用于事件检测和地震属性计算的ObsPy库:为自动分析准备波形

Q1 Social Sciences
R. Turner, R. Latto, A. Reading
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引用次数: 4

摘要

我们对观测地震学obspy软件包进行了扩展,以提供一个精简的工具,专门用于处理来自非震源的地震信号,特别是来自冰川和山体滑坡等变形系统的地震信号。该地震属性库提供以下功能:(1)下载和/或预处理地震波形数据;(2)利用一台或多台地震仪的多分量信号探测和编目地震事件;(3)计算识别事件的特征(“属性”/“特征”)。该工作流程由三个主要功能控制,这些功能已经通过了永久性和活动部署地震仪器所需数据类型的测试。可以将选定的STA/ lta类型(短期平均/长期平均)或其他事件检测算法应用于波形和实现的自定义函数,以计算检测到的事件的任何所需特征。代码是用Python 2/3编写的,可以在GitHub上获得详细的文档和工作示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An ObsPy Library for Event Detection and Seismic Attribute Calculation: Preparing Waveforms for Automated Analysis
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.
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来源期刊
Journal of Open Research Software
Journal of Open Research Software Social Sciences-Library and Information Sciences
CiteScore
6.50
自引率
0.00%
发文量
7
审稿时长
21 weeks
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