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Summary

The Polarization bundle of the Noise Toolkit is based on the eigen-decomposition of the spectra covariance matrix of a sliding window of three-component seismic data, as described by Koper and Hawley (2010). The derived frequency dependent polarization attributes are:

  • degree of polarization (β^2) - a measure of the extent to which noise is organized
  • polarization azimuth (θH) - a horizontal direction parameter representing azimuth of the polarization ellipsoid
  • polarization inclination (θV) - a vertical direction parameter representing inclination of the polarization ellipsoid
  • phase difference between components:
    o phase difference between the vertical and principal horizontal components (Φ VH)
    o phase difference between the horizontal components (Φ HH)


Figure 1. Plot of the polarization parameters obtained by processing one hour of BHZ, BHN, BHE data of the NM.SLM station (St. Louis, MO station, Cooperative New Madrid Seismic Network, NM) between 2009-01-01 01:00:00.0 and 2009-01-01 02:00:00.0 UTC.

This bundle is composed of 3 Python scripts:

  1. ntk_computePolarization.py – an ObsPy script to calculate polarization parameters for a given station and time window
  2. ntk_extractPolarHour.py – a Python script to extract polarization parameters for the given channels and bounding parameters
  3. ntk_binPolarDay.py – a Python script to bin polarization attributes to daily files for a given channel tag and bounding parameters

Contributions

We welcome patches and enhancements to this software. When developing patches, please pay particular attention to ease of use and maintenance and also keep dependencies to a minimum (contact the project manager).

References

  • Koper K.D, and V.L. Hawley, Frequency dependent polarization analysis of ambient seismic noise recorded at a broadband seismometer in the Central United States, Earthquake Science, 23, 439-447, 2010. doi:10.1007/s11589-010-0743-5.

Credits
  • IRIS DMC Products Team
  • Keith Koper University of Utah

Metadata

  • Category: Data Processing
  • Language: Python
  • Keywords:

    noise-toolkit , Polarization, Python

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Manager: Manochehr Bahavar