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| Titel |
Denoising gravity and geomagnetic signals from Etna volcano (Italy) using multivariate methods |
| VerfasserIn |
C. Negro, F. Greco, R. Napoli, G. Nunnari |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 15, no. 5 ; Nr. 15, no. 5 (2008-10-21), S.735-749 |
| Datensatznummer |
250012760
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| Publikation (Nr.) |
 copernicus.org/npg-15-735-2008.pdf |
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| Zusammenfassung |
| Multivariate methods were applied to denoise the gravity and geomagnetic
signals continuously recorded by the permanent monitoring networks on the
Etna volcano. Gravity and geomagnetic signals observed in volcanic areas are
severely influenced by meteorological variables (i.e. pressure, temperature
and humidity), whose disturbances can make the detection of volcanic source
effects more difficult. For volcano monitoring it is necessary, therefore,
to reduce the effects of these perturbations. To date filtering noise is a
very complex problem since the spectrum of each noise component has wide
intervals of superposition and, some times, traditional filtering techniques
provide unsatisfactory results. We propose the application of two different
approaches, the adaptive neuro-fuzzy inference system (ANFIS) and the
Independent Component Analysis (ICA) to remove noise effects from gravity
and geomagnetic time series. Results suggest a good efficiency of the two
proposed approaches since they are capable of finding and effectively
representing the underlying factors or sources, and allow local features of
the signal to be detected. |
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