Software Open Access

pyVERSO - software for building and evaluating Volcano-Seismic Recognition (VSR) system, part of "VULCAN.ears" project - framework

Guillermo Cortés Moreno; Roberto Carniel; Philippe Lesage; María Ángeles Mendoza Pérez

Volcano-seismic recognition - VSR software supporting the VULCAN.ears EU-funded project via H2020-MSCA-IF-2016 Grant

This framework has been developed using Python.3 scientific libraries and wxPython.4 graphical widgets, being composed of:

  1. pyVERSO  - Command Line Interface (CLI) to create and evaluate VSR models given a labelled DB
  2. geoStudio - Graphical User Interface (GUI) acting as a frontend to perform Volcano-Independent VSR (VI.VSR) and volcano-seismic data analysis and visualization
  3. liveVSR      -  tool to remotely  perform a VSR monitoring in real-time of any volcano accessible via FDSN servers

A working snapshot of pyVERSO scripts  is freely distributed in this package, in order to build own VSR-models of volcano-seismic classes given a labelled database of a given volcano. Once they're built, can be used to monitor this volcano in real-time and continuous operation using the liveVSR tool or be exported to geoStudio to perform an offline analysis of non-labelled data. This software includes also a VSR - workpath as an example, prepared to build models from Deception Volcano.

NOTE! that in order to perform VSR tasks, it is mandatory to have a working installation of the HTK tools in your system.You can freely download your copy (after registration) at the HTK web.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No.[749249] (VULCAN.ears).

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Publication date:
December 29, 2019
DOI:
10.5281/zenodo.3594897

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Keyword(s):
VULCAN.ears pyVERSO geoStudio liveVSR Volcano-Seismic Recognition (VSR) Volcano seismology Eruption Forecasting Machine Learning Pattern Recognition
Grants:
European Commission:
  • VULCAN.ears - Volcano-seismic Unsupervised Labelling and ClAssificatioN Embedded in A Real-time Scenario (749249)
Related identifiers:
Supplementary material
License (for files):
Creative Commons Attribution 4.0 International

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