This document contains instructions for running application P and S Waves Detection Tool within the EPISODES Platform. The application is a tool for automatic detection of the first arrival time of the P and S waves. The input seismogram is scanned to find potential events. It uses Deep Learning technique based on a convolutional neural network to process the seismograms and detect the first arrival times. The model is based on Ross, Meier, Hauksson and Heaton (2018). The implementation is based on SeisBench a toolbox for machine learning in seismology (Woollam, Münchmeyer, Tilmann et al. 2022).
To obtain more general information aboutworking with applications within the Platform, seeApplications Quick Start Guide.
CATEGORY Source and Shaking Parameters Estimation
KEYWORDS Waveform viewing, Picking on waveform
CITATION If you use the results or visualizations retrieved from this application in a publication, then you must cite the data source as follows:
Ross, Meier, Hauksson and Heaton (2018). Generalized Seismic Phase Detection with Deep Learning.doi: 10.1785/0120180080.
Woollam, Münchmeyer, Tilmann et al. (2022). SeisBench — A Toolbox for Machine Learning in Seismology.doi: 10.1785/0220210324.
Orlecka-Sikora, B., Lasocki, S., Kocot, J. et al. (2020) An open data infrastructure for the study of anthropogenic hazards linked to georesource exploitation., Sci Data 7, 89, doi:10.1038/s41597-020-0429-3.
