An ObsPy library for event detection and seismic attribute calculation: preparing waveforms for automated analysis
Abstract
We have implemented an extension for the observational seismology obspy software package to provide a streamlined tool tailored to the processing of seismic signals from non-earthquake sources, in particular those from deforming systems such as glaciers and landslides. This seismic attributes library provides functionality to: (1) download and/or pre-process seismic waveform data; (2) detect and catalogue seismic events using multi-component signals from one or more seismometers; and (3) calculate characteristics ('attributes'/'features') of the identified events. The workflow is controlled by three main functions that have been tested for the breadth of data types expected from permanent and campaign-deployed seismic instrumentation. A selected STA/LTA-type (short-term average/long-term average), or other, event detection algorithm can be applied to the waveforms and user-defined functions implemented to calculate any required characteristics of the detected events. The code is written in Python 2/3 and is available on GitHub together with detailed documentation and worked examples.
Cite
@article{arxiv.2108.08601,
title = {An ObsPy library for event detection and seismic attribute calculation: preparing waveforms for automated analysis},
author = {Ross J. Turner and Rebecca B. Latto and Anya M. Reading},
journal= {arXiv preprint arXiv:2108.08601},
year = {2021}
}
Comments
13 pages, 3 figures; submitted to JORS. Code available at https://github.com/rossjturner/seismic\_attributes