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EARTHQUAKE ›› 2021, Vol. 41 ›› Issue (4): 57-67.doi: 10.12196/j.issn.1000-3274.2021.04.004

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Application of Three Strain Calculation Methods Based on GNSS Data in the Southeastern Margin of Tibet Plateau

JIN Yang1, JIN Hong-lin1, GAO Yuan1, HUANG Xing2   

  1. 1. Insititute of Earthquake Forcasting, Key Laboratory of Earthquake Prediction, Beijing 100036, China;
    2. Institute of Geology, China Earthquake Administration, Beijing 100029, China
  • Received:2021-04-29 Revised:2021-06-27 Online:2021-10-31 Published:2022-03-25

Abstract: The methods of using the GNSS velocity field to solve the strain rate have multiple characteristics, which can be divided into mathematical methods and physical methods. This paper selects three mathematical methods to solve the strain rate: Least Squares Collocation Method, Multi-scale Spherical Wavelet Method, Gussian Weighted Interpolation Method, to resolve the GNSS velocity field and uniform GNSS velocity field on the southeastern margin of Tibet Plateau from 1999 to 2019 (97°E~106°E, 21°N~30°N), and the applicability characteristics of the above three methods in this area is discussed. By analyzing the results of principal strain rate (maximum/minimum), maximum shear strain rate, and surface strain rate obtained from two sets of different data distributions, we found that the strain parameters obtained by multi-scale spherical wavelet method have higher resolution in the southeastern margin of Tibet Plateau. In the high-density data distribution, the spatial deformation characteristics in a small area can be reflected in detail, which is helpful to determine the fault deformation characteristics. The result only represents the studied area on the southeastern margin of Tibet Plateau, and the selection of calculation methods for other areas still needs to consider the conditions of the structural deformation background and the distribution density of measurement points.

Key words: GNSS data, Strain rate, Least squares collocation method, Multi-scale spherical wavelet method, Gussian weighted interpolation method

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