A Multiple Algorithm Approach to the Analysis of GNSS Coordinate Time Series for Detecting Geohazards and Anomalies
| العنوان: | A Multiple Algorithm Approach to the Analysis of GNSS Coordinate Time Series for Detecting Geohazards and Anomalies |
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| المؤلفون: | Markus Rothacher, Panos Psimoulis, Richard Bingley, Mohammed Habboub |
| المصدر: | Journal of Geophysical Research: Solid Earth |
| بيانات النشر: | ETH Zurich, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Thesaurus (information retrieval), Geophysics, Series (mathematics), Space and Planetary Science, Geochemistry and Petrology, GNSS applications, Computer science, Earth and Planetary Sciences (miscellaneous), Data mining, computer.software_genre, Coordinate time, computer |
| الوصف: | In this study, a multiple algorithm approach to the analysis of GNSS coordinate time series for detecting geohazards and anomalies is proposed. This multiple algorithm approach includes the novel use of spatial and temporal analyses. In the spatial analysis algorithm, the spatial autoregressive model was used, assuming that the GNSS coordinate time series from a network of stations are spatially dependent. Whereas in the temporal analysis algorithm, it is assumed that the GNSS coordinate time series of a single station is temporally dependent and an artificial neural network is used to extract this dependency as a nonparametric model. This multiple algorithm approach was examined using (i) the BIGF network of GNSS stations in the British Isles and (ii) the GNSS stations of the GEONET network in Japan for the Tohoku‐Oki 2011 Mw9.0 earthquake. It was demonstrated in these case studies that this multiple algorithm approach can be used to detect the effect of a geohazard such as an earthquake on the GNSS network coordinate time series and to detect regional anomalies in the GNSS coordinate time series of a network. The spatial analysis algorithm seemed to be more suitable to detect coordinate offsets in the low‐frequency component and/or variations in the long‐term trends of the GNSS coordinate time series, while it is less reliable in detecting sudden large magnitude coordinate offsets due to earthquakes, as the effects at one station propagate to nearby stations. In contrast, the temporal analysis algorithm detects coordinate offsets in the high‐frequency component which makes it effective in detecting sudden large coordinate offsets in the GNSS coordinate time series such as those due to earthquakes. Thus, it was shown the complementary of the temporal and spatial analysis algorithms and their successful application for the magnitude and frequency content of the anomalies in the two case studies. Journal of Geophysical Research: Solid Earth ISSN:2169-9313 ISSN:0148-0227 ISSN:2169-9356 |
| وصف الملف: | application/application/pdf |
| اللغة: | English |
| تدمد: | 2169-9313 0148-0227 2169-9356 |
| DOI: | 10.3929/ethz-b-000402380 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3645aa09018447cf1832547f5d1e2f87 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....3645aa09018447cf1832547f5d1e2f87 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 21699313 01480227 21699356 |
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| DOI: | 10.3929/ethz-b-000402380 |