Francesco Biagioli

Volcanic activity encompasses a wide range of seismogenic phenomena occurring from the deep magmatic conduit to the surface of volcanic flanks. Volcanic tremor, long period (LP), and very long period (VLP) seismic signals are commonly associated with magma and fluid movement within the conduit, whereas sliding mass and density currents along the flanks typically produce minute-long, cigar-shaped seismic traces.Characterising these phenomena through seismic analysis requires high measurement accuracy over a broad frequency range, together with high spatial and temporal resolution. Meeting these requirements in complex volcanic environments can be particularly challenging because the deployment and the maintenance of dense seismic networks involves considerable logistical effort. Distributed Acoustic Sensing (DAS) offers the opportunity to bridge the gap between sparse seismic networks and denser arrays, enabling continuous strain measurements along fibre-optic cables at comparatively low operational costs.Here, we investigate several different volcanic processes at Stromboli volcano (Italy) through DAS observations acquired along a 6 km fibre-optic cable integrated within a permanent multiparameter monitoring network comprising broadband seismometers, thermal and visible cameras, and infrasonic pressure sensors. The fibre was deployed on the volcanic flanks between 2020 and 2023 and interrogated during several month-long campaigns using a Febus A1-R. The dataset includes signals generated by ordinary Strombolian explosions, major explosions, lava flows, partial crater collapses and pyroclastic density currents (PDCs), which were analysed using different analytical approaches.Array-processing techniques in the 1–5 Hz frequency range were used to track the source of volcanic tremor, explosions, and PDCs with DAS strain-rate signals. Tremor and explosion signals are consistently located near the crater area, whereas PDCs propagate along the volcanic flanks. Moreover, by combining visible imagery with seismic energy recorded by DAS and inertial seismometers, we estimate the flow velocities and volumes of the PDCs and derive empirical, volume-dependent friction angles that provide insight into flow dynamics.Additionally, we exploit the distributed nature of DAS measurements to reconstruct the axisymmetric principal strain axes of VLP strain signals (between 0.04–0.2 Hz) associated with each explosion. The VLP strain signals recorded along the fibre nicely fit a deformation point-source (Mogi) located beneath the active craters, with an estimated volumetric change of ~30 m³.Our results demonstrate the capability of DAS measurements to characterise the dynamics of volcanic processes and to resolve the VLP strain distribution with enhanced spatial resolution. Overall, these findings highlight the significant potential of DAS as an innovative tool for analysing and monitoring a wide range of volcanic phenomena across different spatial and temporal scales.

Indonesia faces a unique combination of exposure to tsunamis, with dense coastal populations, intense seismic and volcanic activity, and multiple tsunami-generation mechanisms that can threaten shorelines with very little time for reaction.BMKG which is in charge of monitoring tsunamis faces 2 limitations: First, the operational system still relies mainly on land-based seismology, coastal sea-level observations, and precomputed modelling, while the availability and operability of deep-ocean buoy observations have remained an ongoing issue. Second, the existing system was designed for tectonic earthquake-generated tsunamis and is not sufficient on its own for non-tectonic sources such as volcanic or landslide-triggered events.To address these limitations, BPPT (subsequently integrated into BRIN in 2021), initiated the planning, design, and deployment of two prototype Ocean Bottom Unit (OBU) sensors between 2020 and 2022. The deployed units integrate high-sensitivity accelerometers and static pressure sensors to enable real-time monitoring of seismic activity and tsunami wave propagation in the northern waters of Labuan Bajo, Flores.The first OBU was installed approximately 25 km offshore at a depth of 2,110 m, whereas the second unit, positioned at the terminal section of the submarine cable, was deployed approximately 55 km offshore at a depth of 4,122 m. Both installations were strategically designed to monitor seismic activity associated with the Flores Thrust, located roughly 100 km north of Flores Island. Historical earthquakes along this tectonic structure, together with the submarine landslides they triggered, generated destructive tsunamis in 1982 and 1992, resulting in significant casualties and coastal run-up heights exceeding 20 m.The deployed submarine cable system has a total length of 55 km and incorporates 12 optical fibres, providing the necessary infrastructure for integrated sensing and real-time data transmission. At the end of April 2026, we connected a Febus Optics A1 DAS interrogator to one of the fibres for a preliminary study of local and regional seismicity. Our objectives with this initial deployment are to catalogue and characterise local seismicity, locate sources, and investigate improvements in the location of local earthquakes by using a combination of land-based seismic stations and the undersea optical cable.

The deployment of dense seismic arrays on volcanoes has increased significantly over the past decades, enabling more precise monitoring of volcanic activity. While short-period sensors are commonly used, Distributed Acoustic Sensing (DAS) represents a promising complementary technology, providing high spatial resolution and remote location of the interrogator. Accurate monitoring requires a robust understanding of seismic wave propagation, particularly within the shallow subsurface beneath the sensors. On volcanic edifices, the distribution of eruptive deposits along the flanks can be highly heterogeneous, leading to strong lateral variations in physical properties that can significantly affect seismic records.We use ambient noise cross-correlation to investigate the subsurface velocity structure beneath a 4 km-long DAS cable installed on Stromboli volcano, Italy. The analysis relies on two months of continuous strain-rate data recorded on this persistently active volcano, enabling a passive approach. Empirical Green’s Functions (EGFs) are retrieved using Phase Cross-Correlation and time-scale Phase-Weighted Stacking methods, and are validated through comparison with EGFs derived from collocated short-period seismic sensors. Local phase velocities are then estimated along the fiber and inverted to obtain a 2D S-wave velocity model. The results reveal two distinct regions along the profile, which correlate with variations in topography and volcanic deposits.

Surveillance des risques volcaniques par détection acoustique distribuée (DAS) sur le volcan Stromboli: Comprendre les signatures géophysiques de l'activité volcanique est crucial pour la prévision des éruptions. Cependant, les environnements volcaniques dangereux et difficiles compliquent souvent la surveillance continue des volcans. La technologie de détection acoustique distribuée (DAS, distributed acoustic sensing) offre une solution plus sûre et économique pour des relevés de longue durée dans les applications sismo-volcaniques. Le DAS sonde les câbles de fibre optique avec un échantillonnage spatial (échelle métrique) et temporel (jusqu'au kHz) très détaillé du champ sismique, en mesurant la déformation dynamique des fibres grâce à l'interférométrie des rayons rétrodiffusés. Dans le cadre du projet ANR MONIDAS, nous avons déployé 4 km de fibre optique sur le flanc nord-est du volcan Stromboli (Italie). Un interrogateur DAS Febus A1-R a enregistré l'activité volcanique lors de plusieurs expériences entre 2020 et 2023, capturant environ cinq mois de données. Pour valider les mesures DAS, nous avons installé des sismomètres le long de la fibre. Nous avons également collecté des données du réseau de surveillance permanent de l'Université de Florence (Italie), qui comprend des stations sismiques, des inclinomètres, des capteurs infrasons, des gauges de tsunamis, ainsi que des caméras visibles et thermiques. Nos objectifs principaux sont (1) d'évaluer la précision du DAS pour la détection des signaux sismiques volcaniques et (2) d'obtenir des informations sur la dynamique et la localisation de ces événements. Nous analysons les formes d'onde DAS en strain rate (taux de déformation) provenant de plusieurs processus volcaniques, en nous concentrant principalement sur l'activité ordinaire, y compris les explosions modérées et fréquentes (~10 événements/heure) ainsi que le trémor volcanique. Les signaux de strain rate des explosions stromboliennes ont généralement des fréquences comprises entre 2 et 10 Hz. De plus, les mesures DAS comprennent des signaux sismiques à très longue période entre 0,03 et 0,3 Hz. Nous examinons également les signaux générès par des explosions plus violentes (majeures) et des coulées pyroclastiques. Pour évaluer la précision du DAS, nous comparons les données de taux de déformation avec celles des sismomètres co-localisés en utilisant deux méthodes : la conversion de la vitesse sismique des sismomètres en strain rate et la conversion du strain rate DAS en vitesse. En utilisant la première méthode, nous observons un accord de phase presque parfait entre les deux ensembles de données. La seconde méthode donne des résultats similaires. Cependant, les amplitudes DAS sont de 1.5 à 5 fois plus faibles que celles enregistrées par les sismomètres, probablement en raison d'un transfert de déformation inefficace entre le sol, le câble et la fibre. Enfin, les techniques de traitement de réseaux nous aident à localiser les sources stationnaires (tremor et explosions) et à suivre les sources mobiles (coulées pyroclastiques). Les back-azimuths obtenus avec le DAS révèlent que les principales sources sismiques sont situées près des cratères actifs lors des explosions et du tremor, ce qui est cohérent avec les résultats obtenus avec les réseaux sismiques co-localisés. Les données DAS nous permettent également de suivre deux coulées pyroclastiques se déplaçant des cratères vers la mer avec des vitesses allant de ~40 à 70 m/s. Ces résultats correspondent à ceux obtenus via les données séismo-acoustiques et les images enregistrées par les caméras de surveillance. Bien que des recherches supplémentaires soient nécessaires, ces résultats démontrent le potentiel de cette nouvelle technologie dans la surveillance des zones volcaniques.

Very long period (VLP; 0.01-0.2 Hz) seismicity is observed at many volcanoes worldwide, and provides key insights into magma and fluid dynamics within volcanic structures. VLPs are typically recorded by sparse networks of seismometers, which limits the ability to resolve the resulting displacement (or deformation) at fine spatial scales. Distributed acoustic sensing (DAS) may help overcome this limitation by densely sampling the projection of the strain tensor along fibre-optic cables with high spatial and temporal resolution, enabling a more complete view of VLP-induced deformation. Here, we analyse VLP strain signals recorded by DAS at Stromboli volcano (Italy) in November 2022 along a 6-km dedicated fibre-optic cable. We designed the cable geometry to provide broad coverage of the craters and to sample the strain at multiple locations and along different directions. We focus on a dataset of approximately 200 VLP events recorded between November 13 and 14, 2022. The VLP strain signals correlate with explosive activity and show consistent features across multiple events, indicating a persistent, non-destructive source. Leveraging the distributed nature of DAS measurements, we recover the principal strain axes of VLPs and estimate both the location and the volumetric change of the source using a quasi-static deformation model. We retrieve the principal horizontal strains for each VLP by inverting strain amplitudes measured along three different fibre directions and at multiple locations along the cable, allowing us to resolve their spatial distribution. The resulting principal VLP strains exhibit radial and tangential orientations with respect to the craters, consistent with observed seismic particle motions and an axisymmetric source. We then model the VLP strain along the fibre using a point-like deformation source (Mogi). The optimal agreement between modeled and observed VLP strain averaged over the 200 events is for a point source located ~500 m beneath the active craters, with an estimated volumetric change of ~30 m³. Under the assumption of a spherical source with a radius of 87 m, the inferred volumetric change corresponds to a pressure change of ~19 kPa. These results are consistent with previous studies and highlight the capability of DAS to investigate volcano deformation at long periods.

The deployment of dense seismic arrays on volcanoes has increased significantly over the past decades, enabling more precise monitoring of volcanic activity. While short-period sensors are commonly used, Distributed Acoustic Sensing (DAS) represents a promising complementary technology, providing high spatial resolution and remote location of the interrogator. Accurate monitoring requires a robust understanding of seismic wave propagation, particularly within the shallow subsurface beneath the sensors. On volcanic edifices, the distribution of eruptive deposits along the flanks can be highly heterogeneous, leading to strong lateral variations in physical properties that can significantly aFect seismic records.In this study, we use ambient noise cross-correlation to characterize the subsurface velocity structure beneath a 3 km long DAS cable deployed on Stromboli volcano, Italy. We analyse two months of continuous strain rate data acquired on this persistently active volcano, which allows the application of a passive approach. Empirical Green’s Functions (EGFs) are retrieved using Phase Cross-Correlation and times-scale Phase Weighted Stack methods. They are validated through comparison with EGFs obtained from collocated short-period seismic sensors. Local phase and group velocities are then computed along the optical fiber and inverted to determine the 2D S-wave velocity profile. We clearly identify 2 distinct regions along the profile which are correlated with changes of local topography, eruptive activity and deposits.

Detecting, locating, and characterising the dynamics of destabilised volcanic material is critical for assessing the extreme hazards posed by volcanic mass flows, such as pyroclastic density currents. Geophysical measurements of these events may offer information otherwise hardly observable at close range. Here we investigate pyroclastic density current dynamics using a multiparameter approach that combines seismic, distributed acoustic sensing, and infrasound data with thermal and visible imagery, supported by numerical simulations. We focus on two events at Stromboli volcano, Italy, that occurred in October and December 2022. By comparing visible imagery with seismic energy and applying array processing techniques, we identify different flow volumes ( ~23.5 ± 9.5 × 10 ³  m ³ and ~80 ± 9 × 10 ³  m ³ , respectively) and velocities (33-42 m/s and 54-59 m/s, respectively). Simulations reveal that reproducing these velocities requires volume-dependent empirical friction angles ( ~27° and 21°), consistent with dry granular flow behaviour and friction weakening. These findings offer new insights into the use of distributed acoustic sensing for volcanic monitoring and underscore the value of integrating multiparameter data with modeling to better understand complex volcanic processes.