Differential Synthetic Aperture Radar (SAR) Interferometry Research Articles

Transport Infrastructure SHM Using Integrated SAR Data and On-Site Vibrational Acquisitions: “Ponte Della Musica–Armando Trovajoli” Case Study

This work presents the first results obtained by applying in situ and remote-sensing methodologies to monitor the Ponte della Musica-Armando Trovajoli located in Rome, within the activities of the WP6 “Structural Health Monitoring and Satellite Data” 2019-21 Reluis Project. In particular, the use of remote-sensing Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) measurements provided a spatial map of the displacement of the investigated infrastructure and the corresponding time-series, with the aim of monitoring deformation phenomena, focusing on the local scale analysis, which produces suitable results for urban monitoring and damage assessment. The DInSAR results have been integrated with the identification of the dynamic characteristics of the bridge, performed through an experimental campaign of ambient vibration measurements carried out in October 2020 and with the local-scale definition of the engineering geological setting of the foundation soil. The subsoil of the bridge is constituted by more than 50 m of recent alluvial deposits resting on Pliocene stiff clay acting as a geological bedrock. A substantially stable behavior of the bridge structural elements has been observed based on the analysis of both satellite and velocimetric data. This case represents a good example about how the integration of in situ sensors with remotely sensed data and the exploitation of a detailed knowledge regarding the on-site conditions represent a key factor for a sustainable structural and infrastructural monitoring and can support the planning both of maintenance and safety management.

Real-World DEM Super-Resolution Based on Generative Adversarial Networks for Improving InSAR Topographic Phase Simulation

Topographic phase simulation is important for deformation estimation in differential synthetic aperture radar (SAR) interferometry (DInSAR). The most commonly used 30-m resolution SRTM digital elevation model (DEM) is usually required to be resampled due to its relatively low resolution (LR) comparing to the high resolution (HR) SAR images. Although the WorldDEM^TM with a 12-m resolution achieves global coverage, it is not available freely. Consequently, it is useful to evaluate the practicability of the super-resolution (SR) from LR SRTM DEMs to HR WorldDEM^TM ones, which has not been investigated. Most existing DEM SR models are trained with synthetic datasets in which the LR DEMs are downsampled from their HR counterparts. However, these models become less effective when applied to real-world scenarios due to the domain gap between the synthetic and real LR DEMs. In this paper, we constructed a real-world DEM SR dataset where the LR and HR DEMs were collected from SRTM and WorldDEM^TM, respectively. An ESRGAN model was adapted to train on the dataset. Considering that the real LR-HR pairs may suffer from misalignment, we introduced the perceptual loss for better optimizing the model. Moreover, a logarithmic normalization was proposed to compress the wide elevation range and adjust the uneven distribution. We also pretrained the model using natural images since collecting sufficient HR DEMs is costly. Experiments demonstrate that the proposed method achieves near 0.69dB improvement of peak signal-to-noise ratio (PSNR). In addition, our method is also validated to improve the topographic phase simulation by 23.42% of MSE.

Differential synthetic aperture radar interferometric phase map despeckling in discrete Riesz wavelets domain

Phase extraction in differential synthetic aperture radar (SAR) interferometry (DInSAR) is an important tool used for detecting subcentimeter-level change in ground deformation. The evaluated phase map processing is conducted via two important and successive steps: phase denoising and phase unwrapping. We attack the first step and propose the performance of discrete Riesz wavelets transform to reduce the residual speckle noise from the generated DinSAR phase map. The performance of the proposed method is appraised using three important criteria such as peak-to-signal-noise ratio (PSNR), the quality index Q, and the edge preservation index. The obtained metric values reveal that this technique can improve the PSNR and Q in comparison with other famous techniques. Finally, we apply the algorithm to denoise a real DinSAR phase map generated with sentinel application platform software using three SAR data of the Napa city in California.

The Parallel SBAS Approach for Sentinel-1 Interferometric Wide Swath Deformation Time-Series Generation: Algorithm Description and Products Quality Assessment

We present an advanced differential synthetic aperture radar (SAR) interferometry (DInSAR) processing chain, based on the Parallel Small BAseline Subset (P-SBAS) technique, for the efficient generation of deformation time series from Sentinel-1 (S-1) interferometric wide (IW) swath SAR data sets. We first discuss an effective solution for the generation of high-quality interferograms, which properly accounts for the peculiarities of the terrain observation with progressive scans (TOPS) acquisition mode used to collect S-1 IW SAR data. These data characteristics are also properly accounted within the developed processing chain, taking full advantage from the burst partitioning. Indeed, such data structure represents a key element in the proposed P-SBAS implementation of the S-1 IW processing chain, whose migration into a cloud computing (CC) environment is also envisaged. An extensive experimental analysis, which allows us to assess the quality of the obtained interferometric products, is presented. To do this, we apply the developed S-1 IW P-SBAS processing chain to the overall archive acquired from descending orbits during the March 2015-April 2017 time span over the whole Italian territory, consisting in 2740 S-1 slices. In particular, the quality of the final results is assessed through a large-scale comparison with the GPS measurements relevant to nearly 500 stations. The mean standard deviation value of the differences between the DInSAR and the GPS time series (projected in the radar line of sight) is less than 0.5 cm, thus confirming the effectiveness of the implemented solution. Finally, a discussion about the performance achieved by migrating the developed processing chain within the Amazon Web Services CC environment is addressed, highlighting that a two-year data set relevant to a standard S-1 IW slice can be reliably processed in about 30 h.The presented results demonstrate the capability of the implemented P-SBAS approach to efficiently and effectively process large S-1 IW data sets relevant to extended portions of the earth surface, paving the way to the systematic generation of advanced DInSAR products to monitor ground displacements at a very wide spatial scale.

Coseismic Ground Deformation Reproduced through Numerical Modeling: A Parameter Sensitivity Analysis

Coseismic ground displacements detected through remote sensing surveys are often used to invert the coseismic slip distribution on geologically reliable fault planes. We analyze a well-known case study (2009 L’Aquila earthquake) to investigate how three-dimensional (3D) slip configuration affects coseismic ground surface deformation. Different coseismic slip surface configurations reconstructed using aftershocks distribution and coseismic cracks, were tested using 3D boundary element method numerical models. The models include two with slip patches that reach the surface and three models of blind normal-slip surfaces with different configurations of slip along shallowly-dipping secondary faults. We test the sensitivity of surface deformation to variations in stress drop and rock stiffness. We compare numerical models’ results with line of sight (LOS) surface deformation detected from differential SAR (Synthetic Aperture Radar) interferometry (DInSAR). The variations in fault configuration, rock stiffness and stress drop associated with the earthquake considerably impact the pattern of surface subsidence. In particular, the models with a coseismic slip patch that does not reach the surface have a better match to the line of sight coseismic surface deformation, as well as better match to the aftershock pattern, than models with rupture that reaches the surface. The coseismic slip along shallowly dipping secondary faults seems to provide a minor contribution toward surface deformation.

Estimation of Water Level Changes of Large-Scale Amazon Wetlands Using ALOS2 ScanSAR Differential Interferometry

Differential synthetic aperture radar (SAR) interferometry (DInSAR) has been successfully used to estimate water level changes (∂h/∂t) over wetlands and floodplains. Specifically, amongst ALOS PALSAR datasets, the fine-beam stripmap mode has been mostly implemented to estimate ∂h/∂t due to its availability of multitemporal images. However, the fine-beam observation mode provides limited swath coverage to study large floodplains and wetlands, such as the Amazon floodplains. Therefore, for the first time, this paper demonstrates that ALOS2 ScanSAR data can be used to estimate the large-scale ∂h/∂t in Amazon floodplains. The basic procedures and challenges of DInSAR processing with ALOS2 ScanSAR data are addressed and final ∂h/∂t maps are generated based on the Satellite with ARgos and ALtiKa (SARAL) altimetry’s reference data. This study reveals that the local ∂h/∂t patterns of Amazon floodplains are spatially complex with highly interconnected floodplain channels, but the large-scale (with 350 km swath) ∂h/∂t patterns are simply characterized by river water flow directions.

Airborne DInSAR Results Using Time-Domain Backprojection Algorithm: A Case Study Over the Slumgullion Landslide in Colorado With Validation Using Spaceborne SAR, Airborne LiDAR, and Ground-Based Observations

The major impediment to accurate airborne repeat-pass differential synthetic aperture radar (SAR) interferometry (DInSAR) is compensating for aircraft motion caused by air turbulence. Various motion compensation (MoCo) procedures have been used in the airborne DInSAR processing to acquire reliable deformation mapping. In this paper, we present the use of time-domain backprojection (BP) algorithm for SAR focusing in an airborne DInSAR survey: No MoCo procedure is needed because the BP algorithm is inherently able to compensate for platform motion. In this study, we present the results of a pilot study aimed at demonstrating the feasibility of deformation mapping with an airborne SAR system based on the monitoring of the Slumgullion landslide in Colorado, USA between July 3 and 10 of 2015. The employed airborne SAR system is an Artemis SlimSAR that is a compact, modular, and multi-frequency radar system. Airborne light detection and ranging and global navigation satellite system (GNSS) observations, as well as spaceborne DInSAR results using COSMO-SkyMed (CSK) images, were used to verify the performance of the airborne SAR system. The surface velocities of the landslide derived from the airborne DInSAR observations showed good agreement with the GNSS and spaceborne DInSAR estimates. A three-dimensional deformation map of the Slumgullion landslide was also generated, which displayed distinct correlation between the landslide motion and topographic variation. This study shows that an inexpensive airborne L -band DInSAR system has the potential to measure centimeter level deformation with flexible temporal and spatial baselines.

A First Assessment of the P-SBAS DInSAR Algorithm Performances Within a Cloud Computing Environment

We present in this work a first performance assessment of the Parallel Small BAseline Subset (P-SBAS) algorithm, for the generation of Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) deformation maps and time series, which has been migrated to a Cloud Computing (CC) environment. In particular, we investigate the scalable performances of the P-SBAS algorithm by processing a selected ENVISAT ASAR image time series, which we use as a benchmark, and by exploiting the Amazon Web Services (AWS) CC platform. The presented analysis shows a very good match between the theoretical and experimental P-SBAS performances achieved within the CC environment. Moreover, the obtained results demonstrate that the implemented P-SBAS Cloud migration is able to process ENVISAT SAR image time series in short times (less than 7 h) and at low costs (about USD 200). The P-SBAS Cloud scalable performances are also compared to those achieved by exploiting an in-house High Performance Computing (HPC) cluster, showing that nearly no overhead is introduced by the presented Cloud solution. As a further outcome, the performed analysis allows us to identify the major bottlenecks that can hamper the P-SBAS performances within a CC environment, in the perspective of processing very huge SAR data flows such as those coming from the existing COSMO-SkyMed or the upcoming SENTINEL-1 constellation. This work represents a relevant step toward the challenging Earth Observation scenario focused on the joint exploitation of advanced DInSAR techniques and CC environments for the massive processing of Big SAR Data.

A User-Oriented Methodology for DInSAR Time Series Analysis and Interpretation: Landslides and Subsidence Case Studies

Recent advances in multi-temporal Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) have greatly improved our capability to monitor geological processes. Ground motion studies using DInSAR require both the availability of good quality input data and rigorous approaches to exploit the retrieved Time Series (TS) at their full potential. In this work we present a methodology for DInSAR TS analysis, with particular focus on landslides and subsidence phenomena. The proposed methodology consists of three main steps: (1) pre-processing, i.e., assessment of a SAR Dataset Quality Index (SDQI) (2) post-processing, i.e., application of empirical/stochastic methods to improve the TS quality, and (3) trend analysis, i.e., comparative implementation of methodologies for automatic TS analysis. Tests were carried out on TS datasets retrieved from processing of SAR imagery acquired by different radar sensors (i.e., ERS-1/2 SAR, RADARSAT-1, ENVISAT ASAR, ALOS PALSAR, TerraSAR-X, COSMO-SkyMed) using advanced DInSAR techniques (i.e., SqueeSAR™, PSInSAR™, SPN and SBAS). The obtained values of SDQI are discussed against the technical parameters of each data stack (e.g., radar band, number of SAR scenes, temporal coverage, revisiting time), the retrieved coverage of the DInSAR results, and the constraints related to the characterization of the investigated geological processes. Empirical and stochastic approaches were used to demonstrate how the quality of the TS can be improved after the SAR processing, and examples are discussed to mitigate phase unwrapping errors, and remove regional trends, noise and anomalies. Performance assessment of recently developed methods of trend analysis (i.e., PS-Time, Deviation Index and velocity TS) was conducted on two selected study areas in Northern Italy affected by land subsidence and landslides. Results show that the automatic detection of motion trends enhances the interpretation of DInSAR data, since it provides an objective picture of the deformation behaviour recorded through TS and therefore contributes to the understanding of the on-going geological processes.

DInSAR Pixel Selection Based on Sublook Spectral Correlation Along Time

The reliability of any final differential synthetic aperture radar (SAR) interferometry (DInSAR) product is directly related to the phase quality of the interferograms involved in the processing. Performing an appropriate selection of high-quality pixels is hence mandatory in order to avoid the inclusion of noisy data in the processing and thus obtain reliable deformation information within the area of study. In this framework, a new full-resolution pixel selection method based on exploiting the spectral properties of pointlike scatterers is presented. The method is developed from the concept of the so-called coherent scatterers, which are characterized by having a correlated spectrum in a single acquisition, but now involving the temporal axis in the detection. Using the spectral properties of scatterers to perform the DInSAR pixel selection step presents some advantages with respect to the well-known permanent scatterer (PS) approach. On the one hand, the radiometric calibration of data is not required since the detection is now not dependent on the amplitude behavior of scatterers. On the other hand, a reliable pixel selection can be performed even with a reduced number of images due to the nature of the estimator. In contrast, its main limitation relies on the loss of range resolution involved in the sublook generation process. The method is more suited for urban scenarios where the density of temporally stable pointlike scatterers is generally higher. In this context, the final deformation maps obtained using the new method presented are compared, in terms of density and phase quality, with the ones obtained with the well-known traditional PS approach, showing a similar performance. Finally, since both methods characterize pointlike scatterers from different points of view, the combination of both techniques is proposed leading to a significant increase in the pixels' density and giving place to a meaningful improvement in the final DInSAR results.

Phase Quality Optimization in Polarimetric Differential SAR Interferometry

In this paper, a study of polarimetric optimization techniques in the frame of differential synthetic aperture radar (SAR) interferometry (DInSAR) is considered. Historically, DInSAR techniques have been limited to the single-polarimetric case, mainly due to the unavailability of fully polarimetric data. Lately, the launch of satellites with polarimetric capabilities, such as the Advanced Land Observing Satellite (ALOS), RADARSAT-2, or TerraSAR-X, allowed merging polarimetric and interferometric techniques to improve the pixels' phase quality and, thus, the density and the reliability of the final DInSAR results. The relationship between the polarimetrically optimized coherence or amplitude dispersion maps and the final DInSAR results is carefully analyzed, using both orbital and ground-based SAR fully polarimetric data. DInSAR processing using polarimetric optimization techniques in the pixel selection process is compared with the classical single-polarimetric approach, achieving up to a threefold increase of the number of pixel candidates in the coherence case and up to a factor of seven in the amplitude dispersion case.

Comparison between Differential SAR interferometry and ground measurements data in the displacement monitoring of the earth-dam of Conza della Campania (Italy)

This paper presents the application of Differential Synthetic Aperture Radar (SAR) interferometry (DInSAR) algorithms for the precise monitoring of earth dams ground deformation. The test site selected for this study is the Conza Dam, located in the southern Apennines (Italy), very close to the epicenter of the big earthquake (Mw=6.9) which took place on November 23th, 1980, striking the Irpinia region. Among the multiple advanced DInSAR techniques developed by the SAR community during the last decade, this work uses the so-called SUBSOFT software, developed by the Remote Sensing Laboratory (RSLab) group from the Universitat Politècnica de Catalunya (UPC), which is based on the use of Coherent Pixels Technique (CPT) algorithm. The analysis is carried out using 51 ENVIronmental SATellite-Advanced Synthetic Aperture Radar (ENVISAT-ASAR) images, corresponding to the period from 29th of November 2002 to the 30th of July 2010. In this framework, ground displacements recorded by a network of conventional ground-based sensors are also available for the same temporal span. Indeed, the embankment dam is well instrumented to measure internal settlements by means of cross-arms placed in six different cross-sections, and superficial displacements by means of targets for precise leveling. A statistical analysis has been performed to carry out a better comparison between the measurements obtained with the conventional field sensors and the interferometric data. The high agreement between final DInSAR displacements and in-situ instrumental data, demonstrates the reliability of such technique for the precise monitoring of civil infrastructures, and concretely, in dams with a high exposure factor and its consequent risk.

An application of the SBAS-DInSAR technique for the assessment of structural damage in the city of Rome

The remote sensing technique known as Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) allows the detection and monitoring of ground settlements, by generating deformation velocity maps and displacement time-series having centimeter to millimeter accuracy. These measurements can contribute to the evaluation of the structural conditions of the constructions. Given the settlements, different approaches exist for the assessment of the structural damage, ranging from empirical estimates to detailed finite element calculations. In this work, we integrate the results of a DInSAR analysis with an intermediate semi-empirical model to investigate three buildings located in the southern part of the city of Rome. The model, originally proposed by Finno et al. [(2005). ASCEJournal of Geotechnical and Geoenvironmental Engineering, 131(10), 1199–1210], considers each building as an equivalent laminated beam, where the layers represent the floors and the core material reproduces the infill walls. The results obtained by the model have been compared to the damages observed on the buildings, showing a good agreement and demonstrating that the proposed approach represents an effective and, at the same time, simple assessment tool for rapidly evaluating the conditions of several structures.

Joint approach using satellite techniques for slope instability detection and monitoring

A joint approach using satellite techniques was applied to two different regions (Sellas and Chalkeio villages) of Peloponissos (Greece) in order to detect and monitor slope instability. In the context of the research effort, a GPS campaign network, along with one permanent GPS station and a corner reflector (CR) network, was established at each region. From the two GPS campaigns that were carried out, ground displacements in the north and east components for Sellas region reached a magnitude of 9 and 8 mm, respectively, whereas for Chalkeio they were of the order of 1 cm and 8 mm, respectively. These results, however, are still preliminary and need validation from additional GPS campaigns that are planned to be carried out in future. The temporal resolution provided by the position time series of the permanent GPS stations highlighted the main features of both instability phenomena, that is, sensitivity at both horizontal components of motion for the Sellas region and slow linear trends for the Chalkeio region. The achieved precision of the daily solutions for both permanent GPS stations was found to be 1–3 mm for the horizontal components and 5–8 mm for the vertical components. Regarding the preliminary study of differential synthetic aperture radar (SAR) interferometry (DInSAR) in CR network, each reflector has been identified in SAR imagery, but at present the volume of SAR acquisitions is not adequate for providing safe deformation and error estimations. On the other hand, the permanent scatterers interferometry and small baselines subset (SBAS) techniques revealed a discontinuity in retrospective deformation rate along the observed rupture of Chalkeio village of almost 6 mm year−1.

Long-term ERS/ENVISAT deformation time-series generation at full spatial resolution via the extended SBAS technique

We extend the small baseline subset (SBAS) differential synthetic aperture radar (SAR) interferometry (DInSAR) approach to allow the generation of deformation time-series by processing, at the full spatial resolution scale, long sequences of European Remote Sensing (ERS-1 and ERS-2) and Environmental Satellite (ENVISAT) SAR data acquired with the same illumination geometry. In particular, we avoid the generation of ERS/ENVISAT cross-interferograms, which are severely affected by noise phenomena due to the carrier frequency separation of the two SAR systems, and we focus on single-platform interferograms only (i.e. ERS/ERS and ENVISAT/ENVISAT interferograms) that are properly combined by applying the singular value decomposition (SVD)-based SBAS approach. Moreover, we exploit the Doppler centroid variations of the post-2000 acquisitions of the ERS-2 sensor and the carrier frequency difference between the ERS-1/2 and the ENVISAT systems, in order to maximize the number of investigated SAR pixels and to improve their geocoding. The presented results, achieved on two data sets relevant to the Napoli Bay area and to the Murge region, both located in southern Italy, confirm the effectiveness of the extended SBAS technique and demonstrate the relevance of deformation analysis carried out at the scale of single buildings or human-made structures with more than 15 years of ERS and ENVISAT acquisitions.

Multi-baseline differential SAR interferometry analysis of Lantau Highway, Hong Kong, using ENVISAT ASAR data

In this letter, two multi-baseline differential synthetic aperture radar (SAR) interferometry (DInSAR) techniques, high-coherent point (HCP) and interferometric point target analysis (IPTA), were applied to monitor the displacement of Lantau Highway as an example of a large-scale artificial linear feature (LALF), using 17 ENVISAT advanced synthetic aperture radar (ASAR) images. The phase ramp was exploited and removed, combining the merits of two different model coherence functions when sparse HCP candidates were encountered. Then, two velocity fields from the advanced DInSAR methods were compared and analysed. The results indicate that the improved HCP method could generate a smoother deformation trend than the IPTA approach at the expense of losing detail information.

Two‐scale surface deformation analysis using the SBAS‐DInSAR technique: a case study of the city of Rome, Italy

We have exploited the capability of the differential synthetic aperture radar (SAR) interferometry (DInSAR) technique, referred to as Small BAseline Subset (SBAS) approach, to analyse surface deformation at two distinct spatial scales: a low resolution, large scale, and a fine resolution, local scale. At the large scale, the technique investigates DInSAR data with a ground resolution of the order of 100 m×100 m and leads to generate mean deformation velocity maps and associated time series for areas extending to some thousands of square kilometres. At the local scale, the technique exploits the SAR images at full spatial resolution (typically of the order of 5 m×20 m), detecting and analysing localized deformation phenomena. The study is focused on the city of Rome, Italy, and we used the ERS‐1/2 satellite radar data relevant to the 1995–2000 time period. The presented results demonstrate the capability of the SBAS approach to retrieve, from the low‐resolution DInSAR data, large‐scale deformation information leading to identify several sites affected by significant displacements. Our analysis permitted us to conclude that a major contribution to the detected displacements is due to the consolidation of the alluvial soils present in the area, mostly enforced by the buildings' overload. Furthermore, in a selected area, a detailed analysis was carried out by exploiting the full resolution DInSAR data. In this case we investigated deformation phenomena at the scale of single buildings. As key result we showed that differential displacements of few mm a−1, affecting single man‐made structures or building complexes, could be detected, thus allowing to identify sites that may potentially be involved in critical situations.

A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms

This paper presents a differential synthetic aperture radar (SAR) interferometry (DIFSAR) approach for investigating deformation phenomena on full-resolution DIFSAR interferograms. In particular, our algorithm extends the capability of the small-baseline subset (SBAS) technique that relies on small-baseline DIFSAR interferograms only and is mainly focused on investigating large-scale deformations with spatial resolutions of about 100/spl times/100 m. The proposed technique is implemented by using two different sets of data generated at low (multilook data) and full (single-look data) spatial resolution, respectively. The former is used to identify and estimate, via the conventional SBAS technique, large spatial scale deformation patterns, topographic errors in the available digital elevation model, and possible atmospheric phase artifacts; the latter allows us to detect, on the full-resolution residual phase components, structures highly coherent over time (buildings, rocks, lava, structures, etc.), as well as their height and displacements. In particular, the estimation of the temporal evolution of these local deformations is easily implemented by applying the singular value decomposition technique. The proposed algorithm has been tested with data acquired by the European Remote Sensing satellites relative to the Campania area (Italy) and validated by using geodetic measurements.

Estimation of rock glacier surface deformation using sar interferometry data

The detection and quantification of surface deformation of an active rock glacier using the differential synthetic aperture radar (SAR) interferometry (D-InSAR) technique is presented. An average deformation rate of -6 mm/35 days in the radar line of ight was estimated for the summer of 1992. The maximum deformation rate, -18 mm/35 days, was identified at the upper part of the rock glacier, whereas the deformation rate at the snout of the rock glacier was about -10 mm/35 days. The spatial distribution of the surface deformation in the D-InSAR displacement map is smooth and supports the idea that ice is the stress-transferring medium in rock glaciers.

Space-borne radar interferometric mapping of precursory deformations of a dyke collapse, Dead Sea area, Jordan

Satellite radar interferometry provides a technique to monitor a zone involving active salt tectonic phenomena. We detected movements in the Dead Sea area between 1993 and 1999. These preceded the catastrophic collapse (22 March 2000) of a newly built 12 km dyke belonging to the industrial salt evaporation ponds of the Arab Potash Company. Eighteen other dykes are present and still operational in this area of complex seismotectonic and hydrogeological settings. We used differential Synthetic Aperture Radar (SAR) interferometry (DInSAR) to investigate precursory deformations. Analysis of data shows that the collapsed area and its surroundings were in active subsidence at least 7 years before the event (maximum 44 mm in slant range from 16 December 1995 to 11 October 1997). This case emphasizes DInSAR as a tool suitable to identify deformations in such sensitive areas. It should be used at the stage of pre-feasibility studies of major projects and later in their stability monitoring, when required conditions of application are met.