Spatio-temporal network modelling and analysis of global strong earthquakes (M w ≥ 6.0)

Autor:	Jing He, Qinjin Fan, Gianvito Scaringi, Weile Li, Gang Liu, Yujie Long, Zheng Li
Rok vydání:	2020
Předmět:	High probability 010504 meteorology & atmospheric sciences Heavy-tailed distribution 0103 physical sciences Spatial ecology Geology 01 natural sciences Seismology Physics::Geophysics 010305 fluids & plasmas 0105 earth and related environmental sciences
Zdroj:	Journal of the Geological Society. 177:883-892
ISSN:	2041-479X 0016-7649
DOI:	10.1144/jgs2019-151
Popis:	We employ a spatio-temporal network modelling approach to identify possible relations between strong earthquakes and spatial regions worldwide. A global strong earthquake dataset containing 7736 events (Mw ≥ 6.0) from 1964 to 2018 is used. Statistical results identify power-law relationships and heavy tail phenomena in the spatial patterns of strong earthquakes. The interactions between regions follow the same law, with a few regions that may be hit by successive strong earthquakes with high probability. Also, we find that the interconnections between regions are mainly related to the succession of events in time, whereas the distribution of events is extremely inhomogeneous in space. This study provides a research prototype for the spatio-temporal analysis of global strong earthquakes, laying a foundation for obtaining insights into the network modelling approach for global strong earthquakes.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6426405310f31e5d83727cf7d531851a https://doi.org/10.1144/jgs2019-151 Zobrazit plný text záznamu