Characterization of GPS time series at the Neapolitan volcanic area by statistical analysis

• Published in: Journal of Geophysical Research: Solid Earth Vol. 115; no. B10
• Main Authors: Bottiglieri, M., Falanga, M., Tammaro, U., De Martino, P., Obrizzo, F., Godano, C., Pingue, F.
• Format: Journal Article
• Language: English
• Published: Washington, DC Blackwell Publishing Ltd 01-10-2010; American Geophysical Union
• Subjects: background level; Deformation; Earth sciences; Earth, ocean, space; Exact sciences and technology; Geodetic surveys; Geodetics; Geophysics; Global positioning systems; GPS; ground deformation; Rock deformation; Satellites; Statistical analysis; Time series; models; Statistical moment; simulation; Independent component analysis; Time series; kurtosis; Laplacian; Global Positioning System; noise; deformation; Amplitude distribution; statistical analysis; filtering
• ISSN: 0148-0227; 2169-9313; 2156-2202; 2169-9356
• DOI: 10.1029/2009JB006594

The GPS time series recorded at the Neapolitan volcanic area reveals a very peculiar behavior. When a clear deformation is observed, the amplitude distribution evolves from a super‐Gaussian to a broader distribution. This behavior can be characterized by evaluating the kurtosis. Spurious periodic components were evidenced by independent component analysis and then removed by filtering the original signal. The time series for all stations was modeled with a fifth‐order polynomial fit, which represents the deformation history at that place. Indeed, when this polynomial is subtracted from the time series, the distributions again become super‐Gaussian. A simulation of the deformation time evolution was performed by superposing a Laplacian noise and a synthetic deformation history. The kurtosis of the obtained signals decreases as the superposition increases, enlightening the insurgence of the deformation. The presented approach represents a contribution aimed at adding further information to the studies about the deformation at the Neapolitan volcanic area by revealing geologically relevant data.