Probabilistic Earthquake Location in 2D
Demonstrates the effect of observation and velocity model errors on the estimation of epicenter location. Assumed data are single P-phase arrivals at each station. The method is based on forward modelling of hyperbolas and their joint likelihood.
INPUTS
eqX, eqX: true epicenter location (km)
staX, staY: station coordinates (km)
params: parameter object (see description below)
OUTPUT
- figure of the used parabolas and the resulting spatial PDF of the epicenter
- error PDFs of the estimated magnitude, horizontal and vertical coordinates
This code was introduced in the following paper to demonstrate the effect of station distribution on magnitude errors.
Kamer & Hiemer (2015), Data-driven spatial b value estimation with applications to California seismicity: To b or not to b, JGR Solid Earth, doi:10.1002/2014JB011510.
Examples:
1) Event at [10,10] using the default station distribution
probEqLoc2D(10, 10);
2) Same event with 3 stations
probEqLoc2D(10, 10, [10 20 30], [20 15 25]);
Zitieren als
Yavor Kamer (2024). Probabilistic Earthquake Location in 2D (https://www.mathworks.com/matlabcentral/fileexchange/61280-probabilistic-earthquake-location-in-2d), MATLAB Central File Exchange. Abgerufen.
Kompatibilität der MATLAB-Version
Plattform-Kompatibilität
Windows macOS LinuxKategorien
- Sciences > Geoscience > Geology >
- Sciences > Geoscience > Seismology >
- Engineering > Civil and Environmental Engineering > Earthquake Engineering >
Tags
Quellenangaben
Inspiriert von: interparc, Generate Random Numbers from a 2D Discrete Distribution
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Version | Veröffentlicht | Versionshinweise | |
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1.1.0.0 | updated the demo pdf |
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1.0.0.0 |