Foreshocks and Short-Term Hazard Assessment to Large Earthquakes using Complex Networks: the Case of the 2009 L’Aquila Earthquake
نویسندگان
چکیده
The monitoring of statistical network properties could be useful for the short-term hazard assessment of the occurrence of mainshocks in the presence of foreshocks. Using successive connections between events acquired from the 10 earthquake catalogue of INGV for the case of the L’Aquila (Italy) mainshock (Mw = 6.3) of 6th April 2009, we provide evidence that network measures, both global (e.g. average clustering coefficient, small-world index) and local (betweenness centrality), could potentially be exploited for forecasting purposes both in time and space. Our results reveal statistically significant increases of the topological measures and a nucleation of the betweenness centrality around the location of the epicenter about two months before the mainshock. The results of the analysis are robust even when considering either large 15 or off-centered the main event space-windows.
منابع مشابه
Interactive comment on “Foreshocks and Short-Term Hazard Assessment to Large Earthquakes using Complex Networks: the Case of the 2009 L’Aquila Earthquake” by E. Daskalaki
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Interactive comment on “Foreshocks and Short-Term Hazard Assessment to Large Earthquakes using Complex Networks: the Case of the 2009 L’Aquila Earthquake” by E. Daskalaki et al
In the last years, complex network theory has been applied in a variety of studies on the spatio-temporal organization of seismicity. The present manuscript by Daskalaki et al. adds to this increasing body of literature by reporting efforts to utilize network approaches for characterizing the foreshock activity associated with the 2009 L’Aquila earthquake. Similar evolving network analyses are ...
متن کاملInteractive comment on “Foreshocks and Short-Term Hazard Assessment to Large Earthquakes using Complex Networks: the Case of the 2009 L’Aquila Earthquake” by E. Daskalaki et al
Response. The proposed approach results to a directed network. In the appendix we give the definitions of statistical measures for directed networks. For example the first equation in the appendix gives the clustering coefficient for a directed graph, as it is defined by Fagiolo, Physical Review E 76, 026107 2007. According to this definition, the clustering coefficient is again the ratio betwe...
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