Current Challenges in Statistical Seismology (Paperback, 1st ed. 2016)

This special issue emerged following the 2013 8th International Statistical Seismology (StatSei8) workshop in Beijing. The articles within have been collected to report on exciting new research in statistical seismology methods and applications; it contains a collection of the newest methods, techniques and results related to statistical analysis of earthquake occurrence and earthquake probability forecasting. The articles within ultimately help to define future research directions in the field. Especially, the rapid development of observation technologies has brought geophysical research into the big-data era. This includes not only non-seismicity geophysical data, such as GPS observation on surface displacement, InSAR observation of the co-seismic deformation, ionospheric observations, etc., but also extended seismological data including slow earthquakes, tremor, and VLF earthquakes. The subject of statistical seismology bridges the gap between physical and statistical models. Many significant achievements have been accomplished during the last several decades, including formulation of conditional intensity models for quantifying seismicity rates, earthquake probability forecasts, and theories related to rigorous testing of forecast models.

General

Imprint:	Birkhauser Verlag AG
Country of origin:	Switzerland
Series:	Pageoph Topical Volumes
Release date:	February 2016
First published:	2016
Editors:	Qinghua Huang • Matthew Gerstenberger • Jiancang Zhuang
Dimensions:	260 x 193 x 18mm (L x W x T)
Format:	Paperback
Pages:	322
Edition:	1st ed. 2016
ISBN-13:	978-3-319-28966-3
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Earth & environment > The environment > Environmental impact of natural disasters & phenomena Books > Science & Mathematics > Physics > Applied physics & special topics > Geophysics Books > Earth & environment > Earth sciences > Structure & properties of the Earth > Volcanology & seismology
LSN:	3-319-28966-7
Barcode:	9783319289663

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