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.
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The source code and data are available for downloading at the link: https://github.com/iperas/paper-fennoscandia-ml.
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Acknowledgements
The majority of this work would not be possible without our late colleague Dr. Grigory Kosarev. We also would like to express special appreciation to Dr. Lev Vinnik for the fruitful discussion.
Funding
The authors (Igor Aleshin, Kirill Kholodkov and Ivan Malygin) were supported by the Ministry of Science and Higher Education of the Russian Federation. The author (Elena Kozlovskaya) did not receive support from any organization for the submitted work.
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IA and IM prepared the data and processing scripting. EK performed the interpretation and shaped the conclusion on the results. Together with IA, KK wrote the main manuscript and prepared the visualization. All authors reviewed the manuscript.
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Aleshin, I., Kholodkov, K., Kozlovskaya, E. et al. Crust Macrofracturing as the Evidence of the Last Deglaciation. Pure Appl. Geophys. 180, 3289–3301 (2023). https://doi.org/10.1007/s00024-023-03334-7
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DOI: https://doi.org/10.1007/s00024-023-03334-7