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Science China Earth Sciences

, Volume 61, Issue 10, pp 1451–1466 | Cite as

Mapping three-dimensional co-seismic surface deformations associated with the 2015 MW7.2 Murghab earthquake based on InSAR and characteristics of crustal strain

  • Jie Gan
  • Jun Hu
  • Zhiwei Li
  • Changjiang Yang
  • Jihong Liu
  • Qian Sun
  • Wanji Zheng
Research Paper

Abstract

Three-dimensional (3D) co-seismic surface deformations are of great importance to interpret the characteristics of coseismic deformations and to understand the geometries and dynamics of seismogenic faults. In this paper, we propose a method for mapping 3D co-seismic deformations based on InSAR observations and crustal strain characteristics. In addition, the search strategy of correlation points is optimized by adaptive correlation distance, which greatly improves the applicability of the proposed method in restoring deformations in decorrelation areas. Results of the simulation experiment reveal that the proposed method is superior to conventional methods in both the accuracy and completeness. The proposed method is then applied to map the 3D co-seismic surface deformations associated with the 2015 MW7.2 Murghab earthquake using ascending and descending ALOS-2 PALSAR-2 images. The results show that the seismogenic fault is the Sarez-Karakul fault (SKF), which is dominated by NE-SW strike slips with an almost vertical dip angle. The north section and the south segment near the epicentre have obvious subsidence along with a southwestward motion in the northwest wall, and the southeast wall has northeast movement and surface uplift trend along the fault zone. The strain field of the earthquake is also obtained by the proposed method. It is found that the crustal block of the seismic area is obviously affected by dilatation and shear forces, which is in good agreement with the movement character of the sinistral slip.

Keywords

InSAR Characteristics of crustal strain Three-dimensional co-seismic deformations Murghab earthquake ALOS-2 

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Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 41404011, 41674010 & 41704001), the Key Research and Development Plan of Hunan Province, China (Grant Nos. 2016SK2002 & 2017RS3001), the Innovation Platform Public Foundation of the Education Department of Hunan Province, China (Grant No. 16K053), the Land and Resource Department Scientific Research Program of Hunan Province, China (Grant No. 2017-13) and the Special Funds for Basic Scientific Research Services of Central Higher Education Institutions of Central South University (Grant No. 2017ZZTS772).

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Copyright information

© Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Jie Gan
    • 1
    • 3
  • Jun Hu
    • 1
    • 2
  • Zhiwei Li
    • 1
    • 2
  • Changjiang Yang
    • 1
    • 4
  • Jihong Liu
    • 1
  • Qian Sun
    • 5
  • Wanji Zheng
    • 1
  1. 1.School of Geosciences and Info-physicsCentral South UniversityChangshaChina
  2. 2.Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Central South University), Ministry of EducationChangshaChina
  3. 3.Hunan Spatio Map Information Technology Limited CompanyChangshaChina
  4. 4.Central Southern China Electric Power Design Institute of China Power Engineering Consulting Group CorporationWuhanChina
  5. 5.College of Resources and Environmental ScienceHunan Normal UniversityChangshaChina

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