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Spatiotemporal analysis of GPS time series in vertical direction using independent component analysis

Liu, Bin; Dai, Wujiao; Peng, Wei; Meng, Xiaolin

Authors

Bin Liu

Wujiao Dai

Wei Peng

Xiaolin Meng xiaolin.meng@nottingham.ac.uk



Abstract

GPS has been widely used in the field of geodesy and geodynamics thanks to its technology development and the improvement of positioning accuracy. A time series observed by GPS in vertical direction usually contains tectonic signals, non-tectonic signals, residual atmospheric delay, measurement noise, etc. Analyzing these information is the basis of crustal deformation research. Furthermore, analyzing the GPS time series and extracting the non-tectonic information are helpful to study the effect of various geophysical events. Principal component analysis (PCA) is an effective tool for spatiotemporal filtering and GPS time series analysis. But as it is unable to extract statistically independent components, PCA is unfavorable for achieving the implicit information in time series. Independent component analysis (ICA) is a statistical method of blind source separation (BSS) and can separate original signals from mixed observations. In this paper, ICA is used as a spatiotemporal filtering method to analyze the spatial and temporal features of vertical GPS coordinate time series in the UK and Sichuan-Yunnan region in China. Meanwhile, the contributions from atmospheric and soil moisture mass loading are evaluated. The analysis of the relevance between the independent components and mass loading with their spatial distribution shows that the signals extracted by ICA have a strong correlation with the non-tectonic deformation, indicating that ICA has a better performance in spatiotemporal analysis.

Journal Article Type Article
Publication Date Nov 25, 2015
Journal Earth, Planets and Space
Electronic ISSN 1880-5981
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 67
APA6 Citation Liu, B., Dai, W., Peng, W., & Meng, X. (2015). Spatiotemporal analysis of GPS time series in vertical direction using independent component analysis. Earth, Planets and Space, 67, https://doi.org/10.1186/s40623-015-0357-1
DOI https://doi.org/10.1186/s40623-015-0357-1
Keywords Vertical GPS time series; Non-tectonic deformation; Spatiotemporal analysis; Common-mode error; Independent component analysis
Publisher URL http://earth-planets-space.springeropen.com/articles/10.1186/s40623-015-0357-1
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0



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