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Wang Leyang, Zou Ajian. Retrieving 3-D coseismic deformation of the 2016 Mw 7.8 Kaikoura earthquake using SAR and optical data[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210352
Citation: Wang Leyang, Zou Ajian. Retrieving 3-D coseismic deformation of the 2016 Mw 7.8 Kaikoura earthquake using SAR and optical data[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210352

Retrieving 3-D coseismic deformation of the 2016 Mw 7.8 Kaikoura earthquake using SAR and optical data

doi: 10.13203/j.whugis20210352
Funds:

The National Natural Science Foundation of China (41874001, 42174011, 42104008), The Graduate Innovation Foundation of East China University of Technology(DHYC-202121).

  • Received Date: 2021-06-29
    Available Online: 2022-03-12
  • Objectives: Co-seismic deformation monitoring is of great significance for the interpretation of Co-seismic deformation characteristics and intuitive understanding of fault geometric characteristics. For large earthquakes with surface rupture, Global Navigation Satellite System(GNSS) technique has a low spatial resolution, and Interferometric Synthetic Aperture Radar(InSAR) technology will cause phase decorrelation due to large deformation gradients, it is impossible to obtain specific deformation around the fault. Optical image correlation(OIC) and pixel offset tracking(POT) based on sub-pixel cross-correlation can solve these problems well. Methods: The main idea of the sub-pixel cross-correlation method is to use the pre-event image in the two images as a reference, and then compare the post-event image with it to evaluate the similarity between the two images, and then retrieve the displacement between the homonymous points. OIC can obtain east-west and north-south deformations, and POT can obtain range and azimuth deformations. In this paper, the deformation in each direction of the Kaikoura earthquake obtained from Sentinel-1 data and Sentinel-2 data is used to form different combinations, and the least square method is used to calculate the three-dimensional deformation. Results: The combination of OIC+POT_As_Des has the best constraint. The accuracy of the north-south deformation obtained by OIC+POT_Range is not as good as that of OIC+POT_As_Des. Compared with POT_As_Des, the north-south deformation precision obtained by it is higher, and the deformation performance on the right side of the KeKerengu fault and the left side of the PaPatea fault is also better. In the northeast of the Kaikoura earthquake epicenter, very complex and huge surface deformation and multiple ruptures were detected in two close areas, and the vertical deformation was mainly uplift. Conclusions: For Sentinel-1 and Sentinel-2, the combination of OIC+POT_As_Des is most suitable for obtaining the three-dimensional deformation of the Kaikoura earthquake. This earthquake is a dextral strike-slip earthquake with reverse.
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Retrieving 3-D coseismic deformation of the 2016 Mw 7.8 Kaikoura earthquake using SAR and optical data

doi: 10.13203/j.whugis20210352
Funds:

The National Natural Science Foundation of China (41874001, 42174011, 42104008), The Graduate Innovation Foundation of East China University of Technology(DHYC-202121).

Abstract: Objectives: Co-seismic deformation monitoring is of great significance for the interpretation of Co-seismic deformation characteristics and intuitive understanding of fault geometric characteristics. For large earthquakes with surface rupture, Global Navigation Satellite System(GNSS) technique has a low spatial resolution, and Interferometric Synthetic Aperture Radar(InSAR) technology will cause phase decorrelation due to large deformation gradients, it is impossible to obtain specific deformation around the fault. Optical image correlation(OIC) and pixel offset tracking(POT) based on sub-pixel cross-correlation can solve these problems well. Methods: The main idea of the sub-pixel cross-correlation method is to use the pre-event image in the two images as a reference, and then compare the post-event image with it to evaluate the similarity between the two images, and then retrieve the displacement between the homonymous points. OIC can obtain east-west and north-south deformations, and POT can obtain range and azimuth deformations. In this paper, the deformation in each direction of the Kaikoura earthquake obtained from Sentinel-1 data and Sentinel-2 data is used to form different combinations, and the least square method is used to calculate the three-dimensional deformation. Results: The combination of OIC+POT_As_Des has the best constraint. The accuracy of the north-south deformation obtained by OIC+POT_Range is not as good as that of OIC+POT_As_Des. Compared with POT_As_Des, the north-south deformation precision obtained by it is higher, and the deformation performance on the right side of the KeKerengu fault and the left side of the PaPatea fault is also better. In the northeast of the Kaikoura earthquake epicenter, very complex and huge surface deformation and multiple ruptures were detected in two close areas, and the vertical deformation was mainly uplift. Conclusions: For Sentinel-1 and Sentinel-2, the combination of OIC+POT_As_Des is most suitable for obtaining the three-dimensional deformation of the Kaikoura earthquake. This earthquake is a dextral strike-slip earthquake with reverse.

Wang Leyang, Zou Ajian. Retrieving 3-D coseismic deformation of the 2016 Mw 7.8 Kaikoura earthquake using SAR and optical data[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210352
Citation: Wang Leyang, Zou Ajian. Retrieving 3-D coseismic deformation of the 2016 Mw 7.8 Kaikoura earthquake using SAR and optical data[J]. Geomatics and Information Science of Wuhan University. doi: 10.13203/j.whugis20210352
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