Following the abrupt geochemical and geophysical variations that occurred on the island of Vulcano in September 2021, the search for previous multidisciplinary data on decades-long time spans became necessary to contextualize the newly recorded anomalous variations, which represented a serious threat for the local population. Our analyses of ‘vintage’ reports, old documents and analogue sei…
Magnitude estimation is a critical task in seismology, and conventional methods usually require dense seismic station arrays to provide data with sufficient spatiotemporal distribution. In this context, we propose the Earthquake Graph Network (EQGraphNet) to enhance the performance of single-station magnitude estimation. The backbone of the proposed model consists of eleven convolutional neural…
A common limitation in applying any deep learning and machine learning techniques is the limited labelled dataset which can be addressed through Data augmentation (DA). SeisAug is a DA python toolkit to address this challenge in seismological studies. DA. DA helps to balance the imbalanced classes of a dataset by creating more examples of under-represented classes. It significantly mitigates ov…