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Scalable Similarity Search in Seismology: A New Approach to Large-Scale Earthquake Detection

  • Karianne BergenEmail author
  • Clara Yoon
  • Gregory C. Beroza
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9939)

Abstract

Extracting earthquake signals from continuous waveform data recorded by networks of seismic sensors is a critical and challenging task in seismology. Earthquakes occur infrequently in long-duration data and may produce weak signals, which are challenging to detect while limiting the number of false discoveries. Earthquake detection based on waveform similarity has demonstrated success in detecting weak signals from small events, but existing techniques either require prior knowledge of the event waveform or have poor scaling properties that limit use to small data sets. In this paper, we describe ongoing research into the use of similarity search for large-scale earthquake detection. We describe Fingerprint and Similarity Thresholding (FAST), a new earthquake detection method that leverages locality-sensitive hashing to enable waveform-similarity-based earthquake detection in long-duration continuous seismic data. We demonstrate the detection capability of FAST and compare different fingerprinting schemes by performing numerical experiments on test data, with an emphasis on false alarm reduction.

Keywords

Similarity search Locality-sensitive hashing Time series Data mining Earthquake detection Template matching Signal processing 

Notes

Acknowledgments

This research was supported by NSF grant EAR-1551462 and by the Southern California Earthquake Center (contribution no. 6325). Waveform data, metadata, or data products for this study were accessed through the Northern California Earthquake Data Center, doi:10.7932/NCEDC. We thank Ossian O’Reilly for his assistance with the hashing techniques used in this work.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Karianne Bergen
    • 1
    Email author
  • Clara Yoon
    • 2
  • Gregory C. Beroza
    • 2
  1. 1.Institute for Computational and Mathematical EngineeringStanford UniversityStanfordUSA
  2. 2.Department of GeophysicsStanford UniversityStanfordUSA

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