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This paper addresses the classification of images depicting the eruptive activity of Mount Etna, captured by a network of ground-based thermal cameras. The proposed approach utilizes Convolutional Neural Networks (CNNs), focusing on pretrained models. Eight popular pretrained neural networks underwent systematic evaluation, revealing their effectiveness in addressing the classification problem. The experimental results demonstrated that, following a retraining phase with a limited dataset, specific networks such as VGG-16 and AlexNet, achieved an impressive total accuracy of approximately 90%. Notably, VGG-16 and AlexNet emerged as practical choices, exhibiting individual class accuracies exceeding 90%. The case study emphasized the pivotal role of transfer learning, as attempts to solve the classification problem without pretrained networks resulted in unsatisfactory outcomes.

Paroxysmal explosive activity at Etna volcano (Italy) has become quite frequent over the last three decades, raising concerns with the civil protection authorities due to its significant impact on the local population, infrastructures, viability and air traffic. Between 4 July and 15 August 2024, during the tourist season peak when the local population doubles, Etna volcano gave rise to a sequence of six paroxysmal explosive events from the summit crater named Voragine. This is the oldest and largest of Etna’s four summit craters and normally only produces degassing, with the previous explosive sequences occurring in December 2015 and May 2016. In this paper, we use thermal images recorded by the monitoring system maintained by the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV–OE), and an automatic procedure previously tested in order to automatically define the eruptive parameters of the six lava fountain episodes. These data allowed us to infer the eruptive processes and gain some insights on the evolution of the explosive sequences that are useful for hazard assessment. Specifically, our results lead to the hypothesis that the Voragine shallow storage has a capacity of ~12–15 Mm3, which was not completely emptied with the last two paroxysmal events. It is thus possible that one or two additional explosive paroxysmal events could occur in the future. It is noteworthy that an additional paroxysmal episode occurred at Voragine on 10 November 2024, after the submission of this paper, thus confirming our hypothesis.

Abstract Lava overflows are highly hazardous phenomena that can occur at Stromboli. They can destabilize the crater area and the “Sciara del Fuoco” unstable slope, formed by several sector collapses, which can generate potentially tsunamigenic landslides. In this study, we have identified precursors of the October-November 2022 effusive crisis through seismic and thermal camera measurements. We analyzed the lava overflow on October 9, which was preceded by a crater-rim collapse, and the overflow on November 16. In both cases, seismic precursors anticipating the overflow onset have been observed. The analysis of the seismic and thermal data led to the conclusion that the seismic precursors were caused by an escalating degassing process from the eruptive vent, which climaxed with the overflows. Volcano deformation derived from ground-based InSAR and strainmeter data showed that inflation of the crater area accompanied the escalating degassing process up to the beginning of the lava overflows. The inflation of the crater area was especially evident in the October 9 episode, which also showed a longer seismic precursor compared to the November 16 event (58 and 40 min respectively). These results are important for understanding Stromboli’s eruptive mechanisms and open a perspective for early warning of potentially dangerous phenomena.

The 2021 eruption at Tajogaite (Cumbre Vieja) volcano (La Palma, Spain) was characterized by Strombolian eruptions, Hawaiian fountaining, white gas-dominated and grey ash-rich plumes, and lava effusion from multiple vents. The variety of eruptive styles displayed simultaneously and throughout the eruption presents an opportunity to explore controls on explosivity and the relationship between explosive and effusive activity. Explosive eruption dynamics were recorded using ground-based thermal photography and videography. We show results from the analysis of short (

Stromboli is an open-conduit active volcano located in the southern Tyrrhenian Sea and is the easternmost island of the Aeolian Archipelago. It is known as “the lighthouse of the Mediterranean” for its continuous and mild Strombolian-type explosive activity, occurring at the summit craters. Sometimes the volcano undergoes more intense explosions, called “major explosions” if they affect just the summit above 500 m a.s.l. or “paroxysms” if the whole island is threatened. Effusive eruptions are less frequent, normally occurring every 3–5 years, and may be accompanied or preceded by landslides, crater collapses and tsunamis. Given the small size of the island (maximum diameter of 5 km, NE–SW) and the consequent proximity of the inhabited areas to the active craters (maximum distance 2.5 km), it is of paramount importance to use all available information to forecast the volcano’s eruptive activity. The availability of a detailed record of the volcano’s eruptive activity spanning some centuries has prompted evaluations on its possible short-term evolution. The aim of this paper is to present some statistical insights on the eruptive activity at Stromboli using a catalogue dating back to 1879 and reviewed for the events during the last two decades. Our results confirm the recent trend of a significant increase in major explosions, small lava flows and summit crater collapses at the volcano, and might help monitoring research institutions and stakeholders to evaluate volcanic hazards from eruptive activity at this and possibly other open-vent active basaltic volcanoes.

Between December 2020 and February 2022, the South East Crater of Etna has been the source of numerous eruptions, mostly characterized by the emission of lava fountains, pyroclastic material and short-lasting lava flows. Here we estimate the volume and distribution of the lava deposits by elaborating multi-source satellite imagery. SEVIRI data have been elaborated using CL-HOTSAT to estimate the lava volume emitted during each event and calculate the cumulative volume; Pléiades and WorldView-1 data have been used to derive Digital Surface Models, whose differences provide thickness distributions and hence volumes of the volcanic deposits. We find a good agreement, with the total average lava volume obtained by SEVIRI reaching 73.2 × 106 m3 and the one from optical data amounting to 67.7 × 106 m3. This proves the robustness of both techniques and the accuracy of the volume estimates, which provide important information on the lava flooding history and evolution of the volcano.

During the last two decades, the Etna volcano has undergone several sequences of lava fountaining (LF) events that have had a major impact on road conditions, infrastructure and the local population. In this paper, we consider the LF episodes occurring between 2011 and 2022, calculating their erupted volumes using the images recorded by the monitoring thermal cameras and applying a manual procedure and a dedicated software to determine the lava fountain height over time, which is necessary to obtain the erupted volume. The comparison between the results indicates the two procedures match quite well, the main differences occurring when the visibility is poor and data are interpolated. With the aim of providing insights for hazard assessment, we have fitted some probabilistic models of both the LF inter-event times and the erupted volumes of pyroclastic material. In more detail, we have tested power-law distributions against log-normal, Weibull, generalised Pareto and log-logistic. Results show that the power-law distribution is the most likely among the alternatives. This implies the lack of characteristic scales for both the inter-event time and the pyroclastic volume, which means that we have no indication as to when a new episode of LF will occur and/or how much material will be erupted. What we can reasonably say is only that short inter-event times are more frequent than long inter-event times, and that LF characterised by small volumes are more frequent than LF with high volumes. However, if the hypothesis that magma accumulates on Etna at a rate of about 0.8 m3s−1 holds, the material accumulated in the source region from the beginning of the observation period (2011) to the present (2022) has already been ejected. In simple terms, there is no accumulated magma in the shallow storage that is prone to be erupted in the near future.

Between 13 December 2020 and 21 February 2022, Etna volcano produced a sequence of 66 paroxysmal explosive eruptions, with Strombolian activity at the summit craters climaxing in lava fountains and eruption columns extending several kilometers above the craters, accompanied by minor and short-lasting lava flows from the crater rim. We selected three of these episodes that occurred within a short space of time, between 13 December 2020 and 12 March 2021, of different magnitude (i.e., erupted volume) and intensity (i.e., mass eruption rate or instantaneous eruption rate), and analyzed them from a multidisciplinary perspective. The aim was to gain insights into those parameters that mostly reveal the eruptive process for hazard assessment purposes. The multidisciplinary data consist of calibrated visible images, thermal images, seismic and infrasound data, ground deformation detected from the strainmeters, as well as satellite SEVIRI images. From these data, we obtained the timing of each paroxysmal event, the erupted volume in terms of tephra and lava flows, and the corresponding deflation of the source region, together with the development of the lava fountains and eruption columns with time. The results enabled determining that the smallest episode was that of 13 December 2020, which comprised three distinctive pulses but did not produce an eruptive column detectable from either monitoring cameras or satellites. The 28 February 2021 episode was remarkable for the short amount of time required to reach the climax, and was the most intense, whereas the 12 March 2021 event showed the longest duration but with an intensity between that of the previous two. Our results show that these three paroxysmal events display a typical trend, with the first event also being the smallest in terms of both erupted volume and intensity, the second being the most intense, and the third the one of greatest magnitude but less intense than the second. This is coherent with the end of the first paroxysmal phase on 1 April 2021, which was followed by 48 days of eruptive pause before starting again. In this context, the end of the paroxysmal phase was anticipated by a more effusive episode, thus heralding a temporary decline in the gas content within the feeding magma batch.

The monitoring of active volcanoes is a complex task based on multidisciplinary and integrated analyses that use ground, drones, and satellite monitoring devices [...]

Low elevation flank eruptions represent highly hazardous events due to their location near, or in, communities. Their potentially high effusion rates can feed fast moving lava flows that enter populated areas with little time for warning or evacuation, as was the case at Nyiragongo in 1977. The January–March 1974 eruption on the western flank of Mount Etna, Italy, was a low elevation effusive event, but with low effusion rates. It consisted of two eruptive phases, separated by 23 days of quiescence, and produced two lava flow fields. We describe the different properties of the two lava flow fields through structural and morphological analyses using UAV-based photogrammetry, plus textural and rheological analyses of samples. Phase I produced lower density (∼2,210 kg m−3) and crystallinity (∼37%) lavas at higher eruption temperatures (∼1,080°C), forming thinner (2–3 m) flow units with less-well-developed channels than Phase II. Although Phase II involved an identical source magma, it had higher densities (∼2,425 kg m−3) and crystallinities (∼40%), and lower eruption temperatures (∼1,030°C), forming thicker (5 m) flow units with well-formed channels. These contrasting properties were associated with distinct rheologies, Phase I lavas having lower viscosities (∼103 Pa s) than Phase II (∼105 Pa s). Effusion rates were higher during Phase I (≥5 m3/s), but the episodic, short-lived nature of each lava flow emplacement event meant that flows were volume-limited and short (≤1.5 km). Phase II effusion rates were lower (≤4 m3/s), but sustained effusion led to flow units that could still extend 1.3 km, although volume limits resulted from levee failure and flow avulsion to form new channels high in the lava flow system. We present a petrologically-based model whereby a similar magma fed both phases, but slower ascent during Phase II may have led to greater degrees of degassing resulting in higher cooling-induced densities and crystallinities, as well as lower temperatures. We thus define a low effusion rate end-member scenario for low elevation effusive events, revealing that such events are not necessarily of high effusion rate and velocity, as in the catastrophic event scenarios of Etna 1669 or Kilauea 2018.

The Etna volcano is renowned worldwide for its extraordinary lava fountains that rise several kilometers above the vent and feed eruptive columns, then drift hundreds of kilometers away from the source. The Italian Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE) is responsible for the monitoring of Mt. Etna, and for this reason, has deployed a network of visible and thermal cameras around the volcano. From these cameras, INGV-OE keeps a keen eye, and is able to observe the eruptive activity, promptly advising the civil protection and aviation authorities of any changes, as well as quantifying the spread of lava flows and the extent of pyroclastic and ash plumes by using a careful analysis of the videos recorded by the monitoring cameras. However, most of the work involves analysis carried out by hand, which is necessarily approximate and time-consuming, thus limiting the usefulness of these results for a prompt hazard assessment. In addition, the start of lava fountains is often a gradual process, increasing in strength from Strombolian activity, to intermediate explosive activity, and eventually leading to sustained lava fountains. The thresholds between these different fields (Strombolian, Intermediate, and lava fountains) are not clear cut, and are often very difficult to distinguish by a manual analysis of the images. In this paper, we presented an automated routine that, when applied to thermal images and with good weather conditions, allowed us to detect (1) the starting and ending time of each lava fountain, (2) the area occupied by hot pyroclasts, (3) the elevation reached by the lava fountains over time, and (4) eventually, to calculate in real-time the erupted volume of pyroclasts, giving results close to the manual analysis but more focused on the sustained portion of the lava fountain, which is also the most dangerous. This routine can also be applied to other active volcanoes, allowing a prompt and uniform definition of the timing of the lava fountain eruptive activity, as well as the magnitude and intensity of the event.

Two paroxysmal explosions occurred at Stromboli on 3 July and 28 August 2019, the first of which caused the death of a young tourist. After the first paroxysm an effusive activity began from the summit vents and affected the NW flank of the island for the entire period between the two paroxysms. We carried out an unsupervised analysis of seismic and infrasonic data of Strombolian explosions over 10 months (15 November 2018–15 September 2019) using a Self-Organizing Map (SOM) neural network to recognize changes in the eruptive patterns of Stromboli that preceded the paroxysms. We used a dataset of 14,289 events. The SOM analysis identified three main clusters that showed different occurrences with time indicating a clear change in Stromboli’s eruptive style before the paroxysm of 3 July 2019. We compared the main clusters with the recordings of the fixed monitoring cameras and with the Ground-Based Interferometric Synthetic Aperture Radar measurements, and found that the clusters are associated with different types of Strombolian explosions and different deformation patterns of the summit area. Our findings provide new insights into Strombolian eruptive mechanisms and new perspectives to improve the monitoring of Stromboli and other open conduit volcanoes.

Stromboli volcano has a persistent activity that is almost exclusively explosive. Predominated by low intensity events, this activity is occasionally interspersed with more powerful episodes, known as major explosions and paroxysms, which represent the main hazards for the inhabitants of the island. Here, we propose a machine learning approach to distinguish between paroxysms and major explosions by using satellite-derived measurements. We investigated the high energy explosive events occurring in the period January 2018–April 2021. Three distinguishing features are taken into account, namely (i) the temporal variations of surface temperature over the summit area, (ii) the magnitude of the explosive volcanic deposits emplaced during each explosion, and (iii) the height of the volcanic ash plume produced by the explosive events. We use optical satellite imagery to compute the land surface temperature (LST) and the ash plume height (PH). The magnitude of the explosive volcanic deposits (EVD) is estimated by using multi-temporal Synthetic Aperture Radar (SAR) intensity images. Once the input feature vectors were identified, we designed a k-means unsupervised classifier to group the explosive events at Stromboli volcano based on their similarities in two clusters: (1) paroxysms and (2) major explosions. The major explosions are identified by low/medium thermal content, i.e., LSTI around 1.4 °C, low plume height, i.e., PH around 420 m, and low production of explosive deposits, i.e., EVD around 2.5. The paroxysms are extreme events mainly characterized by medium/high thermal content, i.e., LSTI around 2.3 °C, medium/high plume height, i.e., PH around 3330 m, and high production of explosive deposits, i.e., EVD around 10.17. The centroids with coordinates (PH, EVD, LSTI) are: Cp (3330, 10.7, 2.3) for the paroxysms, and Cme (420, 2.5, 1.4) for the major explosions.

New maps of the summit of Mount Etna volcano (1:5000–1:4000), derived from helicopter photogrammetry, thermal images and terrestrial laser scanner survey, are here presented. These maps indicate the main morpho-structural changes occurring during the powerful explosive and effusive eruptions involving the summit craters of Etna over the first two weeks of December 2015. The survey enabled identifying the proximal erupted volume (7.2 ± 0.14 × 106 m3) and the size and location of the vent causing the powerful explosive activity inside the Central Crater. Our survey also outlines the growth of a recent (2011–2015) summit cone on top of a former pit crater, named New SE-Crater. This new cone is by now comparable in size to the former SE-Crater. The shape and size of two small cinder cones that formed on the upper eastern flank of the summit zone in May–July 2014 are also shown. This approach can be used in fast and frequent monitoring of very active volcanoes.

On 13 December 2020, Etna volcano entered a new eruptive phase, giving rise to a number of paroxysmal episodes involving increased Strombolian activity from the summit craters, lava fountains feeding several-km high eruptive columns and ash plumes, as well as lava flows. As of 2 August 2021, 57 such episodes have occurred in 2021, all of them from the New Southeast Crater (NSEC). Each paroxysmal episode lasted a few hours and was sometimes preceded (but more often followed) by lava flow output from the crater rim lasting a few hours. In this paper, we use remote sensing data from the ground and satellite, integrated with ground deformation data recorded by a high precision borehole strainmeter to characterize the 12 March 2021 eruptive episode, which was one of the most powerful (and best recorded) among that occurred since 13 December 2020. We describe the formation and growth of the lava fountains, and the way they feed the eruptive column and the ash plume, using data gathered from the INGV visible and thermal camera monitoring network, compared with satellite images. We show the growth of the lava flow field associated with the explosive phase obtained from a fixed thermal monitoring camera. We estimate the erupted volume of pyroclasts from the heights of the lava fountains measured by the cameras, and the erupted lava flow volume from the satellite-derived radiant heat flux. We compare all erupted volumes (pyroclasts plus lava flows) with the total erupted volume inferred from the volcano deflation recorded by the borehole strainmeter, obtaining a total erupted volume of ~3 × 106 m3 of magma constrained by the strainmeter. This volume comprises ~1.6 × 106 m3 of pyroclasts erupted during the lava fountain and 2.4 × 106 m3 of lava flow, with ~30% of the erupted pyroclasts being remobilized as rootless lava to feed the lava flows. The episode lasted 130 min and resulted in an eruption rate of ~385 m3 s−1 and caused the formation of an ash plume rising from the margins of the lava fountain that rose up to 12.6 km a.s.l. in ~1 h. The maximum elevation of the ash plume was well constrained by an empirical formula that can be used for prompt hazard assessment.

Strombolian activity varies in magnitude and intensity and may evolve into a threat for the local populations living on volcanoes with persistent or semi-persistent activity. A key example comes from the activity of Stromboli volcano (Italy). The “ordinary” Strombolian activity, consisting in intermittent ejection of bombs and lapilli around the eruptive vents, is sometimes interrupted by high-energy explosive events (locally called major or paroxysmal explosions), which can affect very large areas. Recently, the 3 July 2019 explosive paroxysm at Stromboli volcano caused serious concerns in the local population and media, having killed one tourist while hiking on the volcano. Major explosions, albeit not endangering inhabited areas, often produce a fallout of bombs and lapilli in zones frequented by tourists. Despite this, the classification of Strombolian explosions on the basis of their intensity derives from measurements that are not always replicable (i.e., field surveys). Hence the need for a fast, objective and quantitative classification of explosive activity. Here, we use images of the monitoring camera network, seismicity and ground deformation data, to characterize and distinguish paroxysms, impacting the whole island, from major explosions, that affect the summit of the volcano above 500 m elevation, and from the persistent, mild explosive activity that normally has no impact on the local population. This analysis comprises 12 explosive events occurring at Stromboli after 25 June 2019 and is updated to 6 December 2020.

Volcanic plume height is a key parameter in retrieving plume ascent and dispersal dynamics, as well as eruption intensity; all of which are crucial for assessing hazards to aircraft operations. One way to retrieve cloud height is the shadow technique. This uses shadows cast on the ground and the sun geometry to calculate cloud height. This technique has, however, not been frequently used, especially not with high-spatial resolution (30 m pixel) satellite data. On 26 October 2013, Mt Etna (Sicily, Italy) produced a lava fountain feeding an ash plume that drifted SW and through the approach routes to Catania international airport. We compared the proximal plume height time-series obtained from fixed monitoring cameras with data retrieved from a Landsat-8 Operational Land Imager image, with results being in good agreement. The application of the shadow technique to a single high-spatial resolution image allowed us to fully document the ascent and dispersion history of the plume–cloud system. We managed to do this over a distance of 60 km and a time period of 50 min, with a precision of a few seconds and vertical error on plume altitude of ±200 m. We converted height with distance to height with time using the plume dispersion velocity, defining a bent-over plume that settled to a neutral buoyancy level with distance. Potentially, the shadow technique defined here allows downwind plume height profiles and mass discharge rate time series to be built over distances of up to 260 km and periods of 24 h, depending on vent location in the image, wind speed, and direction.

Between 28 March and 1 April 2020, Stromboli volcano erupted, with overflows from the NE crater rim spreading along the barren Sciara del Fuoco slope and reaching the sea along the NW coast of the island. Poor weather conditions did not allow a detailed observation of the crater zone through the cameras monitoring network, but a clear view of the lower slope and the flows expanding in the area allowed us to characterize the flow features. This evidence was integrated with satellite, GBInSAR, and seismic data, thus enabling a reconstruction of the whole volcanic event, which involved several small collapses of the summit cone and the generation of pyroclastic density currents (PDCs) spreading along the slope and on the sea surface. Satellite monitoring allowed for the mapping of the lava flow field and the quantification of the erupted volume, and GBInSAR continuous measurements detected the crater widening and the deflation of the summit cone caused by the last overflow. The characterization of the seismicity made it possible to identify the signals that are associated with the propagation of PDCs along the volcano flank and, for the first time, to recognize the signal that is produced by the impact of the PDCs on the coast.

Lava fountains have a major impact on the local population since they cause ash plumes that spread several kilometers above and hundreds of kilometers away from the crater. Ash fallout is responsible for disrupting airports and traffic on the motorways well beyond the area of the volcano itself, as well as affecting the stability of buildings and causing public health issues. It is thus a primary scientific target to forecast the impact of this activity on local communities on the basis of parameters recorded by the monitoring network. Between 2011 and 2015, 49 paroxysmal explosive episodes occurred at two of Mt Etna's five summit craters: the New South-East Crater (NSEC) and the Voragine (VOR). In this paper, we examine the features of the 40 episodes occurring at the NSEC during 2011–2013, and of the 4 events at VOR in December 2015. We study these paroxysms using geophysical monitoring data, characterize the episodes, and analyse all available data statistically. Our main results are two empirical relationships allowing us to forecast the maximum elevation of the ash plume from the average height of the lava fountain, useful for hazard assessment and risk mitigation. For Etna, and using the examples described in this paper, we can infer that wind speed 10 m s−1 is normally associated with weak plumes, bent-over along the wind direction and reaching lower elevations.

During volcanic eruptions, measurements of the rate at which magma is erupted underpin hazard assessments. For eruptions dominated by the effusion of lava, estimates are often made using satellite data; here, in a case study at Mount Etna (Sicily), we make the first measurements based on terrestrial laser scanning (TLS), and we also include explosive products. During the study period (17–21 July 2012), regular Strombolian explosions were occurring within the Bocca Nuova crater, producing a ~50 m-high scoria cone and a small lava flow field. TLS surveys over multi-day intervals determined a mean cone growth rate (effusive and explosive products) of ~0.24 m3·s−1. Differences between 0.3-m resolution DEMs acquired at 10-minute intervals captured the evolution of a breakout lava flow lobe advancing at 0.01–0.03 m3·s−1. Partial occlusion within the crater prevented similar measurement of the main flow, but integrating TLS data with time-lapse imagery enabled lava viscosity (7.4 × 105 Pa·s) to be derived from surface velocities and, hence, a flux of 0.11 m3·s−1 to be calculated. Total dense rock equivalent magma discharge estimates are ~0.1–0.2 m3·s−1 over the measurement period and suggest that simultaneous estimates from satellite data are somewhat overestimated. Our results support the use of integrated TLS and time-lapse photography for ground-truthing space-based measurements and highlight the value of interactive image analysis when automated approaches, such as particle image velocimetry (PIV), fail.

The Etna flank eruption that started on 24 December 2018 lasted a few days and involved the opening of an eruptive fissure, accompanied by a seismic swarm and shallow earthquakes, significant SO2 flux release, and by large and widespread ground deformation, especially on the eastern flank of the volcano. Lava fountains and ash plumes from the uppermost eruptive fissure accompanied the opening stage, causing disruption to Catania International Airport, and were followed by a quiet lava effusion within the barren Valle del Bove depression until 27 December. This was the first flank eruption to occur at Etna in the last decade, during which eruptive activity was confined to the summit craters and resulted in lava fountains and lava flow output from the crater rims. In this paper, we used ground and satellite remote sensing techniques to describe the sequence of events, quantify the erupted volumes of lava, gas, and tephra, and assess volcanic hazards.

Detecting, locating and characterizing volcanic eruptions at an early stage provides the best means to plan and mitigate against potential hazards. Here, we present an automatic system which is able to recognize and classify the main types of eruptive activity occurring at Mount Etna by exploiting infrared images acquired using thermal cameras installed around the volcano. The system employs a machine learning approach based on a Decision Tree tool and a Bag of Words-based classifier. The Decision Tree provides information on the visibility level of the monitored area, while the Bag of Words-based classifier detects the onset of eruptive activity and recognizes the eruption type as either explosion and/or lava flow or plume degassing/ash. Applied in real-time to each image of each of the thermal cameras placed around Etna, the proposed system provides two outputs, namely, visibility level and recognized eruptive activity status. By merging these outcomes, the monitored phenomena can be fully described from different perspectives to acquire more in-depth information in real time and in an automatic way.

After a period of mild eruptive activity, Stromboli showed between 2017 and 2018 a reawakening phase, with an increase in the eruptive activity starting in May 2017. The alert level of the volcano was raised from “green” (base) to “yellow” (attention) on 7 December 2017, and a small lava overflowed the crater rim on 15 December 2017. Between July 2017 and August 2018 the monitoring networks recorded nine major explosions, which are a serious hazard for Stromboli because they affect the summit area, crowded by tourists. We studied the 2017−2018 eruptive phase through the analysis of multidisciplinary data comprising thermal video-camera images, seismic, geodetic and geochemical data. We focused on the major explosion mechanism analyzing the well-recorded 1 December 2017 major explosion as a case study. We found that the 2017−2018 eruptive phase is consistent with a greater gas-rich magma supply in the shallow system. Furthermore, through the analysis of the case study major explosion, we identified precursory phases in the strainmeter and seismic data occurring 77 and 38 s before the explosive jet reached the eruptive vent, respectively. On the basis of these short-term precursors, we propose an automatic timely alarm system for major explosions at Stromboli volcano.

In situ and remote-sensing measurements have been used to characterize the run-up phase and the phenomena that occurred during the August⁻November 2014 flank eruption at Stromboli. Data comprise videos recorded by the visible and infrared camera network, ground displacement recorded by the permanent-sited Ku-band, Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR) device, seismic signals (band 0.02⁻10 Hz), and high-resolution Digital Elevation Models (DEMs) reconstructed based on Light Detection and Ranging (LiDAR) data and tri-stereo PLEIADES-1 imagery. This work highlights the importance of considering data from in situ sensors and remote-sensing platforms in monitoring active volcanoes. Comparison of data from live-cams, tremor amplitude, localization of Very-Long-Period (VLP) source and amplitude of explosion quakes, and ground displacements recorded by GBInSAR in the crater terrace provide information about the eruptive activity, nowcasting the shift in eruptive style of explosive to effusive. At the same time, the landslide activity during the run-up and onset phases could be forecasted and tracked using the integration of data from the GBInSAR and the seismic landslide index. Finally, the use of airborne and space-borne DEMs permitted the detection of topographic changes induced by the eruptive activity, allowing for the estimation of a total volume of 3.07 ± 0.37 × 106 m3 of the 2014 lava flow field emplaced on the steep Sciara del Fuoco slope.

Fogo volcano erupted in 2014–2015 producing an extensive lava flow field in the summit caldera that destroyed two villages, Portela and Bangaeira. The eruption started with powerful explosive activity, lava fountains, and a substantial ash column accompanying the opening of an eruptive fissure. Lava flows spreading from the base of the eruptive fissure produced three arterial lava flows. By a week after the start of the eruption, a master lava tube had already developed within the eruptive fissure and along the arterial flow. In this paper, we analyze the emplacement processes based on observations carried out directly on the lava flow field, remote sensing measurements carried out with a thermal camera, SO2 fluxes, and satellite images, to unravel the key factors leading to the development of lava tubes. These were responsible for the rapid expansion of lava for the ~7.9 km length of the flow field, as well as the destruction of the Portela and Bangaeira villages. The key factors leading to the development of tubes were the low topography and the steady magma supply rate along the arterial lava flow. Comparing time-averaged discharge rates (TADR) obtained from satellite and Supply Rate (SR) derived from SO2 flux data, we estimate the amount and timing of the lava flow field endogenous growth, with the aim of developing a tool that could be used for hazard assessment and risk mitigation at this and other volcanoes.