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In Switzerland, more than 60% of the territory is mountainous, and this characteristic is a main natural resource attracting every year millions of tourists. However, this peculiarity exposes the country also to hazard potential due to the effect of different slope processes (e.g. deep seated gravitational deformations, rock avalanches, rock falls, debris flows, etc.). Moreover, the value of infrastructures and the strategic importance of transportation corridors present in Switzerland expose also neighboring countries to direct and indirect risks in case of catastrophic events. In this scenario, studying surface deformation may help understanding mountain processes, detecting preparatory conditions for potential failure events, and eventually planning countermeasures. Among EO methods, spaceborne radar interferometry has demonstrated great advantages to perform this task. Moreover, the recent advent of the Copernicus Sentinel-1 (S1) constellation has increased our capability to observe surface deformation over wide regions with higher revisit times. Here we present the results obtained by processing 107 images acquired from S1 constellation between April 20, 2015 and March 11, 2018. Differential interferograms were computed and combined taking advantage of the P-SBAS algorithm to obtain ground velocities and displacement time series at the country scale. We discuss the potential of such datasets in alpine countries such as Switzerland, as well the challenges for their thoughtful utilization.

In this work we implement a completely automatic interferometric processing chain, based on the well-known advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS), for the generation of Sentinel-1 (S-1) Interferometric Wide Swath (IWS) deformation mean velocity maps and time-series of very wide areas, implemented within the Amazon Web Services (AWS) Elastic Cloud Compute environment. Our processing chain consists of the initial data query to the S-1 archive that we created on the AWS S3 storage, then the data transfer to the AWS computing nodes, the data processing and, finally, the transfer of the obtained interferometric results back to the original S3 storage.

We are writing this comment because many aspects of the analysis presented by Nappi et al. (2018) are debatable. In particular, a major issue is relevant to the conclusion suggested by Nappi et al. (2018) about a seismogenic normal fault with northward dip; this finding is not grounded because the Authors do not really present a causative source model and, above all, their statement is clearly not consistent with the DInSAR, GPS and seismological measurements presented in the manuscript previously published by De Novellis et al. (2018). Moreover, we also report an evident error in the geologic map proposed by Nappi et al. (2018), see Figure 3 of their manuscript.

Il volume è il quinto di una serie dedicata alle attività svolte nell'ultimo quadriennio dall'Istituto per il Rilevamento Elettromagnetico dell'Ambiente (IREA). Negli ultimi anni c'è stata in IREA un'attenzione sempre crescente alle attività di comunicazione, diffusione e valorizzazione dei risultati della ricerca di cui questo Report è uno dei principali strumenti assieme al sito web. L'obiettivo è quello di illustrare le attività che si svolgono nell'Istituto che, grazie alle competenze presenti, alle sue caratteristiche di multidisciplinarietà e alla vitalità scientifica che lo anima, è diventato un punto di riferimento nell'ambito dei settori di ricerca nei quali opera. Ma lo scopo è anche quello di diffondere la conoscenza scientifica acquisita su temi di rilevante interesse pubblico e sociale verso il mondo esterno a quello scientifico in senso stretto.

The Sentinel-1 (S1) constellation is a family of satellites designed to collect C-band SAR data in continuity with the previous ERS-1/2 and ENVISAT missions, within the framework of the Copernicus Programme of the European Union, with the aim to detect and analyze Earth's surface displacements. S1 is characterized by significant enhancements in terms of spatial coverage, revisit time, timeliness and service reliability. In particular, S1 Interferometric Wide Swath (IWS) scenes are collected through the innovative acquisition mode referred to as Terrain Observation by Progressive Scans (TOPS) [1], which allows a considerable improvement of the range coverage (of about 250 km) with respect to the conventional Stripmap mode, and, at the same time, a significant increase of the acquired SAR data size (around 10 times greater than ERS and ENVISAT scenes). Moreover, the constellation is nowadays made up of two twin sensors (Sentinel-1A and Sentinel-1B) that acquire images all around the world with a repeat pass of 6 days in most areas, thus leading to the creation of large SAR data archives, which can be exploited according to a "free and open" data distribution policy. Such characteristics require the development of innovative and appropriate solutions aimed at handling these huge SAR data archives, more and more increasing in terms of both temporal and spatial coverage, to effectively and routinely exploit the advanced DInSAR methodologies. In this work we present a strategy to perform massive, systematic and automatic analysis of S1 SAR data via the generation of deformation time series. In particular, we propose a solution, based on the Parallel version of the well-known SBAS algorithm (P-SBAS) [2][3], properly designed for processing S1 SAR data. Our solution takes advantage of the P-SBAS characteristics to run on distributed computing infrastructures (i.e., cluster, grid, cloud) by making use of both multi-core and multi-node programming techniques and exploiting an "ad - hoc" designed distributed storage [4]. Moreover, it strongly takes into account the data characteristics of the TOPS mode. Indeed, IWS scenes consist of series of bursts that can be considered as independent, separate acquisitions. This makes a large part of the processing inherently parallel at a burst granularity level; such a condition implies that the processing time can be significantly reduced when large computing resources are available. The developed S1 P-SBAS processing chain is exploited to generate mean deformation velocity maps and corresponding deformation time series of South Italy. In particular, we processed six S1 interferometric SAR data stacks, acquired along descending orbits (tracks 22, 124, 51) and spanning the time interval October 2014 - September 2016. Starting from these data (almost 300 slices), we generated 850 differential interferograms with 5 looks in azimuth and 20 in range directions, thus resulting in a pixel size of approximately 60 x 60 m. In Figure 1 we display the retrieved LoS mean deformation velocity map, geocoded and superimposed on an optical image of the area. The map reveals the presence of localized displacements associated, for instance, to the volcanic activity of the caldera of Campi Flegrei and Mt. Etna volcano. The achieved results demonstrate the capability of the presented processing chain to effectively deal with massive amount of data to generate advanced DInSAR products aimed at detecting displacements at very large spatial scale. Moreover, they show that S1 P-SBAS can be exploited to build up operational services for the easy and rapid generation of advanced interferometric products that can be very useful within risk management and natural hazard monitoring scenarios. Acknowledgments This work has been supported by the Ministry of Economic Development - DGS-UNMIG (Directorate-General for Safety of Mining and Energy Activities - National Mining Office for Hydrocarbons and Georesources), the Italian Department of Civil Protection, the European Union Horizon 2020 research and innovation programme under the EPOS-IP project (grant agreement No 676564), the ESA GEP (Geohazards Exploitation Platform) and I-AMICA (Infrastructure of High -55- Technology for Environmental and Climate Monitoring - PONa3_00363) projects. Sentinel-1 data are copyright of Copernicus (2016). The DEMs of the investigated zone were acquired through the SRTM archive. References [1] F. De Zan and A. M. Monti Guarnieri, "TOPSAR: Terrain Observation by Progressive Scans," IEEE Transactions on Geoscience and Remote Sensing, vol. 44, no. 9, pp. 2352-2360, Sept. 2006. [2] Berardino, P., Fornaro, G., Lanari, R., Sansosti, E., "A new Algorithm for Surface Deformation Monitoring based on Small Baseline Differential SAR Interferograms", IEEE Trans. Geo. Rem. Sens., 40, 11, pp. 2375-2383, 2002. [3] F. Casu, S. Elefante, P. Imperatore, I. Zinno, M. Manunta, C. D. Luca, and R. Lanari, "SBAS-DInSAR Parallel Processing for Deformation Time-Series Computation," Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal, 2014. [4] Zinno, S. Elefante, L. Mossucca, C. De Luca, M. Manunta, O. Terzo, R. Lanari, and F. Casu, "A First Assessment of the P-SBAS DInSAR Algorithm Performances Within a Cloud Computing Environment," IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., pp. 1-12, 2015.

We investigate the ground deformation pattern and the source geometry responsible of the 2016 Central Italy seismic sequence (CISS) by joint exploiting the Multisensors and Multiorbits satellite measurements (i.e. Sentinel-1 and ALOS 2) and the integration with the available geological/structural and seismological data. To this purpose we integrate these measurements in a physically-based optimization model scenario. We consider the new seismic sequence that struck Umbria-Marche Apennines (Central Italy) since the month of August 2016. This seismic sequence started with the Amatrice earthquake (MW 6.0) occurred on August 24th. This event nucleated along a SW dipping extensional lineament, called the Mt. Gorzano fault (e.g. Boncio et al., 2004), and caused 299 casualties and severe damages to buildings and historical monuments, devastating Amatrice itself, Accumoli and other surrounding small towns. During the following months, very numerous aftershocks have nucleated and the CISS has migrated northward (e.g. Tinti et al., 2016). On October 26th two intense events occurred with ML 5.4 and ML 5.9, respectively. Moreover, on October 30th the strongest event of the sequence occurred with MW 6.5 close to the small town of Norcia and nucleated along the Mt. Vettore extensional fault (e.g. Galadini & Galli, 2003). The involved area is still active and a lot of earthquake nucleate every day: up to now, the INGV seismic network has recorded more than 30000 events. Despite to the tectonic complexity of the 2016 CISS, we achieved a good determination/description of the ground deformation pattern thanks to the big amount of SAR data acquired by Sentinel-1 (ESA) and ALOS 2 (JAXA) satellites, characterized by small temporal baselines and from different orbits (ascending and descending orbits). In this way, we can analyse in greater detail the ground deformation pattern of the individual seismic events, also decomposing the vertical component and the east-west one. In this context SAR data are a fundamental tool to better understand the spatio-temporal evolution of 2016 CISS. In this context, the present study, benefiting from satellite and in situ information, will investigate, through a numerical optimization multiphysics approach, the most suitable geological scenario that governed the spatial and temporal evolution of the Amatrice-Norcia seismic sequence. References Boncio, P., Lavecchia, G., Milana, G., & Rozzi, B. (2004). "Seismogenesis in Central Apennines, Italy: an integrated analysis of minor earthquake sequences and structural data in the Amatrice-Campotosto area." Annals of Geophysics, vol. 47, issue 6, December 2004. Galadini, F., & Galli, P. (2003). "Paleoseismology of silent faults in the Central Apennines (Italy): the Mt. Vettore and Laga Mts. faults." Annals of Geophysics, vol. 46, issue 5, October 2003. Tinti, E., Scognamiglio, L., Michelini, A., & Cocco, M. (2016). "Slip heterogeneity and directivity of the ML 6.0, 2016, Amatrice earthquake estimated with rapid finite-fault inversion." Geophysical Research Letters, vol. 43, issue 20.

The SENTINEL-1 (S1) mission is designed to provide operational capability for continuous mapping of the Earth thanks to its two polar-orbiting satellites (SENTINEL-1A and B) performing C-band synthetic aperture radar (SAR) imaging. It is, indeed, characterized by enhanced revisit frequency, coverage and reliability for operational services and applications requiring long SAR data time series. Moreover, SENTINEL-1 is specifically oriented to interferometry applications with stringent requirements based on attitude and orbit accuracy and it is intrinsically characterized by small spatial and temporal baselines. Consequently, SENTINEL-1 data are particularly suitable to be exploited through advanced interferometric techniques such as the well-known DInSAR algorithm referred to as Small BAseline Subset (SBAS), which allows the generation of deformation time series and displacement velocity maps. In this work we present an advanced interferometric processing chain, based on the Parallel SBAS (P-SBAS) approach, for the massive processing of S1 Interferometric Wide Swath (IWS) data aimed at generating deformation time series in efficient, automatic and systematic way. Such a DInSAR chain is designed to exploit distributed computing infrastructures, and more specifically Cloud Computing environments, to properly deal with the storage and the processing of huge S1 datasets. In particular, since S1 IWS data are acquired with the innovative Terrain Observation with Progressive Scans (TOPS) mode, we could benefit from the structure of S1 data, which are composed by bursts that can be considered as separate acquisitions. Indeed, the processing is intrinsically parallelizable with respect to such independent input data and therefore we basically exploited this coarse granularity parallelization strategy in the majority of the steps of the SBAS processing chain. Moreover, we also implemented more sophisticated parallelization approaches, exploiting both multi-node and multi-core programming techniques. Currently, Cloud Computing environments make available large collections of computing resources and storage that can be effectively exploited through the presented S1 P-SBAS processing chain to carry out interferometric analyses at a very large scale, in reduced time. This allows us to deal also with the problems connected to the use of S1 P-SBAS chain in operational contexts, related to hazard monitoring and risk prevention and mitigation, where handling large amounts of data represents a challenging task. As a significant experimental result we performed a large spatial scale SBAS analysis relevant to the Central and Southern Italy by exploiting the Amazon Web Services Cloud Computing platform. In particular, we processed in parallel 300 S1 acquisitions covering the Italian peninsula from Lazio to Sicily through the presented S1 P-SBAS processing chain, generating 710 interferograms, thus finally obtaining the displacement time series of the whole processed area.

We investigate a large geodetic data set of interferometric synthetic aperture radar (InSAR) and GPS measurements to determine the source parameters for the three main shocks of the 2016 Central Italy earthquake sequence on 24 August and 26 and 30 October (M-w 6.1, 5.9, and 6.5, respectively). Our preferred model is consistent with the activation of four main coseismic asperities belonging to the SW dipping normal fault system associated with the Mount Gorzano-Mount VettoreMount Bove alignment. Additional slip, equivalent to a Mw similar to 6.1-6.2 earthquake, on a secondary (1) NE dipping antithetic fault and/or (2) on a WNW dipping low-angle fault in the hanging wall of the main system is required to better reproduce the complex deformation pattern associated with the greatest seismic event (the Mw 6.5 earthquake). The recognition of ancillary faults involved in the sequence suggests a complex interaction in the activated crustal volume between the main normal faults and the secondary structures and a partitioning of strain release.

We present the main activities and the most significant results that the Institute for Electromagnetic Sensing of the Environment (IREA) of the National Research Council (CNR) has retrieved within the framework of its collaboration with the Ministry of Economic Development (MiSE) - Directorate- General for Safety of Mining and Energy Activities National Mining Office for Hydrocarbons and Georesources (DGS-UNMIG). In particular, this agreement aims at detecting and monitoring surface deformation affecting the areas of particular interest for the DGS-UNMIG through space-borne Differential SAR (Synthetic Aperture Radar) Interferometry (DInSAR) analysis and multi-parameters and multi-physics modelling. The first ones provide information on the spatial distribution of the retrieved ground displacements and their temporal evolution, the second on the geological/geophysical processes that characterize the investigated areas. In this work, we present the preliminary results retrieved via interferometric analysis performed by exploiting SAR data acquired from the first (ERS-ENVISAT) and second (Sentinel-1) generation sensors over the Emilia-Romagna Region (North Italy) and the entire Italian Peninsula, respectively. Moreover, we performed a 3D geological-structural model of the Cavone site (Emilia-Romagna) and a 3D FEM (Finite Element Method) model for simulating the co-seismic dislocation of the M6.0 and M5.8 seismic events, which occurred on 20/05/2012 and 29/05/2012 over Emilia-Romagna region, respectively.

In the last decades Earth Observation (EO) from space has very fast evolved through the development of remote sensing data-acquisition systems, contributing to the creation of a Big EO Data scenario. In this work, we present a Cloud Computing solution for the advanced interferometric (DInSAR) processing chain based on the Parallel SBAS (P-SBAS) approach, aimed at processing Sentinel-1 (S1) Interferometric Wide Swath (IWS) data for the generation of large spatial scale deformation maps and corresponding displacement time series in an efficient, automatic and systematic way. The presented approach has been used to perform a national-scale DInSAR analysis over Italy, involving the processing of more than 3000 S1 IWS images acquired from both ascending and descending orbits. Details on the cloud infrastructure and processing times will be presented.

Detection and monitoring of deformations affecting cultural heritage sites and their surroundings represent a key issue for developing strategies for their preservation, particularly in the case of extended archaeological areas. In this chapter, we first introduce the differential SAR interferometry (DInSAR) techniques that, thanks to their capability of performing noninvasive deformation analyses, provide valuable information about the spatial and the temporal evolution of the detected displacements. Subsequently, we present the DInSAR results achieved over the whole archaeological site of the ancient Roman city of Pompeii (Italy), and focus on some historical buildings where small displacements, involving portions or the whole complex structure, have been detected. The performed analysis confirms the relevance of the DInSAR techniques for developing sustainable strategies aimed at the preservation of cultural and historical heritage sites.

In this work we present an efficient interferometric processing chain, based on the advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS), for the generation of Sentinel-1A (S1A) Interferometric Wide Swath deformation time-series, which is able to exploit distributed computing architectures. The presented S1A P-SBAS processing chain has been successfully implemented within the ESA Geohazard Exploitation Platform to provide an on-demand automatic service for the unsupervised generation of P-SBAS displacement time-series. To give an idea of the effectiveness of the presented S1A processing chain, as a preliminary result we show a 12-days interferometric analysis at continental scale, carried out by exploiting 150 S1A interferometric pairs acquired over Europe for an overall covered area of about 7,500,000 km2.

TCS Satellite Data is devoted to provide Earth Observation (EO) services, transversal with respect to the large EPOS community, suitable to be used in several application scenarios. In particular, the main goal is to contribute with mature services that have already well demonstrated their effectiveness and relevance in investigating the physical processes controlling earthquakes, volcanic eruptions and unrest episodes as well as those driving tectonics and Earth surface dynamics. The TCS Satellite Data will provide two kinds of services: satellite products/services, and Value-added satellite products/services. The satellite products/services are composed of three (EPOSAR, GDM and COMET) wellidentified and partly already operational elements for delivering Level 1 products. Such services will be devoted to the generation of SAR interferograms, DTM and ground displacement maps through the exploitation of different advanced EO techniques for InSAR and optical data analysis. The Value-added satellite products/services are composed of 4 elements (EPOSAR, 3D-Def, Mod and COMET) of Level 2 and 3 products. Such services integrate satellite and in situ measurements and observations to retrieve information on source mechanism, such as the geometry (spatial location, depth, volume changes) and the physical parameters of the deformation sources, through the exploitation of modelling approaches. The TCS Satellite Data will provide products in two different processing and delivery modes: 1- surveillance mode - routinely product generation; 2- on demand mode - product generation performed on demand by the user.

We investigate the ground deformation and source geometry of the 2016 Amatrice earthquake (Central Italy) by exploiting ALOS2 and Sentinel-1 coseismic differential interferometric synthetic aperture radar (DInSAR) measurements. They reveal two NNW-SSE striking surface deformation lobes, which could be the effect of two distinct faults or the rupture propagation of a single fault. We examine both cases through a single and a double dislocation planar source. Subsequently, we extend our analysis by applying a 3-D finite elements approach jointly exploiting DInSAR measurements and an independent, structurally constrained, 3-D fault model. This model is based on a double fault system including the two northern Gorzano and Redentore-Vettoretto faults (NGF and RVF) which merge into a single WSW dipping fault surface at the hypocentral depth (8 km). The retrieved best fit coseismic surface deformation pattern well supports the exploited structural model. The maximum displacements occur at 5-7 km depth, reaching 90 cm on the RVF footwall and 80 cm on the NGF hanging wall. The von Mises stress field confirms the retrieved seismogenic scenario.

Here we present the results of the inversion of a new geodetic data set covering the 2012 Emilia seismic sequence and the following 1 year of postseismic deformation. Modeling of the geodetic data together with the use of a catalog of 3-D relocated aftershocks allows us to constrain the rupture geometries and the coseismic and postseismic slip distributions for the two main events (M-w 6.1 and 6.0) of the sequence and to explore how these thrust events have interacted with each other. Dislocation modeling reveals that the first event ruptured a slip patch located in the center of the Middle Ferrara thrust with up to 1 m of reverse slip. The modeling of the second event, located about 15 km to the southwest, indicates a main patch with up to 60 cm of slip initiated in the deeper and flatter portion of the Mirandola thrust and progressively propagated postseismically toward the top section of the rupture plane, where most of the aftershocks and afterslip occurred. Our results also indicate that between the two main events, a third thrust segment was activated releasing a pulse of aseismic slip equivalent to a M-w 5.8 event. Coulomb stress changes suggest that the aseismic event was likely triggered by the preceding main shock and that the aseismic slip event probably brought the second fault closer to failure. Our findings show significant correlations between static stress changes and seismicity and suggest that stress interaction between earthquakes plays a significant role among continental en echelon thrusts.

On 24 August 2016, at 01:36 UTC¸ the intra-Apennine extensional fault system of Central Italy released a destructive earthquake (MW 6.0). It produced widespread damage and fatalities, killing about 300 people and severely destroying the town of Amatrice and surrounding villages. After few hours, the Amatrice earthquake was followed by a significant aftershock (MW 5.5), which nucleated 15 km NW-ward. The epicentral area of the seismic sequence extends in the NNW-SSE direction, for a length of about 25-30 km. It is located at the hanging-wall of the WSW-dipping Vettore-Gorzano active extensional fault system. During the days following the main shock, a significant number of Synthetic Aperture Radar (SAR) data have been acquired from different passes and angles by the L-band ALOS-2, C-band Sentinel-1 and X-band COSMO-SkyMed satellites. This allowed us to map in a very short time the co-seismic ground displacements through the Differential SAR Interferometry (DInSAR) technique, and also to evaluate their Vertical and East-West components with high details. The generated interferometric pattern is characterized by a double-eyed co-seismic shape that spans 20 km along the NNW-SSE direction and that well coincides with the epicentral areas. We modeled the seismic source that well fit the Mw 6.2 event. In particular, for this analysis, we separately applied an analytical Okada approach as well as a 3D Finite Element (FE) numerical modeling, the latter jointly exploiting DInSAR measurements and structural-geological data. The model obtained via the FE approach suggests that the Amatrice 2016 earthquake nucleated at 8 km deep along the intersection line between the Vettoretto-Redentore and the Northern Gorzano faults, and instantly geminated in two rupture patches that radiated with an approximate bilateral symmetry on the two fault planes. The two rupture patches covered differently shaped slip area, with aspect ratio that well recalls the shape of the interferometric lobes of ground subsidence at the two faults hanging wall. The different shapes of the two lobes are partially associated to the different dip-angle of the Vettoreto-Redentore and Gorzano faults (50° ad 60° respectively). In summary, we found evidences of bilateral rupture propagating along two en-echelon faults connected at the hypocenter.

We show the results of the inversion of a new geodetic dataset, involving both remote sensing and ground-based data: high precision levelling data, GPS observations and Differential Synthetic Aperture Radar Interferometry (DInSAR) products covering the 2012 Emilia seismic sequence and the following one year of post-seismic deformation. As far as DInSAR analysis, we used data acquired by the RADARSAT-2 (RSAT2) satellite from the Canadian Space Agency and by the COSMO-SkyMed (CSK) constellation developed by the Italian Space Agency in cooperation with the Ministry of Defense. For what attains the RSAT2 mission, we considered a single interferometric pair only, involving the 30 April and 17 June 2012 stripmap acquisitions, aimed at measuring the cumulative coseismic ground displacement due to the two mainshocks (20 and 29 May 2012). As for the CSK mission, a dataset of 12 stripmap images covering a time interval of almost one year, from 27 May 2012 to 7 May 2013, allowed measuring the coseismic displacement field relevant to the 29 May mainshock as well as one year of post-seismic deformation. To retrieve the CSK deformation time series relevant to the post-seismic sequence, we applied the Small BAseline Subset (SBAS) algorithm [Berardino et al., 2002], specifically the one in Fornaro et al. [2009]. By use of the geodetic dataset together with a catalog of relocated aftershocks, we modeled rupture geometries, and the coseismic and post-seismic slip distributions for the two main events (MW 6.1 and 6.0) of the sequence, allowing us to suggest the influence of structure and/or lithology on slip propagation in intracontinental settings. Moreover, we explored how these thrust events have interacted with each other and, defining the Coulomb stress changes, how first mainshock triggered following activity. Our results also indicate that between the two main events, a third thrust segment was activated by first mainshock, releasing a pulse of aseismic slip equivalent to a MW 5.8 event. We also hypothesized that the aseismic slip event probably brought the second fault closer to failure. Generally, we found that among continental en echelon thrusts, stress transfer and interaction between earthquakes and aseismic slip may play an important role in the way they activate during a seismic sequence. References Berardino, P., Fornaro, G., Lanari, R. and Sansosti, E (2002). A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms, IEEE Trans. Geosci. Remote Sens., 40, 2375-2383 Fornaro, G., Pauciullo, A. and Serafino, F. (2009). Deformation monitoring over large areas with multipass differential SAR interferometry: a new approach based on the use of spatial differences, Int. J. Remote Sens., 30, 1455-1478.

This paper presents the framework of a research program, theoretical and experimental in nature, issued by a cooperative multidisciplinary group of the Department of Earth Sciences – University of Naples Federico II and of the Institute for Electromagnetic Sensing of the Environment (CNR-IREA) National Research Council in Naples. The objective is the analysis of land subsidence phenomena that develop in many areas and are related to over-pumping of groundwater resources by means of advanced technologies to measure surface displacements (inSAR techniques). In the last years many studies showed the great potential of this technique to recognize the hydrodynamic conditions of several strategic regions (Galloway & Hoffmann, 2007). The correlation between the spatial distribution of the surface displacements and the hydrogeological data enables to identify structural and/or lithostratigraphic features that control the groundwater flow (e.g. Bawden et al., 2001; Buckley et al., 2003; Schmidt & Burgmann, 2003) likewise to point out the influence of the natural or man-induced fluctuations of the water level on the temporal spreading of surface deformations (e.g. Hoffmann et al., 2001, 2003; Colesanti et al., 2003; Ferretti et al., 2004), till to evaluate hydrodynamic parameters such .as the hydraulic conductivity and storage coefficient of aquifer systems (Hoffmann et al., 2001, 2003; Halford et al., 2005). In particular, the present paper deals with a sample application of the methodology to analyze both at long-term and short-term the subsidence phenomena and with related review of geological, geotechnical and hydrogeological data on the Campanian Plain (South Italy), in two sectors characterized by different spatial and temporal evolution of groundwater hydrodynamic during the reference period of land subsidence.

In the framework of MORFEO project, financed by the Italian Space Agency (ASI), a study is currently under way to estimate and validate monitoring technologies of deformations with SAR data, to the implementation of a pre-operational service supporting the Civil Protection Department in landslide risk monitoring. The study on ground deformations is performed in MORFEO by applying two different technologies: SBAS developed by CNR-IREA in Naples and SPINUA developed by Politecnico of Bari. These technologies work with SAR data in C band and the use of X band data acquired by COSMO/SKY-MED is under trial. In particular the present report describes the generation and validation activities of EO SAR products (Synthetic Aperture Radar) obtained in landslide areas in Lombardia and Umbria by using ascending and descending passages of ENVISAT satellite. The results obtained in Umbria highlight the presence of deformation phenomena in the area corresponding to the landslide region in Ivancich (Assisi). A general accordance between GPS and SAR sets results by the comparison. In Lombardia GPS deformation time sets have been estimated for SAR data validation. This has highlighted the potential and limits of SAR interferometric techniques for landslide monitoring in an alpine context. Moreover, a first multi-temporal interferometric analysis in X band has been carried out through the SPINUA algorithm. Preliminary results over the area of GARZENO (COMO) show that even with a limited number of COSMO/SkyMED images, there is a good agreement with linear displacement rate maps estimated in C-band. An accurate investigation shall be feasible as soon as a consistent number of COSMO/SkyMED acquisitions is available (not less than 25-30).

Volcanoes deform as a consequence of the rise and storage of magma; once magma reaches a critical pressure, an eruption occurs. However, how the edifice deformation relates to its eruptive behavior is poorly known. Here, we produce a joint interpretation of spaceborne InSAR deformation measurements and volcanic activity at Mt. Etna ( Italy), between 1992 and 2006. We distinguish two volcano-tectonic behaviors. Between 1993 and 2000, Etna inflated with a starting deformation rate of similar to 1 cm yr(-1) that progressively reduced with time, nearly vanishing between 1998 and 2000; moreover, low-eruptive rate summit eruptions occurred, punctuated by lava fountains. Between 2001 and 2005, Etna deflated, feeding higher-eruptive rate flank eruptions, along with large displacements of the entire East-flank. These two behaviors, we suggest, result from the higher rate of magma stored between 1993 and June 2001, which triggered the emplacement of the dike responsible for the 2001 and 2002-2003 eruptions. Our results clearly show that the joint interpretation of volcano deformation and stored magma rates may be crucial in identifying impending volcanic eruptions.