Monitoring displacements with interferometric synthetic aperture radar involves, as final processing stage, the detection of persistent/distributed scatterers. Filtering and multilook is adopted to improve the detection performances in non-urbanized areas, where dominant point scattering mechanisms are less frequent. SqueeSAR and CAESAR based detectors were already compared in [1] under the hypothesis of weak and fully correlated scattering. In this work we extend the comparison to account for the presence of scattering decorrelation. The comparison is carried out by analyzing simulated data as well as data acquired by the COSMO-SkyMed constellation. In both cases the detection based on CAESAR outperforms the one based on SqueeSAR.

In the last two decades, satellite Multi-Temporal Differential Interferometric SAR (DInSAR) techniques have become consolidated tools for studying slow-moving landslides. Moreover, the availability of sensors using different band frequencies and the development of advanced processing algorithms have constantly improved. In this work we discuss the first results of an experimental analysis carried out on multi-temporal multi-baseline L-Band data acquired by the newly launched SAOCOM satellites in the framework of the MEFISTO project founded by the Italian Space Agency (ASI), one of the main aims of which was to test the potentiality of multi-frequency (X, C and L bands) DInSAR data processed with different methodologies applied to a multi-scale slow-landslide analysis.

Among the several applications of multipass InSAR, monitoring of landslides represents one of the most challenging case because of the topographic characteristics, the heterogeneous displacement rates and the frequent presence of vegetation. In this study, we consider the use of multi-frequency InSAR data for the application to case studies located in the North and South Italy.

Basal and superficial displacements of two landslides in overconsolidated clayey soils are being monitored by inclinometers and GPS since 2005, and in some parts of the slope since the 1990s. The mostly North-South (N-S) orientation of the landslide displacements makes monitoring by satellite interferometry a challenging problem. To solve it, COSMO-SkyMed Differential Interferometric Synthetic Aperture Radar (DInSAR) data were analyzed at the scale for which inclinometers and GPS provide clear indication of displacement directions, thus allowing a confident use also of ERS and Envisat data. The kinematic history of the last 20 years of the urbanized area of the landslides was thus reconstructed even where ground-based displacement series were available over short periods or not available at all. The effectiveness of the remedial measures adopted in the area on displacement rates was also evaluated.

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.

Persistent scatterers (PS) interferometry tools are extensively used for the monitoring of slow, long-term ground deformation. High spatial resolution is typically required in urban areas to cope with the variability of the signal, whereas in rural regions, multilook shall be implemented to improve the coverage of monitored areas. Along this line, SqueeSAR and later Component extrAction and sElection SAR (CAESAR) were introduced for the monitoring of both persistent and (decorrelating) distributed scatterers (DS). Multilook generalized likelihood ratio test (MGLRT) is a detector derived in the context of tomographic SAR processing that has been investigated for a fixed multilook degree. In this work, we address MGLRT and CAESAR in the multiresolution context characterized by a spatially variable multilook degree. We compare the two schemes for the multiresolution selection of PS and DS, highlighting the pros and cons of each scheme, particularly the peculiarities of CAESAR that have important implications at the implementation stage. A performance analysis of both detectors in case of model mismatch is also addressed. Experiments carried out with data acquired by the COSMO-SkyMed constellation support both the theoretical argumentation and the results achieved by resorting to Monte Carlo simulations.

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.

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.

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.

Synthetic aperture radar (SAR) tomography has been strongly developed in the last years for the analysis at fine scale of data acquired by high-resolution interferometric SAR sensors as a technique alternative to classical persistent scatterer interferometry and able to resolve also multiple scatterers. SqueeSAR is a recently proposed solution which, in the context of SAR interferometry at the coarse scale analysis stage, allows taking advantage of the multilook operation to filter interferometic stacks by extracting, pixel by pixel, equivalent scattering mechanisms from the set of all available interferometric measurement collected in the data covariance matrix. In this paper, we investigate the possibilities to extend SqueeSAR by allowing the identification of multiple scattering mechanisms from the analysis of the covariance matrix. In particular, we present a new approach, named “Component extrAction and sElection SAR” algorithm, that allows taking advantage of the principal component analysis to filter interferograms relevant to the decorrelating scatterer, i.e., scatterers that may exhibit coherence losses depending on the spatial and temporal baseline distributions, and to detect and separate scattering mechanisms possibly interfering in the same pixel due to layover directly at the interferogram generation stage. The proposed module allows providing options useful for classical interferometric processing to monitor ground deformations at lower resolution (coarse scale), as well as for possibly aiding the data calibration preliminary for the subsequent full-resolution interferometric/tomographic (fine scale) analysis. Results achieved by processing high-resolution Cosmo-SkyMed data, characterized by the favorable features of a large baseline span, are presented to explain the advantages and validate this new interferometric processing solution.

In the last years spaceborne Synthetic Aperture Radar (SAR) Tomography has been successfully exploited for the analysis of complex scenarios, such as urban areas and infrastructures. In this work a novel method is investigated to achieve improved multidimensional tomographic reconstructions of built structures at a fine scale: it exploits a preliminary data filtering stage carried out via the Component extrAction and sElection SAR (CAESAR) algorithm, based on the application of the Principal Component Analysis (PCA) with a reduced multilooking degree. Experimental results obtained by applying this technology to COSMO-SKYMED data are shown.

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.

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.

The new generation of synthetic aperture radar (SAR) sensors is providing images with very high spatial resolution, improved up to the meter scale. Such a resolution increase allows more accurate monitoring capabilities by means of interferometric approaches. The use of higher frequency enhances the sensitivity of the system even to minute changes, such as thermal dilations. This phenomenon has an impact on the interferometric products, particularly on the deformation velocity maps, if not properly handled. Man-made structures, such as steel core bridges and specific buildings, may be very sensible to thermal dilation effects. By extending the multitemporal differential interferometry SAR processing chains, in our case based on the multidimensional imaging (MDI) approach, an additional parameter related to temperature differences at acquisition instants, the thermal coefficient, can be accurately estimated. This parameter provides interesting perspectives in application to infrastructure monitoring: It brings information about the thermal behavior of the imaged objects. In this letter, we investigate the thermal response of the Musmeci bridge (Potenza, Italy), by experimenting the extended MDI approach on a real TerraSAR-X data set. Results highlight the possibility of such a technique to obtain measurements of the motion that is highly correlated with temperature, thus providing useful information about the static structure of bridges.

We present an adaptive filtering algorithm for accurate estimation of differential interferometric phase and coherence, in order to better support the SBAS approach. The typical method to enhance interferograms is a simple boxcar multilooking, that improves the signal-to-noise ratio (SNR) at the expense of the spatial resolution. The presented technique is based on an adaptive space filter that identifies and averages statistically homogeneous pixels in a given neighbourhood. It also consists of a phase filtering operation in the time domain via the temporal multilink for recovering the consistency of the interferometric phase (phase triangulation). Results on real Cosmo-SkyMed data, acquired over the city of Naples, are shown in order to demonstrate the effectiveness of the presented technique.