Integration of Single-Frequency GNSS and Strong-Motion Observations for Real-Time Earthquake Monitoring

Tu, Rui; Zhang, Rui; Zhang, Pengfei; Liu, Jinhai; Lu, Xiaochun

doi:10.3390/rs10060886

Cited by 3 publications

(1 citation statement)

References 33 publications

(29 reference statements)

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“…Therefore, when using GNSS data to estimate the earthquake magnitude, it is inevitable that high-frequency information would be lost, which might result in deviations in earthquake magnitude estimate. Consequently, it is imperative to develop methods of effectively integrating geodetic data with seismic data [34][35][36]. Finally, compared with PGD magnitude, PGV magnitude at different stations fluctuates greatly, meaning that the regression model between PGV and moment magnitude may still need to be improved when dealing with earthquakes in Tibet.…”

Section: Discussionmentioning

confidence: 99%

Earthquake Magnitude Estimation from High-Rate GNSS Data: A Case Study of the 2021 Mw 7.3 Maduo Earthquake

Gao

Shan

et al. 2021

Remote Sensing

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Peak ground displacement (PGD) and peak ground velocity (PGV) are critical parameters during earthquake early warning, as they can provide rapid magnitude estimation before rupture end. In this study, we used the high-rate Global Navigation Satellite System (GNSS) data from 55 continuous stations to estimate the magnitude of the 2021 Maduo earthquake in western China. We used the relative positioning method and variometric approach to acquire real-time GNSS displacement and velocity waveforms, respectively. The results showed the amplitude of displacement and velocity waveforms gradually decreased with increasing hypocentral distance. Our results showed that the fluctuation of PGD magnitudes over time is smaller than that of PGV magnitudes. Nonetheless, the earthquake magnitudes estimated from both methods were consistent with their counterparts (Mw 7.3) reported by the United States Geological Survey (USGS). The final magnitude estimated from the PGD and PGV methods were Mw 7.25 and Mw 7.31, respectively. In addition, our results highlighted how the number of high-rate GNSS stations could influence the stability and convergence time of magnitude estimation.

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Section: Discussionmentioning

confidence: 99%

Earthquake Magnitude Estimation from High-Rate GNSS Data: A Case Study of the 2021 Mw 7.3 Maduo Earthquake

Gao

Shan

et al. 2021

Remote Sensing

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Precise coseismic displacements from the GPS variometric approach using different precise products: Application to the 2008 MW 7.9 Wenchuan earthquake

Shu

Fang

Liu

et al. 2020

Advances in Space Research

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An Integrated GNSS/MEMS Accelerometer System for Dynamic Structural Response Monitoring under Thunder Loading

Wang

Liu

et al. 2023

Remote Sensing

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Dynamic response monitoring is of great significance for large engineering structural anomaly diagnosis and early warning. Although the global navigation satellite system (GNSS) has been widely used to measure the dynamic structural response, it has the limitation of a relatively low sampling rate. The micro-electro-mechanical system (MEMS) accelerometer has a high sampling frequency, but it belongs to the approaches of acceleration measurements as the absolute position is unavailable. Hence, in this paper, an integrated vibration monitoring system that includes a GNSS receiver and 3-axis MEMS accelerometers was developed to obtain the dynamic responses under the thunder loading. First, a new denoising algorithm for thunderstorm-induced vibration data was proposed based on variational mode decomposition (VMD) and the characteristics of white noise, and the low-frequency disturbance was separated from the GNSS displacement time series. Then, a power spectral density (PSD) analysis using data collected by the integrated system was carried out to extract low/high natural frequencies. Finally, field monitoring data collected at Huanghuacheng, Hefangkou, and Qilianguan in Beijing’s Huairou District were used to validate the effectiveness of the integrated system and processing scheme. According to the results, the proposed integrated GNSS/MEMS accelerometer system can not only be used to detect thunder loading events, but also completely extract the natural frequency based on PSD analysis. The high natural frequencies detected from the accelerometer data of the four Great Wall monitoring stations excited by the thunderstorms are 42.12 Hz, 12.94 Hz, 12.58 Hz, and 5.95 Hz, respectively, while the low natural frequencies detected from the GNSS are 0.02 Hz, 0.019 Hz, 0.016 Hz, and 0.014 Hz, respectively. Moreover, thunderstorms can cause the Great Wall to vibrate with a maximum displacement of 14.3 cm.

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Integration of Single-Frequency GNSS and Strong-Motion Observations for Real-Time Earthquake Monitoring

Cited by 3 publications

References 33 publications

Earthquake Magnitude Estimation from High-Rate GNSS Data: A Case Study of the 2021 Mw 7.3 Maduo Earthquake

Earthquake Magnitude Estimation from High-Rate GNSS Data: A Case Study of the 2021 Mw 7.3 Maduo Earthquake

Precise coseismic displacements from the GPS variometric approach using different precise products: Application to the 2008 MW 7.9 Wenchuan earthquake

An Integrated GNSS/MEMS Accelerometer System for Dynamic Structural Response Monitoring under Thunder Loading

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