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Using GNSS Phase Observation Residuals and Wavelet Analysis to Detect Earthquakes

Maciej Lackowski

Maciej Lackowski

Wrocław University of Environmental and Life Sciences, Institute of Geodesy and GeoinformaticsWrocław, Poland
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Lackowski, Maciej
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Kamil Kaźmierski

Kamil Kaźmierski

Wrocław University of Environmental and Life Sciences, Institute of Geodesy and GeoinformaticsWrocław, Poland
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Kaźmierski, Kamil
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Iwona Kudłacik

Iwona Kudłacik

Wrocław University of Environmental and Life Sciences, Institute of Geodesy and GeoinformaticsWrocław, Poland
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Kudłacik, Iwona
  
Jan 19, 2024
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Published Online: Jan 19, 2024
Page range: 341 - 354
Received: Jul 06, 2023
Accepted: Dec 22, 2023
DOI: https://doi.org/10.2478/arsa-2023-0014
Keywords
© 2023 Maciej Lackowski et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Distribution of the earthquake epicenter and GNSS stations
Distribution of the earthquake epicenter and GNSS stations

Figure 2.

Flow chart of the proposed method
Flow chart of the proposed method

Figure 3.

Coordinate differences between a priori coordinates from the RINEX file header and estimated coordinates for each epoch obtained from the kinematic PPP. The vertical dashes define the earthquake ranges obtained from the seismograph for the ACCU station
Coordinate differences between a priori coordinates from the RINEX file header and estimated coordinates for each epoch obtained from the kinematic PPP. The vertical dashes define the earthquake ranges obtained from the seismograph for the ACCU station

Figure 4.

Fast wavelet transform performed for a series of resistances for all satellites at frequency L1 for the ACCU station
Fast wavelet transform performed for a series of resistances for all satellites at frequency L1 for the ACCU station

Figure 5.

GNSS observation residuals (red) and filtered residuals (blue, top panel), continuous wavelet transform scalar for scales 1–64 (bottom panel) for filtered observation residuals for the satellite G05 at frequency L1W for the ACCU station
GNSS observation residuals (red) and filtered residuals (blue, top panel), continuous wavelet transform scalar for scales 1–64 (bottom panel) for filtered observation residuals for the satellite G05 at frequency L1W for the ACCU station

Figure 6.

Detected outliers derived from the scalogram coefficients of the filtered GNSS observation residuals for satellite G05 at frequency L1W (top panel) and the percentage of scalogram coefficients classified as outliers (bottom panel)
Detected outliers derived from the scalogram coefficients of the filtered GNSS observation residuals for satellite G05 at frequency L1W (top panel) and the percentage of scalogram coefficients classified as outliers (bottom panel)

Figure 7.

Detected outliers obtained from summed scalogram coefficients for all satellites (top panel) and percentage of scalogram coefficients classified as outliers (bottom panel)
Detected outliers obtained from summed scalogram coefficients for all satellites (top panel) and percentage of scalogram coefficients classified as outliers (bottom panel)

Figure 8.

Color combinations of outliers determined by a certain number of satellites on the L1W frequency for ACCU stations. Colors used; green: one satellite, yellow: two, orange: three, red: four, purple: five, black: six satellites.
Color combinations of outliers determined by a certain number of satellites on the L1W frequency for ACCU stations. Colors used; green: one satellite, yellow: two, orange: three, red: four, purple: five, black: six satellites.

Figure 9.

Accelerations for the N component of the seismograph (black) and the designated earthquake range for the ACCU station detected using GNSS residuals
Accelerations for the N component of the seismograph (black) and the designated earthquake range for the ACCU station detected using GNSS residuals

Summary of names, azimuths, and distances for GNSS stations and seismographs (Kudlacik et al_ 2019)

Sensor name Azimuth of epicenter Distance [km]
GNSS station Seismograph To Epic. epicenter Between Sens. sensors
ACCU IT.ACCU 158.9° 25.4 0.08
AMAT IT.AMT 157.0° 33.7 0.77
GUMA IV.GUMA 45.6° 24.0 0.49
MTER IV.RM33 171.5° 44.9 0.39

Computational strategy in CSRS-PPP

Section Description
Mask elevation 7.5°
Interval 0.1 s
Observations GPS + GLONASS
Tropospheric modeling VMF1 (Boehm, Werl, and Schuh 2006) + horizontal and zenith gradient estimation
Ionosphere modeling Estimated
Use of the precise products Products from IGS + CSRS-PPP clock combination (Banville 2020)

Parameters of the analyzed earthquake (after Kudlacik et al_ 2019)

Parameter Value
Date 10.26.2016 19:18:08 UTC
Location 3 km NNW of Visso, Italy
Epicenter 42.862°N 13.096°E
Depth 8 km
Magnitude 6.1
Focal mechanism normal, NP1: 333°/40°/−92°, NP2: 155°/50°/−89°
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Geosciences, Geosciences, other
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