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After the collapse of the Genoa Bridge in August 2018, a renewed interest in permanent monitoring of the structural behavior of civil infrastructures [2] was observed. Such monitoring has to encompass the need to survey a very large number of structures that reach critical age but also new structures. In addition, recent technological advances have helped to make the installation and operation of continuous monitoring systems more practical and economical. In parallel, monitoring approaches based on the use of data acquired by satellite Synthetic Aperture Radar (SAR) may complete and enlarge the observation scale of such ground based monitoring systems, to enhance Structural Health Monitoring (SHM) performances.Monitoring of civil structures is frequently based on vibration analysis. Anyway, one limitation to the use of SHM algorithms based on modal parameter analysis is its sensitivity to environmental effects and not to damage. Among them, the subsidence around and at structure’s foundation level is a factor that has a great influence on natural frequencies.In this study, we address quasi-periodic monitoring and subsidence characterization using surface deformation measurements achieved through the Differential Interferometric SAR (DInSAR) technology [1]. Peculiarities of DInSAR have to be taken into account with reference to the application to structures monitoring:Robustness of estimated ground deformation obtained throught the combination of the Line-of-sight (LOS) deformation measurements carried out by the processing of complementary ascending and descending orbits data, for which the measurements points and date of acquisition could be different; Sparse, or absence of, measurements points on some areas induced by strong decorrelation phenomena; Limited range of the actual structure deformation that could reach the accuracy of the DInSAR technology. Bibliographic study showed that it could be difficult to exploit the DInSAR data directly for the SHM because of the problems mentioned above. The proposed procedure aims at reconstructing the deformations over an area of interest using a regularly spaced grid whose deformations would be interpolated on the available sparse measurements dataset. The interpolation is carried out on each orbit trajectory and for each acquisition date. This allows both to:Estimate measurements point on the same, possibly regular, grid for different orbits; Estimate deformation in areas lacking of measurement points; Inspired from research works of Chen et al. [3] we implemented and studied a neural network (NN) kriging based interpolation (introducing the spatial dimension inside the NN). It allows the modelisation of the points correlation (variograms) directly from the data instead of predefined functions.An overview of the studied method and developed software applied on 2 use-cases will be presented and analysed. Perspectives towards improvements of such approach will be also discussed.References[1] Antonio Pepe and Fabiana Calò. “A Review of Interferometric Synthetic Aperture RADAR (InSAR) Multi-Track Approaches for the Retrieval of Earth’s Surface Displacements”. In: Applied Sciences 7.12 (2017). doi: 10.3390/app7121264. [2] Riccardo Lanari et al. “Comment on “Pre-Collapse Space Geodetic Observations of Critical Infrastructure: The Morandi Bridge, Genoa, Italy” by Milillo et al. (2019)”. In: Remote Sensing 12.24 (2020). doi:10.3390/rs12244011.[3] Wanfang Chen et al. “DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction”. In: arXiv:2007.11972 (May 23, 2022).

Deep-seated Gravitational Slope Deformations (DsGSDs) are widespread phenomena across alpine arch. Despite the slow evolution, long-lasting deformation trend of these huge phenomena can represent a relevant geo-hazard, variably affecting human settlements and infrastructures. Given the complexity and spatial heterogeneity of these phenomena, DsGSDs behavior can feature distinct deformation sectors, highlighted by distinctive morpho-structural lineaments. To assess the internal variability in terms of kinematics, deformation trends and style of activity of a deep-seated phenomenon, a local scale analysis is needed. Notoriously, spaceborne radar interferometry have proven to be suitable to characterize ground deformation displacement of very-slow phenomena as DsGSDs, although DInSAR techniques application remain challenging, especially in mountain areas due to complex topography, abundant vegetation and snow cover. In this study, a methodology for the characterization of DsGSDs, exploiting Sentinel-1 dataset on both ascending and descending orbits, is proposed. The Sentinel-1 images are processed with the multi-resolution Component extrAction and sElection SAR- Detector (CAESAR -D), which allows increasing the monitored area density via a spatially variable multilook. Subsequently, operating in a GIS environment, a post-processing and a dedicated analysis of the obtained measured points is implemented. Morpho-structural domains were mainly defined on the basis of geomorphological criteria, leveraging on DEM derivative products (e.g., slope, aspect and hillshade), orthophoto analysis and taking in account the information available in the Italian Landslide Inventory (IFFI). For each recognized domain, firstly, an analysis on the PSs coverage was performed in order to identify the proper distribution and density of the SAR-derived measurement points for a correct definition of the state of activity. Then, we operated filtering the available SAR datasets from possible anomalous values mainly related to the slope orientation to the satellite line of sight (LOS), in order to obtain suitable dataset for the ground deformation analysis. Finally, the filtered measured points were interpolated with the Inverse Distance Weighting (IDW) technique, with the aim of produce diverse ground deformation maps depending on the orientation of the analyzed phenomenon. The combination of ascending and descending geometries allowed to obtain east-west and vertical components of velocity. The projection on the VLOS along the slope allowed to partially reduce the limitation of the topography on SAR sensitivity. This allowed us to analyze the displacement pattern of DsGSDs in more reliable way. We tested the procedure on two variably oriented DsGSDs phenomena, located in the alpine region Aosta Valley, the Croix de Fana DsGSD, mainly north-south oriented, and the Valtournenche DsGSD, mainly east-west oriented. The variations of the kinematic behavior between the morpho-structural sectors is detected, also considering any other phenomenon as secondary landslide or talus, superimposed on the DsGSD. Overall, the implemented methodology allows to a rapid and low-cost generation of ground deformation maps able to spatially analyze and characterize the morpho-structural domains of DsGSDs, providing an effective tool suitable for the definition of DsGSDs impact on the diverse anthropic elements and a proper land use planning in mountainous territories. This research was carried out in the framework of the ASI contract n. 2021-10-U.0 CUP F65F21000630005 MEFISTO

Interferometric methods are drivers of the recent exponential growth in the use of synthetic aperture radar (SAR) for monitoring both natural and anthropogenic hazards. Since the first use of interferometric SAR (InSAR) in the late 1990s to detect deformations associated with earthquakes and volcanoes, important developments have improved sensor performance and data-processing capabilities for the extraction of information of interest in geophysical applications. Here, we describe the improvements that have enabled the 3D reconstruction and monitoring of buildings, with reference to their protection against and prevention of risks. We focus on buildings affected by systematic displacements related to natural hazards-specifically, landslides. We address the straightforward use of InSAR methods in the detection and characterization of the hazard as well as in higher-level exploitation for geotechnical and structural studies and, more generally, vulnerability analysis.

Decorrelation is a major drawback in Synthetic Aperture Radar (SAR) interferometry (InSAR) processing, causing poor density of measurement points, mainly outside of urbanized areas. SAR Tomography is one of the most suitable multi-temporal InSAR technique for built environment monitoring. Although typically capable of identifying a large number of scatterers, SAR Tomography detectors suffer the assumption of fully coherent scatterer response, which can be restrictive in real cases. In this work we address the test of a detector of partially correlated scatterers on a real COSMO-SkyMed (CSK) dataset, which was previously derived in the literature [1] as a Rao test for the single-look case and is here extended to the multi-look scenario. Experimental results are compared with those achieved by the Multi-look Generalized Likelihood Ratio Test (MGLRT). Both Partial Correlation and MGLRT have been implemented with a fixed multi-look degree.

The paper presents recent results of diagnostic and monitoring activities carried out on the Consoli Palace of Gubbio (Italy) through satellite radar interferometry and in-situ continuous measurements. The work aims to investigate the effectiveness of remote sensing technologies in the understanding of complex phenomena, such as seismic vulnerability aspects concerning crack amplitudes evolution over time and soil-structure interaction, for the conservation of Cultural Heritage (CH). These activities have been carried out within the European HERACLES project, funded in the framework of Horizon 2020 and aimed at proposing novel diagnostic monitoring solutions for enhancing heritage resilience against various types of hazards. As far as it concerns the radar interferometry analysis, two datasets from the COSMO-SkyMed satellite constellation were used, processed with the Persistent Scatterer Pair (PSP) and SAR Tomography (TomoSAR) techniques, while the on-site structural monitoring system consists of two LVDTs installed on the Consoli Palace, each of them equipped with environmental sensors, in particular with thermocouples. The comparison between the outputs of satellite radar interferometry and in-situ structural monitoring data of the two test-beds, made between July 2017 and the end of 2018, allows assessing the potential of remote sensing techniques in supporting decision-making and proactive interventions for CH conservation.

Interferometric and tomographic processing at full resolution of data acquired by very high resolution SAR systems allow providing accurate 3-D reconstruction of built environments, as well as deformation monitoring. In this framework, the detection of Persistent Scatterers (PSs) is a fundamental aspect. The exploitation of multiple observation looks (multilook), is an effective strategy which allows improving the coverage of monitored pixels in natural scenarios. In the framework of SAR tomographic processing, the Multilook Generalized Ratio Test (MGLRT) detection scheme has been proposed in literature. In this work we address the potentialities and main issues related to the exploitation of a multiresolution approach for MGLRT detection based on the identification of statistical homogeneous looks.

Approaches based on the coherent processing of Synthetic Aperture Radar (SAR) data archives acquired over long temporal intervals allows 3D reconstruction/imaging and monitoring of urban areas with very high accuracy on the velocity, e.g. sub-centimetric per year. The technology is rather mature and developed in some cases also at the level of operative services. Nevertheless research is still going on to improve the technology in terms of coverage and reliability of estimated parameters for correct localization and accurate monitoring of targets. With this regard, the application to regions characterized by a mixture of urban and rural areas is of interest. This work discusses the different techniques for filtering and selection of scattering mechanisms and for single and multi-look approaches for the multi-resolution detection of Persistent Scatterers.

The Component extrAction and sElection SAR (CAESAR) is a method for the selection and filtering of scattering mechanisms recently proposed in the multibaseline interferometric SAR framework. Its strength is related to the possibility to select and extract multiple dominant scattering mechanisms, even interfering in the same pixel, since the stage of the interferograms generation, and to carry out a decorrelation noise phase filtering. Up to now, the validation of CAESAR has been addressed in the framework of SAR Tomography for the model-based detection of Persistent Scatterers (PSs). In this paper we investigate the effectiveness related to the use of CAESAR eigen-interferograms in classical multi-baseline DInSAR processing, based on the Small BAseline Subset (SBAS) strategy, typically adopted to extract large scale distributed deformation and atmospheric phase screen. Such components are also exploited for the calibration of the full resolution data for PS or tomographic analysis. By using COSMO-SKyMed (CSK) SAR data, it is demonstrated that dominant scattering component filtering effectively improves the monitoring of distributed spatially decorrelated areas (f.i. bare soil, rocks, etc.) and allows bringing to light man-made structures with dominant backscattering characteristics embedded in highly temporally decorrelated scenario, as isolated asphalt roads and block of buildings in non-urban areas. Moreover it is shown that, thanks to the CAESAR multiple scattering components separation, the layover mitigation in low-topography eigen-interferograms relieves Phase Unwrapping (PhU) errors in urban areas due to abrupt height variations.

Protocols for structural safety assessment methods for Cultural Heritage assets affected by ground instability phenomena have still not been standardized. Accordingly, huge attention is directed towards the development of innovative and reliable approaches for the damage analysis of the Cultural Heritage assets. Within this framework, this paper deals with an integrated approach for the combination of deformation time series, derived from the Tomographic processing of X-Band Synthetic Aperture Radar (SAR) data acquired by the Italian COSMO-SkyMed satellite constellation, with ground-based measurements obtained by in-situ survey, laser scanner acquisition and structural analysis. The approach exploits satellite deformation measurements to validate the first interpretation of the structural behaviour of a construction threatened by ground instability based on visual inspection and the analysis of the crack pattern, when geotechnical studies and interpretation, as well as in-situ monitoring systems, are not available. The methodology has been tested on the St. Gerlando Cathedral, located on the westernmost and highest area of the Agrigento hill. The Cathedral is affected by complex ground instability phenomena, that have led to several and continuous cracks over centuries. The spatially dense Tomographic SAR measurements allows accessing differential displacement trends in the different sections of the Cathedral and thereby analyzing the overall kinematic behavior of such a complex and heterogeneous structure. This provides essential information for the definition of the structural models, which are fundamental to better understand the behavior and damage evolution of structures subject to ground instabilities and consequently address the most suitable restoration actions.

This work investigates the capability of Interferometric SAR (InSAR) technique to monitor the atmosphere. Changes in the Atmospheric Phase Screen (APS) derived by InSAR are strictly related to changes in the atmosphere stratification and to the 2-D distribution of the water vapor columnar content. High spatial/temporal resolution APS maps provide by a SAR geosynchronous satellite (GEO-SAR) can be assimilated into limited area models (LAMs) for a better characterization of the local scale phenomena. As the observation of GEO-SAR are taken with high incidence angles, the path delay is measured along the slant direction (STD) and thus both the observation operator and the Global Navigation Satellite System (GNSS) products used for calibrating the APS must be considered along that direction. In this work, we compare the STD predicted by the Weather Research and Forecasting Model (WRF), and retrieved by a network of GNSS stations with the APS derived from Sentinel-1.

Differential Interferometric Synthetic Aperture Radar (DInSAR) technique has revolutionizing the applications of high resolution radar imaging from the space. The class of so called Persistent Scatterers Interferometry (PSI) approaches provides the capability of very accurate localization and monitoring at high resolution of ground assets. Among them 4D (space-velocity) tomographic SAR imaging uses both the phase and the amplitude of the received signal to achieve high density of measurements especially when applied to data with metric/submetric spatial resolution acquired by the new generation very high-resolution (VHR) X-Band SAR sensors. Context information can be exploited in the so called covariance based approaches to trade off the spatial resolution and the measurement coverage. In this work we discuss the application of 4D imaging and covariance based processing to the data acquired by the X-band relevant to Cultural Heritage sites.

In the framework of the Synthetic aperture Instrument for Novel Earth Remote-sensed MetereoloGy and hydrologY (SINERGY) project, co-funded by the Italian Space Agency (ASI), a challenging task has been investigated: improving high resolution Initial Conditions (IC) of the Weather Research and Forecasting model (WRF) through the three dimensional variational assimilation (3DVAR) of InSAR (Interferometric Synthetic Aperture Radar) data. InSAR provides the phase difference of the radar electromagnetic pulse scattered by the earth surface that, in absence of surface displacement, is predominantly determined by the propagation delay through the atmosphere. The latter is a function of the atmospheric profiles and greatly affected by the total columnar quantity of the tropospheric water vapour. The evaluation of the atmospheric contribution from the interferometric products is achieved by applying the SBAS (Small Baseline Subset) technique to a series of Sentinel-1 acquisitions. To evaluate the impact of the assimilation of SAR data on the forecasted precipitation field, a geographic area without complex topography is chosen: the Po Valley, in Italy. Two main case studies are selected to perform the experiments: the first one is in the spring of 2015 and the other one in the autumn of 2016; in both cases, the interested areas are covered by the descending track 168 of Sentinel 1. Model configuration domains have been run to very high resolution (1 km). Final comparisons have been made using available data such as those derived from rain gauges, radar soundings and GNSS stations.

Differential interferometric synthetic aperture radar (SAR) has proven to be effective for accurate localization and monitoring of the displacement of ground targets. The high accuracy and spatial density of the measurements make this technique cost effective compared to the classical geodetic techniques typically used in the risk monitoring context. Ground infrastructure monitoring is typically carried out with in situ sensors. The new generation of high-resolution SAR sensors, however, allows one to acquire data sets with a spatial resolution reaching metric/submetric values. Here we investigate the application of a multi-dimensional SAR imaging technique, which is an extension of classical differential interferometric techniques, to very high resolution TerraSAR-X data in order to demonstrate the potential of this technology for monitoring of transportation infrastructures.

Interferometric and particularly tomographic processing at full resolution of data acquired by very high resolution SAR systems allows accurate 3D imaging and monitoring of buildings and infrastructures. Recently it has been shown that implementing a light data multilooking leads to a dramatical increase of the density of monitored pixels. In this work we investigate different options for performing the the multilook operation in SAR Tomography and we analyze their performances in terms of detection capabilities of single scatterers.

Atmospheric propagation delay is a key error source in DInSAR processing and represents a main limitation to the use of DInSAR in emergency conditions. Current X-Band sensors, characterized by frequent passes, are even more affected by such problems. In this work we discuss a procedure based on the use of information extracted from GPS data.

The identification of facilities in areas affected by subsidence phenomena represents a fundamental activity in processes dealing with land management. For this kind of phenomena, the analyses may be hampered by the lack of official subsidence zoning maps because of the wide extension of the affected areas. This is mainly due to the costs necessary for measurements and surveys to be carried out via conventional in situ techniques which can turn out to be unaffordable for the authorities in charge of land management. In this regard, during the last decade the use of remote sensing data, such as medium resolution synthetic aperture radar (SAR) images processed via differential interferometry algorithms (DInSAR), has proven its benefits for the detection and monitoring of facilities (i.e., buildings and infrastructures) in subsiding areas. Currently, the improved resolution and coverage of the ultimate generation SAR sensors seem very promising for consequence analyses of facilities, although displacement time series are still limited for long-term studies. In this paper, analyses of DInSAR data acquired via both medium (ERS-ENVISAT) and high (COSMO-SkyMed) resolution sensors are carried out over a densely urbanized flat area in southern Italy so as to show how the appropriate use of DInSAR data at different scales can valuably help in the detection and monitoring of damageable facilities.

In this paper a novel procedure for the filtering of interferograms based on the extension of SAR Tomography on multilook data is presented. This algorithm, named “Component extrAction and sElection SAR” (CAESAR) takes advantage of Principal Component Analysis to handle temporal and angular decorrelation effects as well as of SAR Tomography principles to solve the distributed layover at the interferogram generation stage. Results on Cosmo-Skymed real data confirm the effectiveness of the proposed procedure.

Multipass DInSAR processing is a well established technique that allows accurate 3D reconstruction and monitoring of the Earth surface. Many multipass techniques, such as the Small Baseline Subset approach, carry out a spatial multilooking of interferograms to counteract the decorrelation effects and the thermal noise and, also, to reduce computational complexity through spatial subsampling, thus enabling large scale (even full frame) analysis. Multilooking, however, degrades the spatial resolution w.r.t the original full resolution SAR product and therefore does not preserve contours of structures and in general boundaries of areas characterized by different backscattering. In this paper we propose the use of more sophisticated non-local filtering algorithms for the implementation of the interferometric multilook operation to guarantee the same noise rejection power of multilooking, while preserving high-resolution detail. Different strategies are considered and discussed for the selection of the best predictor pixels. Results on real data acquired by the ENVISAT mission demonstrate the good performance of the proposed nonlocal filtering methods.

The new generation of high resolution Synthetic Aperture Radar (SAR) sensors provides a new “light” in the imaging and monitoring of built areas and structures: Ground structures can be now monitored to an unprecedented accuracy. Particularly the use of higher frequency enhances the sensitivity of the system even to minute changes, such as thermal dilations. By extending multitemporal differential interferometry SAR processing chains, in our case based on the multidimensional imaging approach, an additional parameter related to temperature at acquisition instants can be accurately estimated. In this work we investigate the application of the multi-dimensional SAR imaging technique to very high resolution TerraSAR-X data acquired over the city of Potenza (south Italy), with a particular attention to Musmeci bridge. Results demonstrate the potential of this technology to accurately monitor even minute deformations of the bridge, such as those caused by thermal dilations.