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Luke Pajer edited this page Oct 28, 2020 · 1 revision

GPS and infinitesimal strain analysis (GPS Strain)

Main Project Resources: PAJER, Luke; CRONIN, Vincent

Last Updated: October 2020

GETSI page License jupyterlab python


PROJECT OVERVIEW

The GPS_Strain Python package is a simple translation of the methods developed by Vince Cronin and Phil Resor. The purpose of this package is to make the method available to those who are interested in GPS and infinitesimal strain analysis and are more comfortable using Python.

From the GETSI teaching materials:

This module was designed for structural geology courses but can also be successfully used in geophysics, tectonics, or geohazards courses or possibly even a physics or engineering course seeking practical applications. It can be done at almost any point during the term. The module assumes that students have had a basic physical geology introduction to plate tectonics, faults, and earthquakes.

In addition to teaching purposes, the actual analysis can be used for other assessments. See the Victoria E. Worrell thesis titled "The Seismo-Lineament Analysis Method (SLAM) Applied to the South Napa Earthquake and Antecedent Events" to see an example of how this method may be used in practice.

If there are any issues or concerns with the python package, please reach out to Luke Pajer. For any questions regarding the GPS strain method, please reach out to Vince Cronin.


CONTRIBUTORS

This project is an open project, and contributions are welcome from any individual. All contributors to this project are bound by a code of conduct. Please review and follow this code of conduct as part of your contribution.

Contributions to the GPS_Strain Python Package

GPS and infinitesimal strain analysis method Authors/Developers


DATA RESOURCES

  • UNAVCO Web Services is used for the station locations and relative station velocity.

  • Stamen Map Tile Sets are used to generate the maps in this package. The Stamen map tile sets are copyright Stamen Design, under a Creative Commons Attribution (CC BY 3.0) license.