An ObsPy library for event detection and seismic attribute calculation: preparing waveforms for automated analysis

TL;DR

This paper introduces an extension to the ObsPy library that streamlines seismic data processing, event detection, and attribute calculation specifically for non-earthquake sources like glaciers and landslides.

Contribution

It provides a new Python-based toolkit for downloading, processing, detecting, and characterizing seismic signals from deforming systems, enhancing automated analysis capabilities.

Findings

Successfully tested across various seismic data types

Supports customizable event detection algorithms

Facilitates comprehensive seismic attribute calculation

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.