Volcanic Processes Monitoring and Hazard Assessment Using Integration of Remote Sensing and Ground-Based Techniques

Abstract

The monitoring of active volcanoes is a complex task based on multidisciplinary and integrated analyses that use ground, drones, and satellite monitoring devices. Over time, and with the development of new technology and increasing frequency of acquisition, the use of remote sensing to accomplish this important task has grown enormously. This is especially so with the use of drones and satellites for classifying eruptive events, detecting the opening of new vents, the spreading of lava flows on the surface or ash plumes in the atmosphere, the fallout of tephra on the ground, the intrusion of new magma within the volcano edifice, and the deformation preceding impending eruptions, and others besides. The main challenge in using remote sensing techniques is to develop automated and reliable systems that may assist the decision-maker in volcano monitoring, hazard assessment, and risk reduction. The integration with ground-based techniques represents a valuable additional aspect that makes the proposed methods more robust and reinforces the results obtained. This collection of papers is focused on several active volcanoes, such as Stromboli, Etna, and Vulcano in Italy; the Long Valley caldera and Kilauea volcano in the USA; and Cotopaxi in Ecuador. The authors make use of several different methods to predict and forecast the volcanoes’ future behavior, using insights from the available data or from new automated routines applied to the analysis of existing data. The aim is to enable rapid assessments of the state of a volcano, discovering the connection between variables apparently not related to each other and to the state of the volcano. The development of new or automated routines is an important step forward in the process of forecasting eruptive activities, and this collection comprises several such examples. This Special Issue on the monitoring of active volcanoes using an integration of remote sensing and ground-based techniques comprises twelve papers. Three are focused on the results obtained for Stromboli volcano (Italy), where eruptive activity varies from moderate Strombolian, often accompanied by summit overflows, to highly explosive paroxysms, which are very dangerous both for the local population and for the many tourists who frequently visit the island. The first paper [1] presents the precursors of the paroxysmal and devastating explosive eruptions occurring in 2019. This paper applied an unsupervised analysis of seismic and infrasonic data, comprising a dataset of 14,289 Strombolian explosions occurring over 10 months, using a Self-Organizing Map (SOM) neural network to recognize changes in the eruptive patterns preceding the paroxysms. The SOM analysis identified three main clusters indicating a clear change in Stromboli’s eruptive style before the paroxysm of 3 July 2019. The main clusters were then compared with the recordings of the fixed monitoring cameras and with the Ground-Based Interferometric Synthetic Aperture Radar measurements, showing that they were associated with different types of Strombolian explosions and different deformation patterns of the summit area.