Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity

• Tác giả: Stefania Gentili, Rita Di Giovambattista, Robert Shcherbakov, Filippos Vallianatos
• Ngôn ngữ: eng
• ISBN-13: 978-3036542638
• Thông tin xuất bản: Basel : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Mô tả vật lý: 1 electronic resource (180 p.)
• Bộ sưu tập: Tài liệu truy cập mở
• ID: 269555
• Chủ đề: 1. earthquake-prone areas; 2. pattern recognition; 3. system-analytical method; 4. Environmental science, engineering & technology; 5. Technology: general issues

Tóm tắt

Due to the significant increase in the availability of new data in recent years, as a result of the expansion of available seismic stations, laboratory experiments, and the availability of increasingly reliable synthetic catalogs, considerable progress has been made in understanding the spatiotemporal properties of earthquakes. The study of the preparatory phase of earthquakes and the analysis of past seismicity has led to the formulation of seismicity models for the forecasting of future earthquakes or to the development of seismic hazard maps. The results are tested and validated by increasingly accurate statistical methods. A relevant part of the development of many models is the correct identification of seismicity clusters and scaling laws of background seismicity. In this collection, we present eight innovative papers that address all the above topics. The occurrence of strong earthquakes (mainshocks) is analyzed from different perspectives in this Special Issue.