Strain characteristics distribution and potential information analysis in Yunnan based on GNSS data

Based on the observation data of 211 Global Navigation Satellite System (GNSS) regional stations from 2011 to 2016, and 59 continuously operating GNSS stations in the Yunnan region of China since 2013, we analyzed the strain characteristics of Yunnan from the following two perspectives. On the one h...

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Bibliographic Details
Published in:International journal of earth sciences : Geologische Rundschau 2021-04, Vol.110 (3), p.979-994
Main Authors: Gao, Han, Zhang, Ming, Hong, Min, Shao, Desheng, Niu, Yufen, Wang, Lingli, Xu, Liangye, Niu, Tian, Yuan, Xiping
Format: Article
Language:English
Subjects:
Data analysis
Dynamic analysis
Earth and Environmental Science
Earth Sciences
Earthquakes
Geochemistry
Geology
Geophysics/Geodesy
Global navigation satellite system
Hilbert transformation
Information management
Information processing
Mineral Resources
Navigation
Navigation satellites
Navigation systems
Navigational satellites
Original Paper
Satellite observation
Sedimentology
Seismic activity
Spatial variability
Spatial variations
Stations
Strain analysis
Structural Geology
Time series
Wavelet analysis
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Summary:Based on the observation data of 211 Global Navigation Satellite System (GNSS) regional stations from 2011 to 2016, and 59 continuously operating GNSS stations in the Yunnan region of China since 2013, we analyzed the strain characteristics of Yunnan from the following two perspectives. On the one hand, we analyzed the strain characteristics and tried to determine the potentially abnormal areas of Yunnan based on a multi-scale spherical wavelet method, from an overall strain background view. On the other hand, we investigated the relationship between the strain time series and the potentially abnormal areas of Tonghai County through an earthquake case study, and we attempted to extract the potentially information before the earthquake from the strain time series based on Hilbert-Huang transform (HHT), from a local strain time-series view. The results showed that: (1) in the integrated solution processing of the regional strain patterns, the spherical wavelet method can adapt to the spatial variability in station density and estimate the strain patterns at multiple scales; and (2) by combining the long-term characteristics of the strain time series, the grid division, the two times standard deviation constraint, and the HHT dynamic analysis, it gives the some potential information details on the eve of an earthquake such as the Tonghai earthquake.
ISSN:1437-3254
1437-3262
DOI:10.1007/s00531-021-02002-2