Seismic network detection probability assessment using waveforms and accounting to event association logic
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- 作者：Vladimir Pinsky ; Avi Shapira
- 关键词：Seismic network detectability ; Probability of seismic event detection ; Magnitude ; Detection probability of individual station ; Epicentral distance ; Seismic bulletin ; waveforms ; Carl Johnson detection and association algorithm ; Probability of completeness magnitude ; PMC method
- 刊名：Journal of Seismology
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：21
- 期：1
- 页码：69-82
- 全文大小：
- 刊物类别：Earth and Environmental Science
- 刊物主题：Geophysics/Geodesy; Structural Geology; Hydrogeology; Geotechnical Engineering & Applied Earth Sciences;
- 出版者：Springer Netherlands
- ISSN：1573-157X
- 卷排序：21
文摘
The geographical area where a seismic event of magnitude M ≥ Mt is detected by a seismic station network, for a defined probability is derived from a station probability of detection estimated as a function of epicentral distance. The latter is determined from both the bulletin data and the waveforms recorded by the station during the occurrence of the event with and without band-pass filtering. For simulating the real detection process, the waveforms are processed using the conventional Carl Johnson detection and association algorithm. The attempt is presented to account for the association time criterion in addition to the conventional approach adopted by the known PMC method.