We present in this study an enhancement to our previous work, in which an automated method, based on Convolutional Neural Networks (CNNs), has been developed for identifying co-seismic ground deformation patterns within the Differential SAR Interferometry (DInSAR) maps generated through the EPOSAR service of the European Plate Observing System (EPOS) Research Infrastructure. The implemented improvements have been achieved through two main lines of actions. Firstly, the generation of the synthetic dataset, used to train the developed CNN, has been enhanced; this concerns the improvement of the simulation of possible atmospheric disturbance within the DInSAR interferograms, and the introduction of a simulator of phase unwrapping errors. Secondly, the original CNN-based deformation pattern detector layout, performing a binary classification, has been modified to account for a multiclass deformation pattern classification. This allows us extending the capability of the system which, in addition to detect co-seismic deformation patterns, may also provide information on the earthquake source characteristics. The presented solution will be included in the EPOSAR DInSAR processing chain.

Over the past 30 years it has been widely demonstrated the effectiveness of the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique to retrieve surface deformation information relevant to tectonically active areas. However, this technique exhibits some limitations due the presence of possible decorrelation effects, phase unwrapping errors, and artefacts due to the temporal/spatial variability of the atmospheric conditions between the SAR acquisition pairs exploited to generate the interferograms and the corresponding deformation maps or time series. A challenging situation may arise when an earthquake event occurs and a co-seismic DInSAR deformation map is generated to quickly support risk management operations. In this scenario, having an automatic process reducing the uncertainties of the retrieved, DInSAR-based, surface deformation information could highly improve the quality of the products made available to the scientific community and of the service provided to the national disaster recovery authorities. We present in this work a solution, based on standard CNN architectures embedded in the DInSAR processing chain of the EPOSAR service, developed within the European Plate Observing System (EPOS) Research Infrastructure, to automatically identify co-seismic ground deformation patterns.

On 14 November 2021, a doublet earthquake (Mw6.2 and Mw6.3) struck the Fin area in southern Iran. Utilizing the two-pass differential SAR Interferometry (InSAR) method, the coseismic deformation fields, retrieved from 12-day pairs descending and ascending Sentinel-l as well as descending ALOS-2, demonstrate a displacement pattern of maximum 40 cm toward the satellite in the epicentral area. The preliminary slip inversion from the InSAR analysis exhibits best fitting on an east-west trending (∼263°), north-dipping (∼71°) fault as well as an east-west trending (∼84°), south-dipping (∼15°) thrust with a maximum coseismic slip value of ∼2° meters. The south-dipping model shows a better fit and conforms well with the geological setting of the area introduced in the previous studies.

We develop a method of investigation to analyze the variability of the moment tensor solutions in case of light-to-moderate earthquakes. To this purpose, we compare the seismic-induced displacement field predicted from the available moment tensor solutions and estimated from Sentinel-1 InSAR data. The differences between simulated and real deformation scenarios are then evaluated both in terms of epicenter location and kinematics of the fault responsible for the event. Our test dataset consists of two events with a magnitude ranging from light to moderate occurred on 2019 in France and Turkey, respectively.

Sakurajima volcano is one of the most active volcanoes in Japan and caused the most powerful eruption in Japan in the last century (1914). Volcanic eruptions are often preceded by ground deformations. The activity of Sakurajima volcano is monitored through interferometric analysis of SAR data, ALOS Palsar-2 and Sentinel-1, to obtain caldera displacements over the observed period, from 2015 to 2019 and to investigate deformations correlated with inflation and deflation cycles of magma plumbing system, eruptions and diking. Time series are calibrated and validated through GEONET stations of the Geospatial Information Authority of Japan and the global navigation satellite System (GNSS) stations of the Sakurajima Volcano Research Centre. SAR and GPS information are used to identify the most dramatic events affecting the active Sakurajima area since 2015, specifically a dyke intrusion and the ongoing volcanic activity, characterized by several eruptive episodes.

Guagua Pichincha (4784 m a.s.1.) is a dacite-composed stratovolcano, located 12 km to the west of Quito, Ecuador's capital with over 2.7 million inhabitants. In the last decades, it was affected by seismic activity. Here, we present the results of multi-temporal InSAR (Interferometric SAR) processing over Guagua Pichincha volcano during 2014-2019, and the related volcanic source modelling. Our results show a general inflation of a restricted area of the volcanic edifice, reaching 2.7 cm/yr deformation rate in the inner caldera and a cumulative uplift of more than 10 cm in 5 years. The resolved ground velocities are better fitted adopting an ellipsoidal shaped tensile crack opening at a depth of 700 m below the domes, with its major axis of about 1 km length in the N36°E direction.

The use of SAR data for imaging hazardous events is nowadays a well-consolidated approach. Thanks to the synoptic capabilities of satellite data, their high spatial resolution and high revisit time, fast and accurate analysis can be performed at both regional and local scale. This work presents the results of SAR Interferometry applied to a multi-hazard event induced by the eruption of Etna volcano, occurred in late December 2018. We analyse both the syn-eruptive deformation of volcano edifice and the effects of an induced Mw4.9 earthquake and a small-scale landslide by exploiting ESA Sentinel-1 data. The data highlight a main horizontal displacement of the Etna summit of more than 40 cm and 65 cm along west and east directions, respectively. The earthquake caused about 15 cm displacement toward east and 20 cm toward west. Finally, approximately 5 cm displacement along satellite Line of Sight was observed associated to the landslide.

In Indonesia land subsidence is occurring in several cities [1], and it is very important to evaluate the spatial and temporal patterns of deformation and investigate the originating processes. In this work, we attempt to define the rates and spatial patterns of subsidence phenomena in Bandung city (Western Java, Indonesia) exploiting InSAR time-series techniques.The Greater Bandung metropolitan area is the second largest urban area in Indonesia, with a population of 8.6 million. The city is built on a plain, 30km in diameter and surrounded by a mountain range of 2000m peaks and it is exposed to a variety of severe geohazards. Floods are common in the lowest part of the plain just south of the city center. Landslides frequently occur on the mountain slopes. Five active volcanoes are within a 30-km radius. Earthquakes, although infrequent, are caused by nearby crustal faults and pose increasing concerns. The risk is also exacerbated due to climate change, fast urban development and land subsidence at an average rate of -8 cm per year.

In this study, multi-frequency Synthetic Aperture Radar Interferometry (InSAR) data are used to constrain the ground deformation due to the August 21st, 2017, Ischia earthquake. InSAR results are the input data to infer the source model of the seismic event. C-band Sentinel-l and X-band COSMO-SkyMed© InSAR results show a displacement pattern in the epicentral area, with a maximum value of ~3.5 cm and a dominant vertical component. Preliminary analytical and numerical models suggest that the retrieved InSAR ground displacements are due to the combination of two phenomena: the tectonic dislocation caused by the slip on the fault plane and the surficial displacement caused by the triggering of shallow landslides.

We exploit C-band Sentinel-1 and L-band ALOS-2 Synthetic Aperture Radar Interferometry (InSAR) data to constrain the seismic source of the Mw 6.0 intraplate earthquake occurred on May 20, 2016 in the central Australia. It is an uncommon seismic event since it occurred in a region characterized by low seismic activity. The retrieved source modeling revealed that the earthquake nucleated along a NW-SE-oriented reverse fault with a significant strike-slip component.

In this study, an analysis of the November 12, 2017 northwestern Iran earthquake (Mw 7.3) is presented. A multi-frequency Synthetic Aperture Radar Interferometry (InSAR) approach was adopted to retrieve the ground deformation due to the mainshock. Then, InSAR results were used as input for the source modeling of the seismic event. C-Band Sentinel-l (IW TOPSAR acquisition mode) and L-Band ALOS-2 (Wide Swath) SAR data along both the ascending and descending orbits were processed. InSAR results show a displacement pattern in the epicentral area, with a maximum value up to ~1.0 meter. Preliminary analytical and numerical models suggest that the retrieved InSAR ground displacements are due to a slip dislocation (over 3.8 meters) on the causative fault and that dips to the east with a shallow angle of 16°.

We used a variety of SAR-based techniques to measure the crustal deformation associated to the Darfield and Christchurch earthquakes, New Zealand. We detected clear post-seismic signals of the Darfield earthquake, and a pre-seismic signal spatially and temporally associated to the Christchurch earthquake. The small pre-seismic signal (∼25 mm) has an opposite polarity of the much larger co-seismic one (∼150 mm) in the same area.

The differential synthetic aperture radar interferometry (DInSAR) technique has dramatically boosted the application of remote sensing in many geophysical disciplines, particularly tectonics. Coseismic interferograms have provided, in many cases, “images of earthquakes,” showing the surface displacement due to the deep fault dislocation. Aside from being visually appealing, such interferograms are of fundamental importance for the analysis, by means of appropriate dislocation models, of the geometrical and kinematic characteristics of the fault, which are also parameters of key interest for earthquake risk management. This paper provides a contribution in the general framework of the integration of dislocation models in DInSAR processing. In particular, with reference to coseismic interferograms, it proposes a technique that allows the direct inversion of wrapped interferograms for dislocation model analysis. This option makes it possible to avoid the critical and error-prone processing step of phase unwrapping, carried out in the classical analysis of interferometric data. Examples of inversion of real data, relevant to the 1999 Athens and Izmit earthquakes, demonstrate the feasibility and the advantages of this data processing approach.

In this study, we performed a detailed survey of surface deformations occurred in two different regions in Italy. The first, located in Southern Italy, takes into consideration the causative fault of the 1908 Messina earthquake (Mw 7.1), that is an east-dipping normal-oblique fault lying under water along the Straits of Messina. The second site is the L'Aquila area (Central Italy), where a Mw 6.3 earthquake occurred on 6th, April 2009. The subsequent studies demonstrated that the best-fit solution for the main shock, retrieved by DInSAR data, is represented by a normal fault -16 km long and -12 km wide, with a small right-lateral component, dipping 47°SW with a maximum slip of -90 cm (Atzori et al., 2009) [1]. This study is completely carried out within the SiGRiS project, funded by the Italian Space Agency (ASI).

This letter compares the coseismic deformation maps obtained from different synthetic aperture radar (SAR) sensors using the well-known differential SAR interferometry technique. In particular, four deformation maps have been obtained from X-, C-, and L-band SAR sensors onboard COSMO-SkyMed, Envisat, and ALOS satellite missions correspondingly. The test case is the April 6,2009, earthquake (Mw= 6.3). This seismic event struck a densely populated region of the Apennines and was felt all over Central Italy. The SAR data set is rather inhomogeneous, since it includes interferograms with three different wavelengths, four acquisition geometries, different spatial resolutions, variable temporal and spatial baselines, and differently emphasized signal noise. However, we find that the detected displacements are highly comparable. The outcome of this work is that, even though such differences have an impact on the properties of the interferograms, the displacements can be measured with an overall discrepancy of about half the value of the shortest wavelength (COSMO-SkyMed) data set.

A destructive (Mw 7.9) earthquake affected the Sichuan province (China) on May 12, 2008. The seismic event ruptured approximately 270 km of the Yingxiu-Beichuan fault and about 70 km of the Guanxian-Anxian fault. Surface effects were suffered over a wide epicentral area (about 300 km E-W and 250 km N-S). We apply the differential synthetic aperture radar interferometry (DInSAR) technique to detect and measure the surface displacement field, using a set of ALOS-PALSAR L-band SAR images. We combine an unprecedented high number of data (25 frames from six adjacent tracks) to encompass the entire area which has coseismically displaced. The resulting mosaic of differential interferograms covers an overall area of about 340 km E-W and 240 km N-S. We investigate the source of the Sichuan earthquake by modeling the DInSAR data. The geometry and position of the fault parameters are inferred by a nonlinear inversion, followed by a linear inversion to retrieve the relative slip distribution. Our results show two different source mechanisms for the 145-long Yingxiu-Beichuan fault and for the 105-long Beichuan-Qingchuan fault. Both faults are characterized by slip concentrations of up to 8 m.

SIGRIS (SIstema di osservazione spaziale per la Gestione del RIschio Sismico) is a pilot project aiming to the realization of a system, based on satellite remote sensing data, for the seismic risk management. The project is funded by the Italian Space Agency (ASI). ASI is deeply interested on the development of new applications, using satellite data, dedicated to the monitoring and management of the natural hazards. SIGRIS is focused on providing the information services for mapping, monitoring, forecasting and awareness of seismic risk. The Earth Observation products are generated by using GPS data, optical and SAR (Synthetic Aperture Radar) images. This project deals with the data exploitation of the new Italian Earth Observation mission: COSMO-SkyMed, a constellation of four satellites equipped with an X-band high resolution SAR.