSKI M. MALINOWSKI Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen Journal of Glaciology calving glacier geophysics glacier monitoring seismology |
| title | Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen |
| title_full | Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen |
| title_fullStr | Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen |
| title_full_unstemmed | Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen |
| title_short | Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen |
| title_sort | automating long term glacier dynamics monitoring using single station seismological observations and fuzzy logic classification a case study from spitsbergen |
| topic | calving glacier geophysics glacier monitoring seismology |
| url | https://www.cambridge.org/core/product/identifier/S0022143017000259/type/journal_article |
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