Real-Time Seismic Waveforms Estimation of the 2019 MW = 6.4 and Mw = 7.1 California Earthquakes With High-Rate Multi-GNSS Observations
Global Navigation Satellite System (GNSS) is recognized as an effective tool to retrieve high-precision seismic displacements, which has been widely used in earthquake early warning systems such as magnitude estimation and fault slip inversion. In this study, we present two multi-GNSS positioning mo...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9085394/ |
| _version_ | 1831644098636808192 |
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| author | Ke Su Shuanggen Jin |
| author_facet | Ke Su Shuanggen Jin |
| author_sort | Ke Su |
| collection | DOAJ |
| description | Global Navigation Satellite System (GNSS) is recognized as an effective tool to retrieve high-precision seismic displacements, which has been widely used in earthquake early warning systems such as magnitude estimation and fault slip inversion. In this study, we present two multi-GNSS positioning models for rapidly capturing real-time coseismic displacements using the raw pseudorange, carrier phase and Doppler measurements, called constant velocity (CV) and constant acceleration (CA) dynamic precise point positioning (PPP) models, respectively. The proposed methods are validated with the datasets collected during the 2019 July 4 Mw 6.4 and July 6 Mw 7.1 earthquakes in real-time scenarios. Results show that the two models can provide accurate displacement waveforms with the accuracy of few centimeters. Besides, the multi-GNSS integration can significantly improve the model performances compared with GPS-only solutions in both time- and frequency- domains. The dynamic PPP models can also reliably recover the moment magnitudes and permanent seismic displacements, indicating that the methods have the potential to benefit for earthquake early warning and rapid geohazard assessment. |
| first_indexed | 2024-12-19T13:12:05Z |
| format | Article |
| id | doaj.art-11d3f02b75964addaaad816826818812 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T13:12:05Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-11d3f02b75964addaaad8168268188122022-12-21T20:19:54ZengIEEEIEEE Access2169-35362020-01-018854118542010.1109/ACCESS.2020.29921939085394Real-Time Seismic Waveforms Estimation of the 2019 MW = 6.4 and Mw = 7.1 California Earthquakes With High-Rate Multi-GNSS ObservationsKe Su0https://orcid.org/0000-0003-3039-5106Shuanggen Jin1https://orcid.org/0000-0002-5108-4828Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, ChinaShanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, ChinaGlobal Navigation Satellite System (GNSS) is recognized as an effective tool to retrieve high-precision seismic displacements, which has been widely used in earthquake early warning systems such as magnitude estimation and fault slip inversion. In this study, we present two multi-GNSS positioning models for rapidly capturing real-time coseismic displacements using the raw pseudorange, carrier phase and Doppler measurements, called constant velocity (CV) and constant acceleration (CA) dynamic precise point positioning (PPP) models, respectively. The proposed methods are validated with the datasets collected during the 2019 July 4 Mw 6.4 and July 6 Mw 7.1 earthquakes in real-time scenarios. Results show that the two models can provide accurate displacement waveforms with the accuracy of few centimeters. Besides, the multi-GNSS integration can significantly improve the model performances compared with GPS-only solutions in both time- and frequency- domains. The dynamic PPP models can also reliably recover the moment magnitudes and permanent seismic displacements, indicating that the methods have the potential to benefit for earthquake early warning and rapid geohazard assessment.https://ieeexplore.ieee.org/document/9085394/Dynamic PPPmulti-GNSSmagnitudepermanent displacementspositioning precision |
| spellingShingle | Ke Su Shuanggen Jin Real-Time Seismic Waveforms Estimation of the 2019 MW = 6.4 and Mw = 7.1 California Earthquakes With High-Rate Multi-GNSS Observations IEEE Access Dynamic PPP multi-GNSS magnitude permanent displacements positioning precision |
| title | Real-Time Seismic Waveforms Estimation of the 2019 MW = 6.4 and Mw = 7.1 California Earthquakes With High-Rate Multi-GNSS Observations |
| title_full | Real-Time Seismic Waveforms Estimation of the 2019 MW = 6.4 and Mw = 7.1 California Earthquakes With High-Rate Multi-GNSS Observations |
| title_fullStr | Real-Time Seismic Waveforms Estimation of the 2019 MW = 6.4 and Mw = 7.1 California Earthquakes With High-Rate Multi-GNSS Observations |
| title_full_unstemmed | Real-Time Seismic Waveforms Estimation of the 2019 MW = 6.4 and Mw = 7.1 California Earthquakes With High-Rate Multi-GNSS Observations |
| title_short | Real-Time Seismic Waveforms Estimation of the 2019 MW = 6.4 and Mw = 7.1 California Earthquakes With High-Rate Multi-GNSS Observations |
| title_sort | real time seismic waveforms estimation of the 2019 mw x003d 6 4 and mw x003d 7 1 california earthquakes with high rate multi gnss observations |
| topic | Dynamic PPP multi-GNSS magnitude permanent displacements positioning precision |
| url | https://ieeexplore.ieee.org/document/9085394/ |
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