Fault creep along the lower eastern flank of Mt. Etna volcano has been documented since the end of the 19th century and significantly contributes to the surface faulting hazard in the area. On 29 October 2002, during a seismic swarm related to dyke intrusions, two earthquakes caused extensive damage and surface faulting in an area between the Santa Venerina and Santa Tecla villages. On the same day after the two earthquakes, an episodic aseismic creep occurred along the Scalo Pennisi Fault close to the Santa Tecla coastline. On 8 February 2022, during another aseismic creep event along the Scalo Pennisi Fault, we observed the reopening of the pre-existing 2002 ground ruptures mostly as pure dilational fractures. We mapped the 2002 and 2022 surface ruptures, and collected data on displacement, length, and pattern of ground breaks. Ground ruptures affected structures located along the activated fault segments, including roads, walls and buildings. The 2002 surface faulting propagation can be ascribed to a sliding of the Mt. Etna eastern flank toward the SE, as also suggested by the related shallow seismicity, and InSAR and geodetic data between 2002 and 2005. For the 2022 event, differential InSAR data, acquired in both descending and ascending views, allowed us to decompose Line of Sight (LOS) displacement into horizontal and vertical components. We detect a ~ 700 m long and ~ 500 m wide deformation zone with a downward and eastward motion (max displacement ~1,5 cm) consistent with a normal fault. We inverted the InSAR-detected surface deformation using a uniform-slip fault model and obtained a shallow detachment for the causative fault, located at ~300 m depth, within the volcanic pile. This is the first in-depth study along the Scalo Pennisi Fault to suggest a shallow faulting that accommodates Mt. Etna E flank gravitational sliding.

In this paper, we present an innovative Phase Unwrapping (PhU) procedure for Multi Temporal DInSAR techniques, based on the Extended Minimum Cost Flow technique schema. The developed algorithm benefits from the Compressive Sensing (CS) theory. In particular, the procedure consists of the cascade of three steps. At first, the set of spatially connected arcs between close pixels is identified by selecting the points to be unwrapped and linking them through the Delaunay algorithm; in the second step, the temporal PhU of all the arcs is carried out by using the CS approach and an L-norm estimator. In the last step, the algorithm uses the unwrapped arcs to perform spatial PhU of each interferogram using MCF technique. To assess the performance of the developed approach, we analyze the area related to Stromboli volcano (Italy) by processing the dataset acquired by Sentinel-1 constellation over descending orbit from 2016 to 2021.

The "Monitoring Earth's Evolution and Tectonics" (MEET) project is funded by the Italian "Piano Nazionale di Ripresa e Resilienza (PNRR) - Next Generation EU", approved by the Ministry of University and Research. MEET is in the framework of the Research Infrastructure European Plate Observing System "EPOS" and aims to strengthen the observational systems dedicated to discovering the Earth's dynamics, focusing on the Italian territory, particularly those regions more affected by natural hazards.

In this work we describe the implementation of a processing chain for a fully automatic modeling of the seismic source parameters and its slip distribution through the inversion of the InSAR displacements generated from the EPOSAR service. This processing chain consists of a suite of procedures and algorithms handling a sequence of steps: selection of the highest quality InSAR datasets, definition of the area of interest, image sampling, non-linear and linear inversions to get, respectively, the source geometry and its slip distribution. A set of side procedures and interfaces also allows an interactive refinement and the publication of results, consisting of scientific data and graphical outputs. The whole procedure has been developed, tested and validated by considering 100 events with magnitudes between 5.5 and 8.2, worldwide distributed and covering an exhaustive range of mechanisms and tectonic contexts. Main aim of this work is describing the implementation of the automatic modeling procedures, used to produce solutions in real time, already during the emergency phase. These sources, validated by experts before their publication, can be a reference for operational purposes and initial scientific analyses. The creation of this repository sets also the framework to store, out of the emergency time, more sophisticated solutions, manually revised and/or with peer-review quality.

On 2 December 2020 10:54 UTC a shallow earthquake of MW (NOA) = 4.6 occurred near the village of Kallithea (to the east of Thiva), central Greece, which, despite its modest size, was locally damaging. Using InSAR and GNSS data, we mapped a permanent change on the ground surface, i.e., a subsidence of 7 cm. Our geodetic inversion modelling indicates that the rupture occurred on a WNW-ESE striking, SSW-dipping normal fault, with a dip-angle of ~ 54°. The maximum slip value was 0.35 m, which was reached at a depth of about 1100 m. The analysis of broadband seismological data also provided kinematic source parameters such as moment magnitude MW = 4.6 (± 0.1), rupture area 6.3 km2 and mean slip 0.16 m, which agree with the values obtained from the geodetic model. The effects of the earthquake were disproportionate to its moderate magnitude, probably due to its unusually shallow depth (slip centroid at 1.1 km) and the high efficiency of the earthquake (radiation efficiency = 0.62). The geodetic data inversion also indicates that within the uncertainty limits of the technique, three scenarios are possible (a) the earthquake responsible for the mapped surface deformation may have occurred on a ~ 2-km long, blind normal fault different from the well-known active Kallithea normal fault or (b) could have occurred along a secondary fault that branches off the Kallithea fault or (c) it may have occurred along the Kallithea fault itself, but with its geometrical configuration could not be modelled with available data. We have also concluded that with a high dip-angle Kallithea Fault forward model it is not possible to fit the geodetic data. The rupture initiated at a very shallow depth (1.1 km) and it could not propagate deeper possibly because of a structural barrier down-dip. The 2020 event near Kallithea highlighted the structural complexity in this region of the Asopos Rift valley as the reactivation of the WNW-ESE structures indicates their significant role in strain accommodation and that they still represent a seismic hazard for this region.

Previous work at Fernandina, the most active volcano of the Western Galapagos (Ecuador), revealed evidence for both a shallow and a deep magma reservoir, but the relative contribution of the two reservoirs to eruptions remains unclear. Here we investigate the September 2017 circumferential eruption and the June 2018 radial eruption using interferometric synthetic aperture radar data and geodetic modeling. Our results show that during the 2017 eruption magma was simultaneously withdrawn from the deep reservoir, injected upwards through the shallow reservoir, and then fed the circumferential feeder dike to the SW of the caldera. Two episodes of inflow of new magma occurred in both the deep and shallow magma reservoirs in the inter-eruptive period from December 2017 to May 2018. During the 2018 eruption, both reservoirs fed two radial feeder dikes below the north flank, probably interacting with an underlying peripheral melt pocket, and an inclined sheet below the NW sector of the caldera. Our results highlight the primary role of the deeper reservoir which accumulates most of the magma before eruptions. Both eruptions were characterized by rapid magma transfer from the deeper to the shallower reservoir. This is similar to what is observed at the nearby Wolf volcano, but unlike nearby Sierra Negra, where a shallower reservoir accumulates higher volumes of magma before eruptions. These differences in the pre-eruptive role of the deeper and shallower reservoirs might be related to the different evolutionary stages of Fernandina and Wolf with regard to the more mature Sierra Negra.Plain Language Summary Fernandina is the most active volcano of the Western Galapagos (Ecuador). Two magma reservoirs at different depths below the volcano trigger eruptions both near the caldera rim (circumferential eruptions) and lower on the volcano flanks (radial eruptions). The role played by the two reservoirs in the eruptions is poorly understood. Here we studied the 2017 and the 2018 eruptions that occurred at Fernandina by using deformation data derived from radar satellites to investigate the inputs and outputs of new magma into the two reservoirs when eruptions occurred. The 2017 eruption had similar characteristics to the 2005 eruption, while the 2018 eruption had more complex mechanisms of shallow magma transfer, with magma transported in multiple directions below the north flank of Fernandina. We found that rapid magma transfer from the deep to the shallow reservoir provided most of the magma for both eruptions, similar to the nearby Wolf volcano, and unlike nearby Sierra Negra, a feature that may be due to the evolutionary stage of the volcanoes.

Satellite Interferometric Synthetic Aperture Radar (InSAR) is widely used for topographic, geological and natural resource investigations. However, most of the existing InSAR studies of ground deformation are based on relatively short periods and single sensors. This paper introduces a new multi-sensor InSAR time series data fusion method for time-overlapping and time-interval datasets, to address cases when partial overlaps and/or temporal gaps exist. A new Power Exponential Knothe Model (PEKM) fits and fuses overlaps in the deformation curves, while a Long Short-Term Memory (LSTM) neural network predicts and fuses any temporal gaps in the series. Taking the city of Wuhan (China) as experiment area, COSMO-SkyMed (2011-2015), TerraSAR-X (2015-2019) and Sentinel-1 (2019-2021) SAR datasets were fused to map long-term surface deformation over the last decade. An independent 2011-2020 InSAR time series analysis based on 230 COSMO-SkyMed scenes was also used as reference for comparison. The correlation coefficient between the results of the fusion algorithm and the reference data is 0.87 in the time overlapping region and 0.97 in the time-interval dataset. The correlation coefficient of the overall results is 0.78, which fully demonstrates that the algorithm proposed in our paper achieves a similar trend as the reference deformation curve. The experimental results are consistent with existing studies of surface deformation at Wuhan, demonstrating the accuracy of the proposed new fusion method to provide robust time series for the analysis of long-term land subsidence mechanisms.

Structural Health Monitoring (SHM) is a field of increasing interest and worthy of new approaches and innovative applications. As well known, Italy boasts a unique cultural-historical heritage of monuments and archeological sites that need to be managed, particularly in a multi-hazard prone area like our country. A really appealing technique is represented by the advanced multi-temporal differential interferometry synthetic aperture radar (MT-DInSAR), which has been developed and applied in different fields in the last twenty years. The exploitation of such techniques in the monitoring and structural assessment of cultural heritage is still an open issue even if the first applications available in literature show promising potentialities. In this paper the general framework for structural monitoring and assessment previously proposed by the authors, is applied to the complex building San Michele in Rome (Italy). In particular, COSMO-SkyMed (CSK) ascending and descending datasets are collected and processed applying the Small Baseline Subset (SBAS) method obtaining deformation time series and mean velocity maps of the persistent scatterers located in the investigated area, for both geometry acquisitions. Finally, different techniques useful for assessing the structural behavior and monitoring of constructions are applied and critically discussed.

Structural Health Monitoring (SHM) field gained increasing interest during the last years, also due to the huge amount of civil structures and infrastructures near or beyond their design life, and needs to be managed, particularly in a multi-hazard prone area like Italy. In this context, the advanced multi-temporal differential interferometry synthetic aperture radar (MT-DInSAR) techniques represent a great potential for the SHM applications and future development. The exploitation of such techniques in the monitoring and structural assessment of the built environment is still an open issue even if some first applications are available in literature showing promising potentialities. In this work, after a brief description of the general framework for structural monitoring and assessment, previously proposed by the authors, the case study of the Torri Stellari buildings in Rome (Italy) is presented and critically discussed. In particular, starting from COSMO-SkyMed (CSK) ascending and descending SAR datasets and applying the Small BAseline Subset (SBAS) DInSAR processing technique, the measurement points of the investigated area are obtained for both acquisition geometries. Different techniques are applied to both the displacement time series and mean deformation velocity for assessing the structural behavior or monitoring of constructions.

Differential Synthetic Aperture Radar Interferometry (DInSAR) is becoming one of the key techniques to measure ground deformation in any atmospheric conditions, with continuous day and night imaging capabilities and a high accuracy level, thanks to its capability to provide dense measurements at large spatial scale and at relatively low cost. The increasing diffusion of the use of DInSAR is also due to the large availability of huge and easily accessible SAR data archives, as those acquired, since late 2014, by the Copernicus Sentinel-1 constellation, which is globally and routinely providing C-band SAR data with a defined repeat-pass frequency. Therefore, with such a constant and reliable availability of data, it is possible to use the DInSAR technique for monitoring purposes, such as those related to the measurements of ground motion in natural hazard prone areas.

In this work, we present an advanced implementation of the full resolution Parallel Small BAseline Subset (P-SBAS) DInSAR processing chain, aimed to effectively and automatically generate DInSAR products (displacement time series and corresponding velocity maps) related to single buildings and infrastructures over the whole Italian territory. The proposed full resolution P-SBAS pipeline exploits innovative hardware and software parallel technologies based on GPUs, which are able to efficiently process large amounts of full resolution DInSAR data stacks in reasonable time frames and with high scalability. The presented results, achieved by processing very large archives of full resolution X-band first and second generation COSMO-SkyMed data and C-band Sentinel-1 images, demonstrate the effectiveness of the proposed solution in terms of computing time and computational efficiency.

We investigate the presence of possible bias affecting the deformation time series retrieved through the advanced differential SAR interferometry (DInSAR) algorithm referred to as Parallel Small BAseline Subsets (P-SBAS) approach. To do this we summarize the main results of a case study, originally presented by De Luca et al., 2021, which is based on the extensive analysis of a Sentinel-1 dataset relevant to an area in Sicily (southern Italy). The presented analysis allow us to show that the deformation time series obtained through the P-SBAS approach do not present significant bias, thus clarifying that there is no need to exclude the short temporal baseline interferograms when dealing with advanced DInSAR analyses. Moreover, our results confirm that the small baseline interferograms are beneficial in order to mitigate the impact of phase unwrapping errors and to maximize the coherent pixels spatial density of the achieved results.

Reservoirs accumulate and evolve magma during decades to centuries under Canary Islands volcanoes. Finally, magma migrates towards the surface before eruptions. However, little is known about the pathways and mechanisms controlling this migration. Past low eruption recurrence rate and the fact that the most recent 2011-2012 El Hierro eruption was off-shore hampered us to fully understand the magma(s) migration process. During the 2021 Cumbre Vieja eruption eruptible magmas showed remarkable mobility during the preceding 8 days before the eruption on the 13th of September 2021. This magma migration was reflected as surface ground deformation and seismicity. We used satellite radar interferometry to track 1) the geometry of the active magmatic reservoirs, and 2) the dynamics of magma emplacement and migration. To further, speculate about the reasons for that geometry and dynamics. Hence, the 2021 Cumbre Vieja eruption represents a unique opportunity to learn more about the mechanisms that facilitate magma migration beneath these volcanoes, and compare it with similar basaltic volcanoes. Our work aims to contribute knowledge that will help hazard assessment and volcanic risk reduction.

The Thessaly seismic sequence (TSS) in Central Greece, started on 3 March 2021 with a Mw 6.3 event that struck an area located about 25 km WNW of the Larissa town. In the following days, TSS was affected by other two major events: An Mw 6.0 on March 4, localized about 7 km to the northwest of the first one, and a Mw 5.6 on March 12, located 12 km further towards the northwest of the second one. A large number of smaller events have been also recorded until mid-April when the sequence decreased in frequency and magnitude. The TSS represents the largest seismic sequence affecting a continental extensional domain in Greece that has been monitored by modern geodetic techniques. Thanks to the short satellite revisit time, InSAR measurements made it possible to isolate each contribution of the three major earthquakes of the sequence, thus allowing the study of their interactions. In addition, available geological data indicate that the northern sector of Thessaly represents a large seismic gap. This may be a direct consequence of the limited size of the faults (less than 20 km) and their intrinsic capability to originate earthquakes of small-to-moderate magnitude only. TSS, which finally filled the gap, confirmed this hypothesis. We modelled the available InSAR deformation maps to retrieve the parameters characterizing some finite dislocation sources, which were used to perform a Coulomb stress transfer in order to investigate possible faults interactions. To constrain the geometry and location of the main fault structures involved during the TSS, we considered 1853 earthquakes occurred in the area from 28 February 2021 to 26 April 2021 with magnitude ranging between 0.2 and 6.3. Our model shows that the TSS has nucleated at shallow depths (<12 km) and is related to the activation of several blind, previously unknown, faults; moreover, the seismic sequence developed in a sort of domino effect involving a complex interaction among the normal faults within the activated crustal volume. As for the temporal evolution of the sequence, the delayed triggering of the Mw 6.0 earthquake can be explained by the distribution of the events occurred earlier, which encircle the asperities that will fail in the subsequent event together with a fluid diffusion in the seismogenic volume. Finally, we highlight the key role played by the configuration of the Thessaly Basin characterized by blind faults interconnected at depth, particularly interesting from the neotectonics point of view. The used approach can help improving our knowledge on the seismic potential of the Thessaly region and refine the associated seismic hazard.

This paper, presents the initial results of digital elevation model (DEM) extraction from PAZ Synthetic Aperture Radar (SAR) satellite images using repeat-pass interferometric analysis. We used a multi-temporal high-resolution strip-map mode X-band satellite image that has a single polarization. Five main classes, i.e., volcanic structures, agriculture, settlement, sand dune and plain bareland are considered depending on the structure of the region. Within the category, the coherence value and DEM value are evaluated. In the accuracy assessment analysis, a reference map produced from aerial photogrammetry is used. Additionally, global DEM TanDEM-X data is also tested in the study region. In the analysis, quality metrics, mean error (ME), root means square error (RMSE), standard deviation (STD), and the normalized median absolute deviation (NMAD) are used. The results showed that as the temporal baseline increases the coherence values and the quality of the DEM product decrease. The RMSE values range between 2.36 m to 7.09 m in different classes. The TanDEM-X data provided high accuracies over each class range from 0.88 m to 2.40 m. Since the study area is vulnerable to sinkhole formation, sinkhole-like signals were also observed in the interferograms obtained from different and sequential pairs. The high-resolution repeat-pass PAZ data pointed out its potential for interferometric products generation.

The current and planned synthetic aperture radar (SAR) sensors mounted on satellite platforms will continue to operate over the coming years, providing unprecedented SAR data for monitoring wide-range surface deformations. The near real-time processing of SAR interferometry (InSAR) data for the retrieval of ground-deformation time series is urgently required in the current era of big data. The state-of-the-art Kalman filter (KF) and sequential least squares (SLS) algorithms have been proposed to update an InSAR-driven ground-deformation time series. As a contribution of this study, we customize the conventional KF and SLS for big InSAR data for near real-time processing. The development of an accurate prediction model for KF-based InSAR processing is a challenge owing to the large scale of the targets for surface monitoring. We developed a modified KF algorithm, abbreviated as npKF, that does not require any prediction information, abbreviated as npKF. In this context, to avoid occupying a large storage space in SLS-based InSAR processing, we developed a modified SLS algorithm with a truncated cofactor matrix, abbreviated as TSLS. Using both simulated and actual SAR data, we evaluated the performance of these methods under three different aspects: accuracy, computation, and storage performance. With big data, the proposed method can estimate the deformation time series in near real time. It will be a reliable and effective tool for producing near real-time InSAR deformation products in the coming era of processing big SAR data and will play a part in the geologic hazard routine monitoring and early warning system.

This work explores the properties characterizing the phase non-closure of multi-look synthetic aperture radar (SAR) interferograms. Specifically, we study the implications of multi-look phase time incongruences on the generation of ground displacement time-series through small baseline (SB) multi-temporal InSAR (Mt-InSAR) methods. Our research clarifies how these phase inconsistencies can propagate through a time-redundant network of SB interferograms and contribute, along with phase unwrapping (PhU) errors, to the quality of the generated ground displacement products. Moreover, we analyze the effects of short-lived phase bias signals that could happen in sequences of short baseline (SB) interferograms and propose a strategy for their mitigation. The developed methods have been tested using both simulated and real SAR data. The latter were collected by the Sentinel-1A/B (C-band) sensors over the study areas of Nevada state, U.S., and Sicily Island, Italy.