On statistical declustering of global earthquake catalogue

Debashis Mondal; Suhas Sastry

Presentation information

[E] Oral

S (Solid Earth Sciences ) » S-TT Technology & Techniques

[S-TT52] Seismic Big Data Analysis Based on the State-of-the-Art of Bayesian Statistics

convener:Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo), Aitaro Kato(Earthquake Research Institute, the University of Tokyo), Keisuke Yano(The University of Tokyo, Graduate School of Information Science and Technology), Takahiro Shiina(Earthquake Research Institute, The University of Tokyo)

[STT52-05] On statistical declustering of global earthquake catalogue

★Invited Papers

*Debashis Mondal¹, Suhas Sastry¹ (1.Oregon State University)

Keywords:Scale-free networks, Mixture model, Point process

Declustering of global earthquake catalogue into mainshocks, foreshocks and aftershocks is an important problem on its own, particularly for studying patterns of global seismicity. Declustering often leads to better understanding of not just mainshock-aftershock relationship, but also swarms, bursts, gaps, switching, and their distributions which can be key to various data-driven discoveries. There is a large body of literature on statistical declustering of earthquakes. In this talk, we will look into the question of magnitude, space and time interaction among mainshocks using nearest neighbor clustering method. We will also discuss point process models for declusering of global earthquake data and potential computational and other challenges.