Pre-seismic strain anomalies and coseismic deformation of Meinong earthquake from continuous GPS

Tsai, Mi-Ching; Shin, Tzay‐Chyn; Kuo, Kai-Wen

doi:10.3319/tao.2017.04.19.01

Cited by 7 publications

(5 citation statements)

References 73 publications

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“…Therefore, they concluded that the surface deformation of the Meinong earthquake was mainly controlled by the shallow structure (duplex structure; less than 10 km) instead of the deeper seismogenic fault. Moreover, according to Tsai et al (2017), the results related to the coseismic displacements of the Meinong earthquake (Figure 13) were also similar to those from Huang, Kuo, et al (2016). Based on the electronic supplement of Lee et al (2016), the NW-SE plane could not well produce the similar pattern of the GPS measurements (vertical component).…”

Section: Comparison Between This Study and Other Source Modelssupporting

confidence: 84%

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Strong Ground Motion Simulation of 2016 M_L6.6 Meinong, Taiwan, Earthquake Using the Empirical Green's Function Method

et al. 2019

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The Meinong mainshock (ML6.6) occurred in southern Taiwan at 19:57:26.08 (UTC) on 5 February 2016. To study source characteristics of the mainshock, ground motions of the mainshock are simulated using the empirical Green's function method to construct a strong motion generation area (SMGA) source model. Records of the event occurred on 2 May 2010 (ML4.6) are chosen as the empirical Green's functions along with six strong motion stations surrounding the source area. Waveforms of the mainshock at all used stations are simulated utilizing the empirical Green's function method to construct a best‐fit source model by comparing the synthetic waveforms with the observed ones in the frequency range 0.2–10 Hz. The estimated SMGA is located on the NS‐striking fault plane. The size of SMGA is 7.2 km in length along the strike direction by 7.2 km in width along the dip direction. The rupture starts at the bottom left‐hand corner (i.e., southern bottom) of the SMGA and then extends radially toward the upper right‐hand corner with a rupture velocity of 2.6 km/s. The size of the SMGA and the rise time of the mainshock follow the self‐similar empirical relationship by Miyake et al. (2003, https://doi.org/10.1785/0120020183).

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Section: Comparison Between This Study and Other Source Modelssupporting

confidence: 84%

“…Horizontal and vertical coseismic deformation of the Meinong earthquake adopted from Tsai et al (). The used GPS data are 5 days before and after earthquake.…”

Section: Resultsmentioning

confidence: 99%

Strong Ground Motion Simulation of 2016 M_L6.6 Meinong, Taiwan, Earthquake Using the Empirical Green's Function Method

et al. 2019

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“…Similarly, Fu and Lee (2017) has reported significant changes in soil radon simultaneously at four stations in southern Taiwan approximately two weeks before the 2010 Jiasian earthquake. Furthermore, the significant rate-slow-down anomalies in cGPS pre-seismic baseline variations near the epicenter of the Meinong earthquake were also demonstrated in southern Taiwan (Tsai et al 2017). A 3D modelling work, i.e., mass flow-reactivegeomechanical transport is necessary in future.…”

Section: Resultsmentioning

confidence: 99%

Preseismic anomalies in soil-gas radon associated with 2016 M 6.6 Meinong earthquake, Southern Taiwan

Fu¹,

Walia²,

Yang³

et al. 2017

Terr. Atmos. Ocean. Sci.

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Taiwan is tectonically situated in a terrain resulting from the oblique collision between the Philippine Sea plate and the continental margin of the Asiatic plate, with a continuous stress causing the density of strong-moderate earthquakes and regional active faults. The continuous time series of soil radon for earthquake studies have been recorded and some significant variations associated with strong earthquakes have been observed. Earthquake prediction is not still operative but these correlations should be added to the literature about seismo-geochemical transients associated to strong earthquakes. Rain-pore pressure related variations, crustal weakness at the studied faults system is consistent with the simultaneous radon anomalies observed. During the observations, a significant increase of soil radon concentrations was observed at Chunglun-T1 (CL-T1), Hsinhua (HH), Pingtung (PT), and Chihshan (CS) stations approximately two weeks before the Meinong earthquake (M L = 6.6, 6 February 2016) in Southern Taiwan. The precursory changes in a multi-stations array may reflect the preparation stage of a large earthquake. Precursory signals are observed simultaneously and it can apply certain algorithms the approximate location and magnitude of the impending earthquake.

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“…The continuous GPS data show that the coseismic deformation in the Longci district (west side of Guanmiao district) had the largest vertical displacement of 100 mm and west horizontal displacement of 50 mm [38]. Based on the seismic data, GPS data and InSAR, Huang et al [22] presented a two-fault model, which included a 15-20-km depth main thrust fault and a 5-10-km depth shallower thrust fault.…”

Section: Study Areamentioning

confidence: 99%

Coherence Difference Analysis of Sentinel-1 SAR Interferogram to Identify Earthquake-Induced Disasters in Urban Areas

Chang

et al. 2018

Remote Sensing

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This study proposes a workflow that enables the accurate identification of earthquake-induced damage zones by using coherence image pairs of the Sentinel-1 satellite before and after an earthquake event. The workflow uses interferometric synthetic aperture radar (InSAR) processing to account for coherence variations between coseismic and preseismic image pairs. The coherence difference between two image pairs is useful information to detect specific disasters in a regional-scale area after an earthquake event. To remove background effects such as the atmospheric effect and ordinal surface changes, this study employs the two-step threshold method to develop the coseismic coherence difference (CCD) map for our analyses. Thirty-four Sentinel-1 images between January 2015 and February 2016 were collected to process 30 preseismic image pairs and two coseismic image pairs for assessing multiple types of disasters in Tainan City of southwestern Taiwan, where severe damages were observed after the Meinong earthquake event. The coseismic unwrapping phases were further calculated to estimate the surface displacement in east-west and vertical directions. Results in the CCD map agree well with the observations from post-earthquake field surveys. The workflow can accurately identify earthquake-induced land subsidence and surface displacements, even for areas with insufficient geological data or for areas that had been excluded from the liquefaction potential map. In addition, the CCD details the distribution of building damages and structure failures, which might be useful information for emergency actions applied to regional-scale problems. The conversion of 2D surface displacement reveals the complex behavior of geological activities during the earthquake. In the foothill area of Tainan City, the opposite surface displacements in local areas might be influenced by the axis activities of the Kuanmiao syncline.

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Pre-seismic strain anomalies and coseismic deformation of Meinong earthquake from continuous GPS

Cited by 7 publications

References 73 publications

Strong Ground Motion Simulation of 2016 M_L6.6 Meinong, Taiwan, Earthquake Using the Empirical Green's Function Method

Strong Ground Motion Simulation of 2016 M_L6.6 Meinong, Taiwan, Earthquake Using the Empirical Green's Function Method

Preseismic anomalies in soil-gas radon associated with 2016 M 6.6 Meinong earthquake, Southern Taiwan

Coherence Difference Analysis of Sentinel-1 SAR Interferogram to Identify Earthquake-Induced Disasters in Urban Areas

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Pre-seismic strain anomalies and coseismic deformation of Meinong earthquake from continuous GPS

Cited by 7 publications

References 73 publications

Strong Ground Motion Simulation of 2016 ML6.6 Meinong, Taiwan, Earthquake Using the Empirical Green's Function Method

Strong Ground Motion Simulation of 2016 ML6.6 Meinong, Taiwan, Earthquake Using the Empirical Green's Function Method

Preseismic anomalies in soil-gas radon associated with 2016 M 6.6 Meinong earthquake, Southern Taiwan

Coherence Difference Analysis of Sentinel-1 SAR Interferogram to Identify Earthquake-Induced Disasters in Urban Areas

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Strong Ground Motion Simulation of 2016 M_L6.6 Meinong, Taiwan, Earthquake Using the Empirical Green's Function Method

Strong Ground Motion Simulation of 2016 M_L6.6 Meinong, Taiwan, Earthquake Using the Empirical Green's Function Method