Crust Macrofracturing as the Evidence of the Last Deglaciation
Machine learning methods were applied to reconsider the results of several passive seismic experiments in Finland. We created datasets from different stages of the receiver function technique and processed them with one of the basic machine learning algorithms. All the results were obtained uniforml...
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| Veröffentlicht in: | Pure and applied geophysics 2023-09, Vol.180 (9), p.3289-3301 |
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| creator | Aleshin, Igor Kholodkov, Kirill Kozlovskaya, Elena Malygin, Ivan |
| description | Machine learning methods were applied to reconsider the results of several passive seismic experiments in Finland. We created datasets from different stages of the receiver function technique and processed them with one of the basic machine learning algorithms. All the results were obtained uniformly with the k-nearest neighbors algorithm. The first result is the Moho depth map of the region. Another result is the delineation of the near-surface low
S
-wave velocity layer. There are three such areas in the Northern, Southern, and Central parts of the region. The low
S
-wave velocity in the Northern and Southern areas can be linked to the geological structure. However, we attribute the central low
S
-wave velocity area to a large number of water-saturated cracks in the upper 1–5 km of the crust. Analysis of the structure of this area leads us to the conclusion that macrofracturing was caused by the last deglaciation. |
| doi_str_mv | 10.1007/s00024-023-03334-7 |
| format | Article |
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S
-wave velocity layer. There are three such areas in the Northern, Southern, and Central parts of the region. The low
S
-wave velocity in the Northern and Southern areas can be linked to the geological structure. However, we attribute the central low
S
-wave velocity area to a large number of water-saturated cracks in the upper 1–5 km of the crust. Analysis of the structure of this area leads us to the conclusion that macrofracturing was caused by the last deglaciation.</description><identifier>ISSN: 0033-4553</identifier><identifier>EISSN: 1420-9136</identifier><identifier>DOI: 10.1007/s00024-023-03334-7</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Algorithms ; Datasets ; Deglaciation ; Earth and Environmental Science ; Earth Sciences ; Experiments ; Geological structures ; Geophysics/Geodesy ; Learning algorithms ; Machine learning ; Meltwater ; Moho ; S waves ; Seismic velocities ; Velocity ; Wave velocity</subject><ispartof>Pure and applied geophysics, 2023-09, Vol.180 (9), p.3289-3301</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a293t-63882c66020c1dafe94d2b6ee1aff15bed3266e6dc6c77b2f41e63b791616c4d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00024-023-03334-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00024-023-03334-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,41486,42555,51317</link.rule.ids></links><search><creatorcontrib>Aleshin, Igor</creatorcontrib><creatorcontrib>Kholodkov, Kirill</creatorcontrib><creatorcontrib>Kozlovskaya, Elena</creatorcontrib><creatorcontrib>Malygin, Ivan</creatorcontrib><title>Crust Macrofracturing as the Evidence of the Last Deglaciation</title><title>Pure and applied geophysics</title><addtitle>Pure Appl. Geophys</addtitle><description>Machine learning methods were applied to reconsider the results of several passive seismic experiments in Finland. We created datasets from different stages of the receiver function technique and processed them with one of the basic machine learning algorithms. All the results were obtained uniformly with the k-nearest neighbors algorithm. The first result is the Moho depth map of the region. Another result is the delineation of the near-surface low
S
-wave velocity layer. There are three such areas in the Northern, Southern, and Central parts of the region. The low
S
-wave velocity in the Northern and Southern areas can be linked to the geological structure. However, we attribute the central low
S
-wave velocity area to a large number of water-saturated cracks in the upper 1–5 km of the crust. Analysis of the structure of this area leads us to the conclusion that macrofracturing was caused by the last deglaciation.</description><subject>Algorithms</subject><subject>Datasets</subject><subject>Deglaciation</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Experiments</subject><subject>Geological structures</subject><subject>Geophysics/Geodesy</subject><subject>Learning algorithms</subject><subject>Machine learning</subject><subject>Meltwater</subject><subject>Moho</subject><subject>S waves</subject><subject>Seismic velocities</subject><subject>Velocity</subject><subject>Wave velocity</subject><issn>0033-4553</issn><issn>1420-9136</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kE9LxDAQxYMouFa_gKeC5-jkT5PtRZC6q8KKFz2HNJ2sXdZ2TVrBb292K3jzNMzw3hvej5BLBtcMQN9EAOCSAhcUhBCS6iMyY5IDLZlQx2QG6UxlUYhTchbjBoBpXZQzcluFMQ75s3Wh98G6YQxtt85tzId3zBdfbYOdw7z3h31lk_Ye11vrWju0fXdOTrzdRrz4nRl5Wy5eq0e6enl4qu5W1PJSDFSJ-Zw7pYCDY431WMqG1wqRWe9ZUWMjuFKoGqec1jX3kqEStS6ZYsrJRmTkasrdhf5zxDiYTT-GLr00fK4LJXiZimaET6pUJsaA3uxC-2HDt2Fg9pzMxMkkTubAyehkEpMp7vbVMfxF_-P6AW7Lafc</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Aleshin, Igor</creator><creator>Kholodkov, Kirill</creator><creator>Kozlovskaya, Elena</creator><creator>Malygin, Ivan</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TG</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>L7M</scope><scope>M2P</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>Q9U</scope></search><sort><creationdate>20230901</creationdate><title>Crust Macrofracturing as the Evidence of the Last Deglaciation</title><author>Aleshin, Igor ; 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Geophys</stitle><date>2023-09-01</date><risdate>2023</risdate><volume>180</volume><issue>9</issue><spage>3289</spage><epage>3301</epage><pages>3289-3301</pages><issn>0033-4553</issn><eissn>1420-9136</eissn><abstract>Machine learning methods were applied to reconsider the results of several passive seismic experiments in Finland. We created datasets from different stages of the receiver function technique and processed them with one of the basic machine learning algorithms. All the results were obtained uniformly with the k-nearest neighbors algorithm. The first result is the Moho depth map of the region. Another result is the delineation of the near-surface low
S
-wave velocity layer. There are three such areas in the Northern, Southern, and Central parts of the region. The low
S
-wave velocity in the Northern and Southern areas can be linked to the geological structure. However, we attribute the central low
S
-wave velocity area to a large number of water-saturated cracks in the upper 1–5 km of the crust. Analysis of the structure of this area leads us to the conclusion that macrofracturing was caused by the last deglaciation.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s00024-023-03334-7</doi><tpages>13</tpages></addata></record> |
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| subjects | Algorithms Datasets Deglaciation Earth and Environmental Science Earth Sciences Experiments Geological structures Geophysics/Geodesy Learning algorithms Machine learning Meltwater Moho S waves Seismic velocities Velocity Wave velocity |
| title | Crust Macrofracturing as the Evidence of the Last Deglaciation |
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