Data for: Machine Learning as a Detection Method of Strombolian Eruptions in Infrared Images from Mount Erebus, Antarctica

• Main Author: Dye, Brian
• Format: Dataset
• Language: unknown
• Published: Mendeley 2020
• Subjects: Geology; FOS Earth and related environmental sciences; Artificial Intelligence; Volcanology; Volcanic Seismology; Machine Learning; Volcano; Volcanism; Volcanic Eruption; Lava Lake; Mount Erebus; Antarc*; Antarctica
• Online Access: https://dx.doi.org/10.17632/ycnjmkttj4.1; https://data.mendeley.com/datasets/ycnjmkttj4/1

Jupyter notebooks written in python to identify strombolian eruptions in infrared images in the Ray lava lake atop Mount Erebus in Antarctica and cross-correlate volcano seismic data from the strombolian eruptions. These notebooks are related to the research by Brian Dye and Gabriele Morra titled, "Machine Learning as a Detection Method of Strombolian Eruptions in Infrared Images from Mount Erebus, Antarctica." The notebooks were written to be ran in Google CoLab with the current file names under the "Colab Notebooks" folder located in the "My Drive" folder of Google Drive. Some notebooks require ObsPy miniseed data, those should be run outside of Google CoLab. All outputs are contained within the folder so any notebook may be ran in or out of numerical order.