https://github.com/schipp/azimuthal_anisotropy

Retrieve azimuthal anisotropy of surface waves from inter-station measurements, following Schippkus et al. 2020
https://github.com/schipp/azimuthal_anisotropy

anisotropy open-science seismic-ambient-noise seismic-processing seismology

Last synced: about 1 year ago
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Retrieve azimuthal anisotropy of surface waves from inter-station measurements, following Schippkus et al. 2020

• Host: GitHub
• URL: https://github.com/schipp/azimuthal_anisotropy
• Owner: schipp
• License: mit
• Created: 2020-05-16T08:09:21.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2021-05-03T09:13:57.000Z (about 5 years ago)
• Last Synced: 2025-04-10T21:13:52.301Z (about 1 year ago)
• Topics: anisotropy, open-science, seismic-ambient-noise, seismic-processing, seismology
• Language: Python
• Homepage: https://doi.org/10.1093/gji/ggz565
• Size: 2.02 MB
• Stars: 8
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Azimuthal anisotropy from inter-station velocity measurements

[![DOI](https://zenodo.org/badge/264389474.svg)](https://zenodo.org/badge/latestdoi/264389474)

Determine the 2-Theta and 4-Theta terms of azimuthal anisotropy from inter-station group-velocity residuals in overlapping cells. This methodology is established in Schippkus et al. (2020), but the original version used in the paper requires the specific output of a specific isotropic inversion code, relying on the parametrization of the isotropic inversion. This new version is based purely on a .csv file of station-pair locations and inter-station group-velocity residuals.

Format of the header-less `.csv` input: `lat1, lon1, lat2, lon2, vel`

[1] Schippkus, S., Zigone, D., Bokelmann, G., AlpArray Working Group. (2020). Azimuthal anisotropy in the wider Vienna basin region: a proxy for the present-day stress field and deformation. Geophysical Journal International, 220(3), 2056–2067. http://doi.org/10.1093/gji/ggz565

## Requirements

- Python 3.5+

- Numpy

- Matplotlib

- Obspy (https://github.com/obspy/obspy/wiki)

- Shapely (https://pypi.org/project/Shapely/)

## TODO

- [x] Implement weighted average using path-lengths within cells.

- [ ] Actually test with real data.

- [ ] Synthetic example that can handle varying anisotropy.