New Tables for Infrasound Event Catalogs with a Focus on Machine Learning

Abstract

Natural and anthropogenic sources such as volcanoes, earthquakes, auroral processes, chemical and nuclear explosions, rocket launches, and aircraft can generate infrasound, sound with frequencies less than 20 Hz. Both the availability of infrasound data and interest in machine learning (ML) applications have grown in recent years. Large, open-source datasets are essential to solving complex ML problems, but the field of infrasound is lacking in this arena. To increase the utility of ML for infrasound, here we present new tables for infrasound event catalogs. It is the aim that these tables be incorporated into both existing and future infrasound processing pipelines to generate large datasets ripe for use with ML/DL methods.