The application of sparse synthetic aperture radar tomographic (TomoSAR) reconstruction in urban areas faces several challenges, including deficiencies related to outliers and amplitude/position biases resulting from low SNR, small baseline aperture, and an insufficient number of acquisitions.$\ell _{1}$-$\ell _{2}$norm-minimization for sparse reconstruction relies primarily on the Lagrange multiplier to promote sparsity in the solution. However, inaccurate estimation of the noise level and the Lagrange multiplier can significantly degrade reconstruction performance. To address these limitations, we propose an enhanced sparse reconstruction framework that integrates improved$\ell _{1}$-$\ell _{2}$norm minimization with refined noise estimation. We also introduce support shrinkage based on a modified singular value decomposition (M-SVD) to improve the localization of correct scatterers in elevation and reduce the outliers. We estimated the Lagrange multiplier for the shrunk system of equations, followed by a final reconstruction using$\ell _{1}$-$\ell _{2}$norm-minimization. This study provides a comprehensive evaluation of the proposed method under various parameter settings and compares its performance against conventional approaches using simulated datasets to demonstrate the effectiveness of M-SVD in accurately localizing scatterers in elevation. Moreover, a practical application of a 3-D elevation point cloud of the Mapfre Tower in Barcelona using TerraSAR-X satellite data is generated.

This work proposes a supervised classifier of ground motion phenomena using as main input the SAR Differential Interferometry (DInSAR) data contained in the European Ground Motion Service (EGMS) datasets. The classifier operates on the active deformation areas (ADAs) extracted from the EGMS data, which are categorized into three deformation classes, i.e. deep-seated gravitational slope deformation (DSGSD), landslide and subsidence. Digital Elevation Models (DEM) and Land Cover maps are used as ancillary input data, whereas landslide and subsidence inventories are employed as ground truth to form the training dataset. The implemented machine learning (ML) classifier employs the Extreme Gradient Boosting technique on a set of features extracted from the input data. Feature importance is analysed to provide an insight on the physical meaning of the implemented classification, moving towards the explainable artificial intelligence paradigm. The results show good classification performance on the test dataset. The classification reliability is evaluated on the unseen data through class probabilities.

Multi-temporal synthetic aperture radar interferometry is nowadays a well-developed remote sensing technique for monitoring Earth’s surface deformation. The European Ground Motion Service (EGMS) is an important component of ground deformation monitoring in Europe, which offers consistent, accurate, and annually updated information about ground displacements related to both natural and anthropogenic phenomena. The policy of providing EGMS products free of charge enables us to leverage the data and develop tools to identify buildings and urban structures that are vulnerable to damage due to differential movement. The tool described in this paper facilitates the generation of a differential deformation map for individual buildings by computing the spatial gradient of deformation for each building and then classifying them into distinct classes according to their gradient values. To demonstrate the reliability and trustworthiness of identified buildings, an uncertainty analysis was performed. Its output includes the relationship between the ratio of average-to-standard deviation of gradient and the density of points in each building. The proposed approach was tested with EGMS data over the area of Catalunya (Spain) from 2015 to 2021. A total of 308 buildings were identified as vulnerable to damage, with around half of them classified as "Low" gradient intensity. This map can serve as the initial step required for an in-depth analysis and risk assessment, aiming to mitigate risks and maintain the stability and safety of buildings.

This work addresses the automatic extraction of active deformation areas (ADAs) using a pan European ground deformation dataset, provided by the European Ground Motion Service. The ADA extraction routine is based on the ADA Finder tool, which selects the persistent scatterers that are likely to belong to a surface affected by a ground deformation phenomenon. The result consists of two European ADA maps, associated with the Sentinel-1 ascending and descending trajectories. A preliminary validation of the European ADA maps is addressed by analysing the detected ADAs in the territory of Valle d'Aosta region (Italy), that is affected by the presence of landslides and deep-seated gravitational slope deformations, showing a limited number of false positives.

This letter aims at investigating the potential of high-resolution (up to$0.7\times0.5\,\,\text{m}^{2}$) synthetic aperture radar (SAR) images in generating digital elevation models (DEMs) using the radargrammetry technique. In this work, we process two SAR images recorded by the Capella Space X-band satellite-borne radar sensor on two consecutive days, October 2 and 3, 2021, over La Palma (Canary Islands, Spain) during the Cumbre Vieja volcanic eruption. We adopt an iterative point-aggregation algorithm to identify matching pixels between the two images; then, the height estimation is performed using a distance minimization routine over the previously identified pairs of matching points. The resultant radargrammetric DEM is validated against a lidar-based DEM for various land cover (LC) classes, showing a good agreement in the areas less affected by lava flow. An estimation of the lava thickness is performed, yielding profiles of the cone area, which are compared to the photogrammetry estimates obtained from the Pléiades mission data.

The Copernicus European Ground Motion Service (EGMS) provides consistent, regular, standardised, harmonised and reliable information regarding natural and anthropogenic ground motion phenomena over the Copernicus Participating States and across national borders, with millimetre accuracy. The EGMS is based on the multitemporal interferometric analysis of Sentinel-l radar images at full resolution. Global navigation satellite systems (GNSS) data are used to calibrate the interferometric measurements. EGMS provides an unprecedent opportunity to study geohazards and human-induced deformation over Europe, such as slow-moving landslides, natural subsidence or due to groundwater exploitation or underground mining activities, volcanic unrests and many other phenomena. This paper offers a first look at the products distributed by EGMS through relevant case studies in different environmental contexts of Europe.

Generation of Digital Elevation Models (DEMs) using Synthetic Aperture Radar (SAR) data is a valid flexible alternative to other surveying techniques. In this work we adopt radargrammetry on two SAR images recorded by the Capella Space X-band spaceborne sensor on two consecutive days over La Palma Island (Canary Islands, Spain) during the Cumbre Vieja volcanic eruption, with the aim of investigating the potential of these high-resolution (up to 0.7 by 0.5 m2) SAR images in generating precise DEMs. The adopted method employs a multilook-based spatial filter followed by an iterative region-growing algorithm to identify matching pixels between the two images. The resultant radargrammetric DEM is compared with a Lidar-based DEM, showing a good agreement in the areas less affected by lava flow.

This work addresses the problem of estimating and filtering the Atmospheric Phase Screen from a stack of image phases, extracted from a sequence of SAR images using the PSInSAR approach. Leveraging the assumption that the atmospheric disturbance is a signal with a high spatial correlation and low temporal correlation, a Nonequispaced FFT is used to estimate the spatial spectrum of the input data, which are distributed spatially on a non-uniform grid, then perform a lowpass filter, followed by a highpass temporal filter. The obtained APS estimate is then removed from the input data. The performance of the proposed method is evaluated over Sentinel-1 SAR data to study mining-induced terrain deformations in the Polkovice area, Poland.

Understanding the effects of Earth's surface topography in Global Navigation Satellite Systems Reflectometry (GNSS-R) spaceborne data is essential to correct experimental observations so as to achieve accurate Soil Moisture Content (SMC) determination and biomass monitoring. A comprehensive set of observables obtained from Delay Doppler Maps (DDMs) generated on-board Cyclone Global Navigation Satellite Systems (CyGNSS) are evaluated as a function of several topographic parameters derived from a Digital Elevation Model (DEM). Terrain Ruggedness Index (TRI) and profile curvature have a moderate-to-strong impact on CyGNSS-derived trailing edge (TE) and reflectivity Γ for low elevation angles θe~ [20, 30]° (r_tri_Γ ~ -0.39, r_tri_TE ~ 0.39, r_curv_Γ ~ 0.41, r_curv_TE ~ -0.38). On the other hand, local slopes have an influence on Γ and TE for a constant curvature level, while both observables are independent of the slopes for a constant TRI.

A performance assessment of the Cyclone Global Navigation Satellite System (CyGNSS) mission for biomass studies is presented in this paper over Congo and Amazon tropical rainforests. The functional correlation between CyGNSS-derived trailing edge TE and Avitabile et. al. Above Ground Biomass (AGB) pan-tropical data is evaluated using ICESat/GLAS-derived Canopy Height (CH), SMAP-derived Vegetation Optical Depth (VOD) and Polarization Index (PI). The main objective is to investigate the sensitivity of CyGNSS to biomass over dense forest canopies. The potential advantage of CyGNSS as compared to classical monostatic radar missions could rely on the increasing signal attenuation by the upwelling vegetation cover that reduces the coherent scattering component σ coh,0 . This term can only be collected in a bistatic radar geometry. Ignoring measurement noise, preliminary results show that the use of TE allows to estimate AGB up to ~400 ton/ha and ~250 ton/ha over Congo and Amazon rainforests at low elevation angles θ e ~ [20, 40] °. The analysis using the SMAP-derived microwave vegetation parameters shows that: a) VOD performs well even over rainforests, and b) PI could depend on the CH levels.

Persistent Scatterer Interferometry (PSI) data, deriving from the processing of SAR images acquired by high-resolution sensors such as TerraSAR-X, provide accurate measurements of displacements affecting structures (e.g., buildings) and linear infrastructure networks (e.g., roads, bridges, embankments, and pipelines). Such widespread displacements, when available on buildings on unstable slopes, offer new perspectives for their integration in procedures pursuing the analysis and the prediction of the physical vulnerability of exposed buildings. In this letter, both deterministic and probabilistic cause (differential settlements)-effects (damage) relationships are generated by using PSI-derived building settlements and the results of building damage surveys. The procedure is applied to El Papiol town (Spain), whose urban area has been suffering diffuse damage of different severity to buildings and roads due to extremely slow-moving landslide phenomena.

Earth's surface bistatic reflectivity ΓLHCP,CyGNSS profiles are obtained using Global Navigation Satellite Systems Reflectometry (GNSS-R) products from NASA's Cyclone Global Navigation Satellite Systems (CyGNSS). The focus of this study is to evaluate the influence of the GNSS satellites' elevation angle θe on ΓLHCP,CyGNSS. Specific target areas with differentiated scattering media are selected to characterize these profiles as a function of the land-cover type and the wind-speed regimes for ocean-surfaces. In the former case, the main interest is to further understand the function ΓLHCP,CyGNSS=f(θe,...) in preparation of the potential application of the so-called Tau-Omega model to GNSS-R. In the latter case, the objective is to analyze the impact of the coherent scattering component in GNSS-R observables. Preliminary results show ΓLHCP,CyGNSS increases ~ 3.7 dB over land and ~ 5.3 dB ocean, as θe moves from~ [70], [90]° to ~ [20], [40]°.

This work presents an assessment on the correlation between CyGNSS-derived Global Navigation Satellite Systems Reflectometry (GNSS-R) bistatic reflectivity Γrland SMAP-derived brightness temperature TB, over land surfaces. This parametric-study is performed as a function of Soil Moisture Content (SMC), and vegetation opacity τ. Several target areas are selected to evaluate potential differentiated geophysical effects on “active” (as many transmitters as navigation satellites are in view), and passive approaches. Although microwave radiometry has potentially a better sensitivity to SMC, the spatial resolution is poor ~ 40 km. On the other hand, GNSS-R bistatic coherent radar footprint is limited by half of the first Fresnel zone which provides about ~ 150 m of spatial resolution (depending on the geometry). The synergetic combination of both techniques could provide advantages with respect to active monostatic Synthetic Aperture Radar (SAR).

In this paper, an approach to Persistent Scatterer Interferometry (PSI) is used to derive deformation measurements over the Catalonia region (Northern Spain). A set of tools to control the quality of the 2+1d phase unwrapping, one of the key steps of the proposed procedure, are described and applied over a set of Sentinel-1A (S-1A) images. The results, derived using 64 S1-A images comprising the period from March 2015 to May 2017, are analyzed in the last section of the paper. Finally, the deformation velocity map and the time series are described, in particular over the urban areas, where the proposed approach yields the best results.

In the last decade, Persistent Scatterer Interferometry (PSI) and SAR tomography (TomoSAR) have been used for reconstructing the elevation profile of a scene, starting from a set of co-registered Synthetic Aperture Radar (SAR) images. The possible advantage of TomoSAR over classical interferometric methods consists in the potential capability of improving the detection of single scatterers presenting stable proprieties over time (Persistent Scatterers or PS), as well as to enable the detection of multiple scatterers interfering within the same range-azimuth resolution cell. In urban environment, when only single dominant scatterers are present in each range-azimuth resolution cell, both methods can be exploited to estimate the altitude, deformation rate and thermal expansion of a subset of reliable scatterers, which are selected on the basis of different criteria. This paper is focused on a performance analysis of the two class of methods, using the results obtained in urban environment on simulated and real TerraSAR-X data. A concise description of both techniques, along with a discussion on their potential capabilities in selecting the most reliable scatterers, is given.

This paper describes some of the key features of the Persistent Scatterer Interferometry chain of the Geomatics (PSIG) Division of CTTC. The paper firstly provides an overview of the entire PSI chain. It then focuses on the first part of the chain, which provides the input data for the estimation of the Atmospheric Phase Screen (APS). In this part, the so-called Cousin Persistent Scatterers (CPSs) are sought, which are Persistent Scatterers (PSs) characterized by a moderate spatial phase variation that ensures a correct phase unwrapping. The main output of this part of the chain is a set of correctly unwrapped and temporally ordered phases, which are computed on CPSs that cover homogeneously the area of interest. In order to do so a procedure to check the consistency of phase unwrapping is used. The paper describes the used algorithms and illustrates their performances using a set of TerraSAR-X StripMap images over the metropolitan area of Barcelona.

The monitoring of Cultural Heritages is an operational issue that requires a multidisciplinary approach to provide their dynamic and sustainable surveying in response to climate changes and natural events. Within such a framework, an integrated system of proximal remotely-sensed tools is investigated for Cultural Heritage monitoring purposes in a seismic area. It consists of a Ground-Based Synthetic Aperture Radar (GBSAR), a GB Real Aperture Radar (RAR) and a Terrestrial Laser Scanner (TLS). Preliminary results, gathered over the Sant'Agostino Church in Cosenza city, allow demonstrating the benefits of the proposed approach for Cultural Heritages monitoring.

Deformation monitoring using ground-based synthetic aperture radar (GB-SAR) data usually exploits the interferometric phases. In this letter, a new noninterferometric procedure is proposed, which exploits the geometric content of GB-SAR amplitude imagery and estimates deformation through image matching. This letter describes, step by step, this procedure. In order to achieve acceptable deformation measurement performances, the technique needs special targets, which have to guarantee a good image matching quality. If the available natural targets are insufficient, artificial corner reflectors are required. The new approach overcomes some of the main limitations of GB-SAR interferometry; it yields aliasing-free deformation estimates, is insensitive to atmospheric effects, and provides 2-D displacement measurements while interferometry only has a mono-dimensional measurement capability. Several experiments focusing on the performances of the new procedure are described. The procedure is validated using different scenarios. On a real-size landslide scenario, a mean absolute error over 12 corner reflectors of 0.59 cm is achieved, i.e., 1/85th of the pixel size. These encouraging results can be of interest for several deformation monitoring applications.

This letter focuses on the thermal expansion component of persistent scatterer (PS) interferometry (PSI), which is a result of temperature differences in the imaged area between synthetic aperture radar (SAR) acquisitions. This letter is based on very high resolution X-band StripMap SAR data captured by the TerraSAR-X spaceborne sensor. The X-band SAR interferometric phases are highly influenced by the thermal dilation of the imaged objects. This phenomenon can have a strong impact on the PSI products, particularly on the deformation velocity maps, if not properly handled during the PSI analysis. In this letter, we propose a strategy to deal with the thermal dilation phase component, which involves further developing the standard two-parameter PSI model (deformation velocity and residual topographic error) with a third unknown parameter called the thermal dilation parameter, which is estimated for each PS. The map obtained from plotting this parameter for all PSs of a given area is hereafter called thermal map. This letter describes the proposed model and outlines the issue of parameter estimability. In addition, the potential of exploiting the thermal maps is analyzed by illustrating two examples of the Barcelona (Spain) metropolitan area. Thermal maps provide two types of information: The first one is the coefficient of thermal expansion of the observed objects, while the second one, which is related to the pattern of the thermal dilation parameter, gives information about the static structure of these objects. Two important aspects that influence the exploitation of thermal maps are discussed in the last section of this letter: the line-of-sight nature of the derived estimates and the achievable precision in the estimation of the coefficient of thermal expansion.

The DInSAR technique enables to determine with precision the surface displacements, using a combination of multiple interferograms. The DInSAR processing steps generate different kinds of errors, which propagate in the entire chain. This work is focused on a particular type of error generated during the DInSAR processing: the unwrapping related errors. The errors generated during the unwrapping process and the use of a procedure to automatically detect and correct them are presented in this work. By an iterative process and exploiting the SVD least squares method for outliers rejection, this procedure determines the phases values associated with each SAR image, starting from a stack of interferograms. It works on previously selected pixels and provides good results with high observation redundancy. The effectiveness of the procedure is illustrated by using ERS SAR data acquired over Barcelona (Spain).

The paper describes the main characteristics of three procedures to perform subsidence monitoring using SAR interferometry, which are suitable to support quantitative applications, like those related to risk assessment and public safety. The first procedure can be effective even with a single interferogram, while the other ones are suitable to the configurations based on multiple interferograms.

A novel procedure to analyse the uncertainty associated to the output of GIS-based models is presented. The procedure can handle models of any degree of complexity that accept any kind of input data. Two important aspects of spatial modelling are addressed: the propagation of uncertainty from model inputs and model parameters up to the model output (uncertainty analysis); and the assessment of the relative importance of the sources of uncertainty in the output uncertainty (sensitivity analysis). Two main applications are proposed. The procedure allows implementation of a GIS-based model whose output can reliably support the decision process with an optimized allocation of resources for spatial data acquisition. This is possible in low cost strategy, based on numerical simulations on a small prototype of the GIS-based model. Furthermore, the procedure provides an effective model building tool to choose, from a group of alternative models, the best one in terms of cost-benefit analysis. A comprehensive case study is described. It concerns the implementation of a new GIS-based hydrologic model, whose goal is providing near real-time flood forecasting.