Flank instability and sector collapses, which pose major threats, are common on volcanic islands. On 22 Dec 2018, a sector collapse event occurred at Anak Krakatau volcano in the Sunda Strait, triggering a deadly tsunami. Here we use multiparametric ground-based and space-borne data to show that prior to its collapse, the volcano exhibited an elevated state of activity, including precursory thermal anomalies, an increase in the island’s surface area, and a gradual seaward motion of its southwestern flank on a dipping décollement. Two minutes after a small earthquake, seismic signals characterize the collapse of the volcano’s flank at 13:55 UTC. This sector collapse decapitated the cone-shaped edifice and triggered a tsunami that caused 430 fatalities. We discuss the nature of the precursor processes underpinning the collapse that culminated in a complex hazard cascade with important implications for the early detection of potential flank instability at other volcanoes.

Most of the world’s 1500 active volcanoes are not instrumentally monitored, resulting in deadly eruptions which can occur without observation of precursory activity. The new Sentinel missions are now providing freely available imagery with unprecedented spatial and temporal resolutions, with payloads allowing for a comprehensive monitoring of volcanic hazards. We here present the volcano monitoring platform MOUNTS (Monitoring Unrest from Space), which aims for global monitoring, using multisensor satellite-based imagery (Sentinel-1 Synthetic Aperture Radar SAR, Sentinel-2 Short-Wave InfraRed SWIR, Sentinel-5P TROPOMI), ground-based seismic data (GEOFON and USGS global earthquake catalogues), and artificial intelligence (AI) to assist monitoring tasks. It provides near-real-time access to surface deformation, heat anomalies, SO2 gas emissions, and local seismicity at a number of volcanoes around the globe, providing support to both scientific and operational communities for volcanic risk assessment. Results are visualized on an open-access website where both geocoded images and time series of relevant parameters are provided, allowing for a comprehensive understanding of the temporal evolution of volcanic activity and eruptive products. We further demonstrate that AI can play a key role in such monitoring frameworks. Here we design and train a Convolutional Neural Network (CNN) on synthetically generated interferograms, to operationally detect strong deformation (e.g., related to dyke intrusions), in the real interferograms produced by MOUNTS. The utility of this interdisciplinary approach is illustrated through a number of recent eruptions (Erta Ale 2017, Fuego 2018, Kilauea 2018, Anak Krakatau 2018, Ambrym 2018, and Piton de la Fournaise 2018–2019). We show how exploiting multiple sensors allows for assessment of a variety of volcanic processes in various climatic settings, ranging from subsurface magma intrusion, to surface eruptive deposit emplacement, pre/syn-eruptive morphological changes, and gas propagation into the atmosphere. The data processed by MOUNTS is providing insights into eruptive precursors and eruptive dynamics of these volcanoes, and is sharpening our understanding of how the integration of multiparametric datasets can help better monitor volcanic hazards.

After a month-long increase in activity at the summit craters, on 24 December 2018, the Etna volcano experienced a short-lived lateral effusive event followed by a rapid resumption of low-level explosive and degassing activity at the summit vents. By combining space (Moderate Resolution Imaging Spectroradiometer; MODIS and SENTINEL-2 images) and ground-based geophysical data, we track, in near real-time, the thermal, seismic and infrasonic changes associated with Etna’s activity during the September–December 2018 period. Satellite thermal data reveal that the fissural eruption was preceded by a persistent increase of summit activity, as reflected by overflow episodes in New SouthEast Crater (NSE) sector. This behavior is supported by infrasonic data, which recorded a constant increase both in the occurrence and in the energy of the strombolian activity at the same crater sectors mapped by satellite. The explosive activity trend is poorly constrained by the seismic tremor, which shows instead a sudden increase only since the 08:24 GMT on the 24 December 2018, almost concurrently with the end of the infrasonic detections occurred at 06:00 GMT. The arrays detected the resumption of infrasonic activity at 11:13 GMT of 24 December, when tremors almost reached the maximum amplitude. Infrasound indicates that the explosive activity was shifting from the summit crater along the flank of the Etna volcano, reflecting, with the seismic tremor, the intrusion of a gas-rich magma batch along a ~2.0 km long dyke, which reached the surface generating an intense explosive phase. The dyke propagation lasted for almost 3 h, during which magma migrated from the central conduit system to the lateral vent, at a mean speed of 0.15–0.20 m s−1. Based on MODIS and SENTINEL 2 images, we estimated that the summit outflows erupted a volume of lava of 1.4 Mm3 (±0.5 Mm3), and that the lateral effusive episode erupted a minimum volume of 0.85 Mm3 (±0.3 Mm3). The results presented here outline the support of satellite data on tracking the evolution of volcanic activity and the importance to integrate satellite with ground-based geophysical data in improving assessments of volcanic hazard during eruptive crises.