Poster #113, Tectonic Geodesy
Exploratory visualization and analysis of high resolution GPS data across California
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Poster Presentation
2020 SCEC Annual Meeting, Poster #113, SCEC Contribution #10644 VIEW PDF
used computers. We then normalized and interpolated the displacement data onto a regular grid across Southern California to produce exploratory animated visualizations. For exploratory purposes we also investigated the viability of a dynamic mode decomposition (DMD) of the data with the goal of finding low dimensional representation of large-scale deformation features. With the Python scripts we authored, users are able to plot the three-component time series for a given GPS station, interpolate displacements onto a regular grid in a given region, and animate the evolution of the displacements over a given time interval. Our initial application of DMD to the time series indicates that, although DMD is ideal for time-dependent observational data, the complexity of underlying features may indicate that the underlying features cannot be effectively characterized using harmonic and decaying modes alone. Packaging the dataset in parquet files will make the dataset more accessible for sophisticated data analysis within the rapidly proliferating Python language, as opposed to the niche languages that similar analyses are currently being done on. Additional analyses are needed in order to determine the viability of a dynamic mode decomposition for revealing patterns in the data.
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