Seismic network detection probability assessment using waveforms and accounting to event association logic

Vladimir Pinsky, Avi Shapira

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)69-82
Number of pages14
JournalJournal of Seismology
Volume21
Issue number1
DOIs
StatePublished - 1 Jan 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016, Springer Science+Business Media Dordrecht.

Keywords

  • Carl Johnson detection and association algorithm
  • Detection probability of individual station
  • Epicentral distance
  • Magnitude
  • PMC method
  • Probability of completeness magnitude
  • Probability of seismic event detection
  • Seismic bulletin, waveforms
  • Seismic network detectability

ASJC Scopus subject areas

  • Geophysics
  • Geochemistry and Petrology

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