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The San Bartolo eruption is the last flank eruption occurred at Stromboli volcano about 2 ka ago on the NE flank of the island. Despite its importance in being the most recent example of flank activity outside the barren Sciara del Fuoco slope, where the recent activity concentrated, some important volcanological data, such as the duration and lava volume have not yet been provided. Here, we present a new simulation of the San Bartolo eruption carried out using a combination of field analyses and numerical modelling. In particular, we used the CL-HOTSAT satellite monitoring system to estimate the effusion rate and erupted volume of the 2002-03 eruption, which formed a similar lava flow field extending from about 600 m in elevation to the coast. These were used as input of the physics-based model GPUFLOW to reproduce the emplacement dynamics of the San Bartolo lava flow. The aim is to reconstruct the sequence of events and infer a possible duration and impact of the eruption. Our results can provide a useful scenario should a flank eruption occur in the future, a possibility that was close to happening in 1998, when the ground deformation stations revealed a lateral intrusion in the shallow supply system of the volcano.

Combining field measurements, satellite estimates and numerical modeling provide great advantages for the continuous monitoring of effusive eruptions. Here we demonstrate the potential of a new integrated monitoring system called HOTFLOW developed for Etna volcano, which is based on the CL-HOTSAT thermal monitoring system for the processing of satellite imagery and GPUFLOW model for the simulation of lava flows. The potential of HOTFLOW is demonstrated here using the ongoing eruption of Mount Etna started on November 27, 2022. We provide insights into lava flow field evolution by supplying detailed views of flow field construction (e.g., the opening of ephemeral vents) that are useful for more accurate and reliable forecasts of the eruptive activity. Moreover, we give a detailed chronology of the lava flow activity based on field observations and satellite images (i.e. SEVIRI, MODIS, Landsat 8/9, Sentinel-2, Planetscope, Skysat), assess the potential extent of impacted areas, map the evolution of lava flow field, and provide lava flow hazard projections.

The classic definition of risk as the product of hazard, exposure and vulnerability was initially intended as a qualitative rather than quantitative formula. Its informal nature becomes more apparent when evaluating strategies for risk mitigation, for which different informal equations have been presented in the literature.We offer here a mathematical perspective on the equations that define risk and a novel approach for a quantitative analysis of risk mitigation that help highlight decision variables among the many input variables that participate in risk analysis and modeling.We show how the classic Risk = Hazard * Exposure * Vulnerability formula represents a zero-order approximation of the more formal integral representation that we derive, and that risk mitigation can be quantified based on parallels with mathematical homotopies with an associated cost function, with an interesting outlook on the design of both long-term and short-term risk mitigation strategies.

Mt. Etna is one of the most active basaltic volcanoes worldwide, characterized by both explosive and effusive eruptive activity. Lava flows represent the main hazard linked to the volcanic activity, which can be emplaced at high rates during paroxysmal eruptions from the main vents located at summit, or through vents located on the flank of the volcano. In the last decades, the eruptive activity interested mainly the summit area, particularly the South East Crater (SEC), with vigorous lava fountains, as during the 2011-2013 and 2020-2022 series, alternated by effusive activity through fissures opened at the base of the scoria cone, as during the July-August 2014, February-April 2017, May-July 2019 and May-June 2022 eruptions. This posed the need to quantify the hazard from lava flow inundation in the summit area, which is essential during volcanic emergencies and for mitigation actions.In this study, we present the new lava flows hazard map of Etna’s summit, which has been developed through a probabilistic approach that combines the statistical analyses of the volcanological historical data with the numerical simulations of lava flows on a 2022 Digital Surface Model (DSM). The probabilistic approach includes: i) the estimation of the spatiotemporal probability of future vent opening; ii) the calculation of the occurrence probability of the eruptive classes, which are defined considering the distribution of the lava volume erupted and the durations of eruptions; iii) the simulation of the lava flow paths for all the defined eruptive classes from each potential vent using the GPUFLOW model; iv) the mapping of the probability of inundation by combining the numerical simulations with the probability of future vent opening and the occurrence probability.A grid of potential vents have been defined over an area corresponding to the Ellittico caldera, while the eruptive classes have been derived by considering both the short- and long-lasting eruptions that occurred at Etna’s summit since 1998. The highest probabilities of inundation of lava flows provided by the obtained map are linked to the vents located in the SEC’s area, according to the observation of the eruptive dynamics in the last decades.

International audience; Implicit integration of the viscous term can significantly improve performance in computational fluid dynamics for highly viscous fluids such as lava. We show improvements over our previous proposal for semi-implicit viscous integration in Smoothed Particle Hydrodynamics, extending it to support a wider range of boundary models. Due to the resulting loss of matrix symmetry, a key advancement is a more robust version of the biconjugate gradient stabilized method to solve the linear systems, that is also better suited for parallelization in both shared-memory and distributed-memory systems. The advantages of the new solver are demonstrated in applications with both Newtonian and non-Newtonian fluids, covering both the numerical aspect (improved convergence thanks to the possibility to use more accurate boundary model) and the computational aspect (with excellent strong scaling and satisfactory weak scaling).

We present a new model called GPUFLOW for the modeling and simulation of geophysical flows. GPUFLOW, which is based on the cellular automaton paradigm, features a physical model for the thermal and rheological evolution of lava flows (including temperature-dependent emissivity and cooling by radiation and air convection), support for debris flows without thermal dependency, a parallel implementation on graphic processing units (GPUs), and a simpler and computationally more efficient solution to the grid bias problem. Here, we describe the physical–mathematical model implemented in GPUFLOW and estimate the influence of input data on the flow emplacement through different synthetic test cases. We also perform a validation using two real applications: a debris flow that occurred in July 2006 in the Dolomites (Italy) and the December 2018 lava flow from the Etna volcano. GPUFLOW’s reliability prediction is accomplished by fitting the simulation with the actual flow fields, obtaining average values between ~55% and 75%.

The effects of volcanic hazards can be quantified by applying new methods to provide support for rational decision-making. Mt Etna is one the most active volcanoes in the world, producing both effusive and explosive eruptions together with a very intense seismic activity, which significantly affect the territory and human society. We present the preliminary results obtained in the framework of the PANACEA project (INGV’s project “Pianeta Dinamico”, funded by the Italian Ministero dell’Università e la Ricerca, MUR) regarding the multi-hazard assessment around Mt Etna. These include: (i) the production of an updated spatio-temporal probability map of vent opening at Etna, using a procedure exploiting different Kernel functions (e.g. the exponential, Cauchy, and Gaussian functions), and testing volcanic deformation patterns to explore possible dynamic, structural conditioning on the vent opening process; (ii) the identification of a set of cascading effects scenarios that account for volcanic phenomena (i.e., volcanic unrest, seismicity, volcanic explosions, volcanic effusive events, lava flows, tephra/ballistic fall, and PDC), as well as other external hazards potentially linked in such chains (e.g., flooding, forest fires, etc.); and (iii) the identification of scenarios involving systemic impacts (e.g., impacts on the functionality or connectivity of networks).

By 2021, Vulcano, Aeolian Islands (Italy), experienced a dramatic increase in different monitoring parameters, including microseismicity, ground deformation, fumarole temperatures, and volatile emissions of steam, carbon, and sulfur dioxide. The volcanic unrest was noticeable in September 2021, causing the Civil Protection to raise the alert level from green to yellow on October 1st. Here we present a number of ground- and satellite-based thermal methodologies used to detect and characterize the change of state of the La Fossa hydrothermal system between January 2021 and January 2022. We analyzed: (i) the temperature and (ii) CO2 flux data acquired at 15 cm‐depth on a N-S profile N-S and grid in the geothermally heated area during three field surveys in June, September 2021 and January 2022; (iii) a time series acquired with a radiometer including temperatures and number of vents inside the fumarole field from 1994 to 2022; (v) thermal images acquired by a hand-held thermal camera during four field surveys in March, June and September 2021, plus January 2022; (v) nighttime multi-spectral satellite images acquired by ASTER, ECOSTRESS and VIIRS sensors from January 2021 to January 2022. Satellite images show a clear increase in the radiant heat flux/land surface temperature as well as in the number of thermally anomalous pixels, this thermal anomaly has been observed from mid-September. However, by combining ground and satellite techniques the starting point of this change can be tracked thermally from at least June 2021. Our experience suggests that the methods, essentially based on the thermal monitoring, could be used to herald upcoming crises. This method has been applied on a close conduit volcano and highlighted changes of trend in the solfataric release. Further tests, aiming to reduce (filter or define) the external effects on the land surface temperature, and to define the correlations with the long term monitoring data (either ground-based or by remote sensing) in this area, would assess a standardized methodology to monitoring the subtle, but diffuse fluid release. The assessed methodology could then be applied to other active hydrothermal systems, to herald thermal changes on the surface, related to the increasing energy released from a deep source.

On 19 September 2021, after about 50 years of quiescence, a new eruption started at Cumbre Vieja volcano (Canarias, Spain). The onset was preceded by a series of seismic swarms, the last one of which occurred on 11 September 2021. A system of eruptive fissures opened and multiple vents produced lava fountains, sustained ash columns, and lava flows that travelled over 5 km W to the sea, damaging hundreds of properties along their path. The eruption forced the evacuation of over 7,000 people and destroyed nearly 3,000 buildings, ending on 13 December, after 85 days.We here detail the different phases of the eruption and describe and discuss the lava flow field structures and emplacement dynamics by using ground- and air-based thermal camera data as well as using multispectral satellite images. Indeed, the high temporal resolution of SEVIRI images - i.e. an image every 15 minutes - allowed tracking the lava flow development and provided an estimation of the effusion rate. Sentinel 2, Landsat 8 and PlanetScope images enabled mapping the active areas of the lava field and, thus to clearly depict the formation of lava tube systems promoting lava flow lengthening to the sea. Moreover, the satellite-derived data were used as input to the GPUFLOW model to produce near real time, short-term lava flow hazard maps.

Modelling and simulation of geophysical flows are crucial to the forecasting of the propagation extent and the assessment of the related hazards. Here we introduce a new physics-based model called GPUFLOW, which was born from our twenty years of experience in Fluid Dynamics (CFD) modelling of geophysical flows. GPUFLOW features an improved physical model for the thermal and rheological evolution of lava flows, support for debris flows without thermal dependency and a parallel implementation on graphic processing units (GPUs). We estimate the influence that the GPUFLOW input parameters have on flow emplacement through different synthetic test cases and demonstrate its reliability through the 2014 pyroclastic flow and the 2018 eruption occurred at Etna volcano. This work was supported by the INGV project Pianeta Dinamico funded by MIUR (“Fondo finalizzato al rilancio degli investimenti delle amministrazioni centrali dello Stato e allo sviluppo del Paese,” legge 145/2018), Tema 8 – PANACEA 2021.

One of the main issues with naive Smoothed Particle Hydrodynamics (SPH) implementations is the lack of uniform accuracy in the computational domain. If not mastered correctly, this leads to non-phy...

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.

How (in)formal should the classic expression describing risk as the product of hazard, exposure, and vulnerability be considered? What would be the most complete way to describe the process of risk mitigation? These are the questions we try to answer here, using a formal, mathematically sound yet abstract description of hazard, exposure, vulnerability, and risk. We highlight the elements that can be affected for the purpose of mitigation and show how this can improve the quantitative assessment of the procedural aspects of risk mitigation, both long- and short-term, down to the timescale of emergency response.

Satellite remote sensing is playing an increasing role in volcano monitoring, not only at little-known and remote volcanoes where in-situ data are often unavailable, but also at well-monitored volcanoes to complement ground-based measurements. The synoptic view captured by multi-source satellite imagery over volcanoes can benefit hazard monitoring efforts, both following the different phases and intensities of an eruption, as well as helping in nowcasting and eventually forecasting the areas potentially threatened by hazardous phenomena. Here we demonstrate how satellite data from different sources can be combined to refine the satellite-derived radiant heat flux and time-averaged discharge rates (TADRs) estimation, and to improve real-time monitoring and nowcasting of eruptive events. This is achieved by cross-referencing TADRs obtained from low spatial/high temporal resolution satellite data (e.g. MODIS, SEVIRI, VIIRS, SLSTR) with maps of volcanic deposits including the time-varying evolution of lava flow emplacement derived from medium spatial resolution multispectral satellite data (e.g. EO-ALI, Landsat, Sentinel-2, ASTER), and with detailed three-dimensional maps of volcanic deposits retrieved from the topographic monitoring by using stereo or tri-stereo optical data (e.g. Pleiades, PlanetScope, SkySat, ASTER). Finally, satellite-derived parameters are used as input and validation for the numerical modelling of lava flow scenarios. This strategy is here applied to recent eruptions occurred on Etna, Stromboli and Nabro volcanoes.

Lava flows represent the greatest threat by far to exposed population and infrastructure on Mt. Etna, Italy. The increasing exposure of a larger population, which has almost tripled in the area around Mt. Etna during the past 150 years, has resulted from poor assessment of the volcanic hazard and inappropriate land use in vulnerable areas. Here we quantify the lava flow risk on the flanks of Mt. Etna volcano using a Geographic Information System (GIS)-based approach that integrates the hazard with the exposure of elements at stake. The hazard, which shows the long-term probability related to lava flow inundation, is obtained by combining three different kinds of information: the spatiotemporal probability of new flank eruptive vents opening in the future, the event probability associated with classes of expected eruptions, and the overlapping of lava flow paths simulated by the MAGFLOW model. Data including all exposed elements were gathered from institutional web portals and high-resolution satellite imagery and organized in four thematic layers: population, buildings, service networks, and land use. The total exposure is given by a weighted linear combination of the four thematic layers, where weights are calculated using the Analytic Hierarchy Process (AHP). The resulting risk map shows the likely damage caused by a lava flow eruption and allows rapid visualization of the areas subject to the greatest losses if a flank eruption were to occur on Mt. Etna. The highest risk is found in the southeastern flank due to the combination of high hazard and population density.

GPUSPH is an implementation of Weakly-Compressible Smoothed Particle Hydrodynamics with an explicit predictor–corrector integration scheme, that takes advantage of the parallel nature of the method to run on Graphic Processing Units (GPUs). Despite the massive speed-up granted by the use of GPUs, the application of GPUSPH to the simulation of highly viscous fluids is still problematic, due to the severe time-stepping restrictions imposed by the explicit integration scheme when the viscous term becomes dominant. This is an issue in the simulation of lava flows, where the thermal-dependent rheology can lead to kinematic viscosities in the order of 10 4 m 2 s − 1 or more at low temperatures. To overcome this limitation, we introduce a semi-implicit integration scheme, where only the viscous part of the momentum equation is solved implicitly. Here we show the significant advantages of our approach in terms of simulation run times as well as better quality of the results over the fully explicit scheme.

The application of remote sensing for monitoring, detecting and analysing the spatial and extents and temporal changes of waste dumping sites and landfills could become a cost-effective and powerful solution. Multi-spectral satellite images, especially in the thermal infrared, can be exploited to characterize the state of activity of a landfill. Indeed, waste disposal sites, during the period of activity, can show differences in surface temperature (LST, Land Surface Temperature), state of vegetation (estimated through NDVI, Normalized Difference Vegetation Index) or soil moisture (estimated through NDWI, Normalized Difference Water Index) compared to neighboring areas. Landfills with organic waste typically show higher temperatures than surrounding areas due to exothermic decomposition activities. In fact, the biogas, in the absence or in case of inefficiency of the conveying plants, rises through the layers of organic matter and earth (landfill body) until it reaches the surface at a temperature of over 40 ° C. Moreover, in some cases, leachate contamination of the aquifers can be identified by analyzing the soil moisture, through the estimate of the NDWI, and the state of suffering of the vegetation surrounding the site, through the estimate of the NDVI. This latter can also be an indicator of soil contamination due to the presence of toxic and potentially dangerous waste when buried or present nearby. To take into account these facts, we combine the LST, NDVI and NDWI indices of the dump site and surrounding areas in order to characterize waste disposal sites. Preliminary results show how this approach can bring out the area and level of activity of known landfill sites. This could prove particularly useful for the definition of intervention priorities in landfill remediation works.

Numerical simulation is a fundamental aspect of modern volcanology, providing tools for the forecasting of lava flows behavior, so as to assist in the design of mitigation actions for volcanic risk. In addition to the prediction of the emplacement topology, numerical simulation can be useful to study the possible outcomes of the interaction between a lava flow and a building. This kind of information can help to estimate the vulnerability of buildings so as to produce more accurate risk evaluations. Smoothed Particle Hydrodynamics (SPH) is a particle-based numerical method, particularly suited for the simulation of fluids with a high level of complexity, that can intrinsically deal with all of the physical properties of lava. GPUSPH is a simulation engine based on the SPH method that has been developed in order to take into account the challenging aspects of lava simulations and has been successfully applied to the simulation of lava-related benchmark tests. Here we use the SPH method, coupled within the framework of GPUSPH with a rigid body mechanics solver provided by the Project Chrono engine, for the realistic study of lava-buildings interaction. The resulting coupled model is able to simulate masonry with a brick-level accurate description, providing insights on any damages happening to the structure. We will show the simulation of a lava flow interacting with an elementary masonry piece, where a total collapse of the structure is induced by the action of the lava.

On 24 December 2018 a flank eruption started on Etna from an eruptive fissure opened on the eastern side of the New Southeast Crater (NCSE) at about 3,100 m asl, which in few minutes, propagated to the south-east, overcoming the edge of the western wall of the Valle del Bove (VdB), reaching an altitude of 2,400 m asl and a total length of about 2 km. The eruption, which lasted only three days, produced lava flows from different vents along the eruptive fissure that reached a distance of about 4.2 km and covered an area of about 1 km2. The satellite monitoring of the 2018 Etna eruption was performed using the HOTSAT system using mid and thermal infrared data acquired by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), which provided minimum and maximum estimates for the lava thermal flux, the effusion rate and the lava volume. The SEVIRI-derived effusion rate estimates were used as input of the MAGFLOW model to simulate the actual lava flow field, obtaining a very good fit. We also simulated different eruptive scenarios assuming the lava emission wouldn’t run out in only three days to forecast if, when and how the lava flow could reach the inhabited areas, causing possible significant damage.

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.

Mitigating hazards when lava flows threaten infrastructure is one of the most challenging fields of volcanology, and has an immediate and practical impact on society. Lava flow hazard is determined by the probability of inundation, and essentially controlled by the topography of the area of interest. The most common actions of intervention for lava flow hazard mitigation are therefore the construction of artificial barriers and ditches that can control the flow direction and advancement speed. Estimating the effect a barrier or ditch can have on lava flow paths is non-trivial, but numerical modelling can provide a powerful tool by simulating the eruptive scenario and thus assess the effectiveness of the mitigation action. We present a numerical method for the design of optimal artificial barriers, in terms of location and geometric features, aimed at minimizing the impact of lava flows based on the spatial distribution of exposed elements. First, an exposure analysis collects information about elements at risk from different datasets: population per municipality, distribution of buildings, infrastructure, routes, gas and electricity networks, and land use; numerical simulations are used to compute the probability for these elements to be inundated by lava flows from a number of possible eruptive scenarios (hazard assessment) and computing the associated economic loss and potential destruction of key facilities (risk assessment). We then generate several intervention scenarios, defined by the location, orientation and geometry (width, length, thickness and even shape) of multiple barriers, and compute the corresponding variation in economic loss. Optimality of the barrier placement is thus considered as a minimization problem for the economic loss, controlled by the barrier placement and constrained by the associated costs. We demonstrate the operation of this system by using a retrospective analysis of some recent effusive eruptions at Mount Etna, Sicily.

The Etna flank eruption 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, and by large and widespread ground deformation especially on the eastern flank of the volcano. Lava fountains and ash plume from the uppermost eruptive fissure have accompanied the opening stage causing disruption of Catania international airport, and have been followed by a quiet lava effusion within the barren Valle del Bove depression until 27 December. This is the first flank eruption occurring 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 use ground and satellite remote sensing techniques to describe the sequence of events, quantify the erupted volumes of lava, gas and tephra, and assess volcanic hazard.

We explore the use of graph theory to assess short-term hazard of lava flow inundation, with Mt Etna as a case study. In the preparation stage, we convert into a graph the long-term hazard map produced using about 30,000 possible eruptive scenarios calculated by simulating lava flow paths with the physics-based MAGFLOW model. Cells in the original DEM-based representation are merged into graph vertices if reached by the same scenarios, and for each pair of vertices, a directed edge is defined, with an associated lava conductance (probability of lava flowing from one vertex to the other) computed from the number of scenarios that reach both the start and end vertex. In the application stage, the graph representation can be used to extract short-term lava flow hazard maps in case of unrest. When a potential vent opening area is identified e.g. from monitoring data, the corresponding vertices in the graph are activated, and the information about lava inundation probability is iteratively propagated to neighboring vertices through the edges, weighted according to the associated lava conductance. This allows quick identification of potentially inundated areas with little computational time. A comparison with the deterministic approach of subsetting and recomputing the weights in the long-term hazard map is also presented to illustrate benefits and downsides of the graph-based approach.

The 2011 eruption of Nabro volcano, situated at the southeast end of the Danakil Alps in Eritrea, has been the first historical on record and one of the largest eruptions of the last decade. Due to the remote location of the Nabro volcano and the lack of data from ground monitoring networks at the time of the eruption, satellite remote sensing gives the first global view of the event, providing insights on its evolution over time. Here we used numerical modeling and high spatial resolution satellite data (i.e. EO-ALI, ASTER, PlanetScope) to track the path and velocity of lava flows and to reconstruct the pre- and post-eruptive topographies in order to quantify the total bulk volume emitted. High temporal resolution images (i.e. SEVIRI and MODIS) were exploited to estimate the time-averaged discharge rate (TADR) and assess the dense rock equivalent (DRE) lava volumes constrained by the topographic approach. Finally, satellite-derived parameters were used as input and validation tags for the numerical modelling of lava flow scenarios, offering further insights into the eruption and emplacement dynamics. We found that the total volume of deposits, calculated from differences of digital elevation models (DEMs), is about 580 × 106 m3, of which about 336 × 106 m3 is the volume of the main lava flow that advanced eastward beyond the caldera. Multi-spectral satellite observations indicate that the main lava flow had reached its maximum extent (∼16 km) within about 4 days of the eruption onset on midnight 12 June. Lava flow simulations driven by satellite-derived parameters allow building an understanding of the advance rate and maximum extent of the main lava flow showing that it is likely to have reached 10.5 km in one day with a maximum speed of ~0.44 km/h.

Detect, locate and characterize eruptions in real-time is fundamental to monitor volcanic activity. Here we present an automatic system able to discover and identify the main types of eruptive activities by exploiting infrared images acquired by the thermal cameras installed around Mount Etna volcano. The system, which employs the machine learning approach, is 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 classifiers detects the onset of the eruptive activity and recognize the eruption type among either explosion and/or lava flow or plume. Thus, applied to each image of all thermal cameras over Etna in real-time, the proposed system provides two outputs, namely the visibility level and the recognized activity status. By merging the outcomes coming from each thermal camera, the monitored phenomena can be fully described from different perspectives getting deeper information in real-time and in an automatic way.

The 3 July 2019 explosive paroxysm at Stromboli volcano (Italy) caused severe concern in the local population and media, and killed one tourist hiking the volcano. The great explosion formed a 4-km-high eruptive cloud, and its partial collapse ignited the dry vegetation and caused hot rock avalanches spreading along the northern slope to the sea and triggering a small tsunami wave. This paroxysm was followed by 56 days of lava flow effusion, and another explosive paroxysm occurred on 28 August 2019. Also this explosive event caused an eruptive column of about 4 km and hot avalanches spreading on the north flank of the volcano and on the sea surface. Here we use effusion rate time-series derived from MODIS and SLSTR data to follow the different thermal phases of this eruption and compute the dense rock equivalent volume emitted. At the same time we computed four digital elevation models from Pleiades triplets acquired on June, July, August and October 2019 in order to map the morphological changes occurred during the eruption. By differencing pre, syn and post eruptive topographies we computed the bulk lava volume at the different stages. Combining tri-stereo Pleiades results with MODIS and SLSTR ones, beside giving insights in the characterization of volcanic deposits, provides important constraints in the conversion between radiant heat flux and TADR, and demonstrates the powerful merging capability of multi-platform remote sensing data.