Clustering features and seismogenesis of the 2014 M6.6 Jinggu earthquake in Yunnan Province, China - Zheng, Jianchang (Frontiers in Earth Science, 2023)
Seismic activities can be seen as the composition of background and clustering earthquakes. It is important to identify seismicity clusters from background events. Based on the Nearest Neighbour Distance algorithm proposed by Zaliapin, we use the Gaussian mixture model (GMM) to fit its spatiotemporal distribution and use the prior probability corresponding to clustering seismicity in the GMM model as the clustering rate. After testing with synthetic catalogues under the ETAS (epidemic-type aftershock sequence) model. We believe our method can discriminate cluster events from randomly occurring background seismicity in a more physical background. We investigate the seismicity and its clustering features before the M6.6 Jinggu earthquake in Yunnan Province, China on 7 October 2014. Our results show the following: (1) The seismogenic process of this strong earthquake has three stages, which are already described by the IPE model; 2. The main shock might have been caused by the breaking of a local locked barrier in the hypocentre, and the meta-instability stage was sustained for about one year on the fault. From this study, we conclude that the evolution of seismicity clustering features can reflect changes in stress in the crust, and it is closely connected to the seismogenic process of a strong earthquake.