Abstract
Muography is a novel method of visualizing the internal structures of active volcanoes by using high-energy near-horizontally arriving cosmic muons. The purpose of this study is to show the feasibility of muography to forecast the eruption event with the aid of the convolutional neural network (CNN). In this study, seven daily consecutive muographic images were fed into the CNN to compute the probability of eruptions on the eighth day, and our CNN model was trained by hyperparameter tuning with the Bayesian optimization algorithm. By using the data acquired in Sakurajima volcano, Japan, as an example, the forecasting performance achieved a value of 0.726 for the area under the receiver operating characteristic curve, showing the reasonable correlation between the muographic images and eruption events. Our result suggests that muography has the potential for eruption forecasting of volcanoes.
Highlights
Muography is a novel method of visualizing the internal structures of active volcanoes by using highenergy near-horizontally arriving cosmic muons
We investigated the effectiveness of a convolutional neural network (CNN) for eruption forecasting at the Showa crater of Sakurajima volcano based on muograms
We have shown that our method may achieve moderate performance for day-level eruption forecasting at the Showa crater of Sakurajima volcano
Summary
Muography is a novel method of visualizing the internal structures of active volcanoes by using highenergy near-horizontally arriving cosmic muons. The observation, in conjunction with the observation of a low-density magma pathway imaged underneath a solidified magma deposit, confirmed that muograms could resolve a volcano structure with more precision than the preexisting geophysical techniques. Since this first experimental study on the internal structure of volcanos in 2007, similar experiments have been carried in Japan[3,4,5,6] and in the US7 and Europe[8,9,10,11]. We focused on muographic data acquired at Sakurajima volcano, Japan, between 2014 and 2016 when it was most activated in the last eruption episode (2009–2017)
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