State of unrest of active volcanoes through advanced seismic waves analysis
From 01 / 09 / 2018 to 20 / 09 /2020
The overarching goal of this project was to advance the current understanding of the relation between seismicity and eruption at volcanoes.
The application of Advanced Signal Processing and Machine Learning techniques allows for the characterization of volcanic activity and better identification of eruption precursors.
New algorithms for automatic earthquake classification were developed and applied to seismic signals recorded at active volcanoes. In the same way, new catalogues of volcanic earthquakes were generated with unprecedented resolution.
Responsible
Luciano Attilio María Zuccarello
Goal
Build a database of continuous and segmented seismic data from volcanoes representative of different eruptive scenarios.
Responsible
Luciano Attilio María Zuccarello
Goal
Develop new metrics and methods for the characterization of volcano-seismic signals through the development and application of advanced signal processing algorithms.
Responsible
Luciano Attilio María Zuccarello
Goal
Develop automated methods for identifying temporal changes in seismic time series that could be used to generate forecasts of imminent volcanic activity.
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