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| Titel |
Decomposing spatio-temporal seismicity patterns |
| VerfasserIn |
C. Goltz |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 1, no. 1/2 ; Nr. 1, no. 1/2, S.83-92 |
| Datensatznummer |
250000025
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| Publikation (Nr.) |
 copernicus.org/nhess-1-83-2001.pdf |
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| Zusammenfassung |
| Seismicity is a
distributed process of great spatial and temporal variability and
complexity. Efforts to characterise and describe the evolution of
seismicity patterns have a long history. Today, the detection of changes
in the spatial distribution of seismicity is still regarded as one of the
most important approaches in monitoring and understanding seismicity. The
problem of how to best describe these spatio-temporal changes remains,
also in view of the detection of possible precursors for large
earthquakes. In particular, it is difficult to separate the superimposed
effects of different origin and to unveil the subtle (precursory) effects
in the presence of stronger but irrelevant constituents. I present an
approach to the latter two problems which relies on the Principal
Components Analysis (PCA), a method based on eigen-structure analysis, by
taking a time series approach and separating the seismicity rate patterns
into a background component and components of change. I show a sample
application to the Southern California area and discuss the promising
results in view of their implications, potential applications and with
respect to their possible precursory qualities. |
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