Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/16278
Authors: Gentili, Stefania* 
Di Giovambattista, Rita* 
Shcherbakov, Robert* 
Vallianatos, Filippos* 
Title: Editorial of the Special Issue “Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity”
Journal: Applied Sciences 
Series/Report no.: /12 (2022)
Publisher: MDPI
Issue Date: 2022
DOI: 10.3390/app12094504
Abstract: In recent years, there have been significant advances in the understanding of seismicity scaling laws, the study of spatiotemporal correlations, and earthquake clustering, with direct implications for time-dependent seismic hazard assessment. New models based on seismicity patterns, considering their physical and statistical significance, have shed light on the preparation process before large earthquakes and the evolution of clustered seismicity in time and space. On the other hand, the increasing amount of seismic data available at both local and global scales, together with accurate assessments of the reliability of the catalogs, offers new opportunities for model verification. This Special Issue brings together eight peer-reviewed articles. The articles represent a collection of innovative applications of earthquake forecasting, including the earthquake preparation process, seismic hazard assessment, statistical analysis of seismicity, synthetic catalogs, and cluster identification. It is therefore invaluable to seismologists, statistical seismologists, research students, government agencies, and academics. We are especially grateful to all the authors as without them this Special Issue would not have become a reality. As guest editors, we would like to thank the reviewers for their careful evaluation and valuable contributions. Special thanks go to Assistant Editors Carlos Sanchez and Jill Fang for their dedication to this project and their invaluable collaboration in setting up, promoting, and managing the Special Issue
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