<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Global Navigation Satellite Systems (GNSSs) are one of the techniques that can be used for the deformation monitoring caused by earthquakes. GNSSs enable the monitoring of specific areas affected by earthquakes in real-time and post-processing modes. This paper provides a novel method for the short-term displacement detection based on the phase residuals of GNSS observations. The study examines a natural earthquake from October 26, 2016, in Italy with Mw 6.1. In the proposed methodology, the residuals of the GNSS phase observations are derived using Precise Point Positioning. Then, residuals are transformed to the frequency domain using a wavelet transform, and the earthquake moment is identified using the anomalies detected in the scalogram, which do not appear in stable conditions. The described methodology allows for detecting the starting and ending moments of the earthquake. The methods described detected that the moment of the earthquake is visible in the residues 8 seconds after the seismic catalog time. The conducted experiments show that the use of signal analysis tools allows it to properly detect the ground vibrations in the residuals of GNSS phase observations and thus confirms the registration of ground vibrations in satellite observation data recorded by a GNSS receiver.</p>
</abstract>

Global Navigation Satellite Systems (GNSSs) are one of the techniques that can be used for the deformation monitoring caused by earthquakes. GNSSs enable the monitoring of specific areas affected by earthquakes in real-time and post-processing modes. This paper provides a novel method for the short-term displacement detection based on the phase residuals of GNSS observations. The study examines a natural earthquake from October 26, 2016, in Italy with Mw 6.1. In the proposed methodology, the residuals of the GNSS phase observations are derived using Precise Point Positioning. Then, residuals are transformed to the frequency domain using a wavelet transform, and the earthquake moment is identified using the anomalies detected in the scalogram, which do not appear in stable conditions. The described methodology allows for detecting the starting and ending moments of the earthquake. The methods described detected that the moment of the earthquake is visible in the residues 8 seconds after the seismic catalog time. The conducted experiments show that the use of signal analysis tools allows it to properly detect the ground vibrations in the residuals of GNSS phase observations and thus confirms the registration of ground vibrations in satellite observation data recorded by a GNSS receiver.

Using GNSS Phase Observation Residuals and Wavelet Analysis to Detect Earthquakes

Wrocław University of Environmental and Life Sciences

Artificial Satellites

This work is licensed under the Creative Commons Attribution 4.0 International License.

Global Navigation Satellite Systems (GNSSs) are one of the techniques that can be used for the deformation monitoring caused by earthquakes. GNSSs enable the...

Using GNSS Phase Observation Residuals and Wavelet Analysis to Detect Earthquakes

Pubblicato online: 19 gen 2024

Pagine: 341 - 354

Ricevuto: 06 lug 2023

Accettato: 22 dic 2023

DOI: https://doi.org/10.2478/arsa-2023-0014

Parole chiave
short-term ground displacements, GNSS observation residuals, earthquake vibrations, PPP, continuous wavelet transform

© 2023 Maciej Lackowski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Using GNSS Phase Observation Residuals and Wavelet Analysis to Detect Earthquakes

Pubblicato online: 19 gen 2024

Pagine: 341 - 354

Ricevuto: 06 lug 2023

Accettato: 22 dic 2023

DOI: https://doi.org/10.2478/arsa-2023-0014

Parole chiaveshort-term ground displacements, GNSS observation residuals, earthquake vibrations, PPP, continuous wavelet transform

© 2023 Maciej Lackowski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
short-term ground displacements, GNSS observation residuals, earthquake vibrations, PPP, continuous wavelet transform