Multitemporal differential interferometric synthetic aperture radar (MT-DInSAR) techniques have become essential tools for monitoring ground displacement with millimeter-scale precision. While widely applied to spaceborne SAR systems for global, long-term monitoring, and to ground-based SAR (GBSAR) for continuous tracking in localized areas, these platforms remain constrained by fixed acquisition geometries and line-of-sight (LOS) sensitivity. In addition, spaceborne systems face inherent limitations in capturing high-magnitude displacements due to their relatively long revisit times, often leading to temporal decorrelation in such scenarios. In this context, airborne SAR systems offer a compromise by enabling flexible acquisition geometries and on-demand revisit times, with drone platforms emerging as a cost-effective alternative to the high operational and logistical demands of conventional airborne systems. This article presents the SAR-Drone system, a Ku-band drone-based SAR, and a coregistration and interferometric processor together with two multitemporal DInSAR (MT-DInSAR) methodologies adapted to the SAR-Drone data. The first is displacement-based and designed for scenarios with moderate motion, where interferometric phase remains coherent between consecutive acquisitions; the second is velocity-based, targeting scenarios with high-magnitude displacements where decorrelation occurs even when only a few hours separate acquisitions. The displacement-based methodology is validated in a controlled experiment using corner reflectors, while the velocity-based methodology is demonstrated in a real open-pit mine, where metric-scale slope movements occur within intervals of approximately one day. The results presented in the article demonstrate the potential of drone-based SAR to complement existing spaceborne, ground-based, and airborne systems by enabling high-resolution 3-D displacement tracking in complex and rapidly evolving environments.

The accurate flight trajectory knowledge is crucial for airborne and drone-borne repeat-pass synthetic aperture radar (SAR) interferometry. Given that Global Navigation Satellite Systems (GNSS) inaccuracies are comparable with typical radar wavelengths, especially at high-frequency bands (X band and higher), estimating the residual motion error (RME) is essential to ensure precise coregistration of single-look complex (SLC) stacks and to generate high-quality repeat-pass interferograms. In this framework, traditional RME estimation techniques, such as the multisquint algorithm, often suffer performance degradation under large errors and high-decorrelation conditions, as they rely heavily on the quality of uncoregistered interferograms. To address this limitation, this article introduces an enhanced version of the multisquint technique that solves the estimation of RME using a minimization strategy in the complex domain and uses the retrieved RMEs of the entire interferometric dataset to refine the estimates. This approach improves the RME estimation robustness against large errors and decorrelation artifacts, particularly in high-frequency airborne and drone-borne SAR datasets. The proposed method is validated using a real dataset acquired with a Ku-band drone-borne SAR system, demonstrating significant improvements in coregistration accuracy. Quantitative evaluations based on interferometric coherence and phase fringe frequency metrics confirm its effectiveness, establishing the proposed refinement as a robust solution for high-precision interferometric applications.

In recent years, drone-based Synthetic Aperture Radar (SAR) systems have emerged as flexible and cost-efficient solutions for detecting changes in the Earth’s surface, retrieving topographic data, or detecting ground displacement processes in localized areas, among other applications. These systems offer a unique combination of short and versatile revisit times and flexible acquisition geometries that are not achievable with space-borne, airborne, or ground-based SAR sensors. However, due to platform limitations and flight stability issues, they also present significant challenges regarding instrument design and data processing, particularly when generating interferometric repeat-pass datasets. This paper demonstrates the feasibility of repeat-pass interferometry using a Ku-band drone-based SAR system. The system integrates a dual-channel Ku-band Frequency Modulated Continuous Wave (FMCW) radar with cross-track single-pass interferometric capabilities, mounted on a drone platform. The proposed repeat-pass interferometric processing chain leverages an accurate Digital Elevation Model (DEM), generated from the single-pass interferograms, to precisely coregister the entire stack of acquisitions, thereby producing repeat-pass interferograms free from residual motion errors. The results underscore the potential of this system and the processing chain proposed for generating multi-temporal repeat-pass stacks suitable for repeat-pass applications.

Airborne Synthetic Aperture Radar (SAR) systems have been widely used in the last decades, especially for research purposes, offering higher revisiting time, better spatial resolution, and flexible acquisition geometry compared to satellite radar systems. In recent years, the rapid technological evolution of Remotely Piloted Aircraft (RPA) has opened up the possibility of integrating SAR systems into these agile platforms, allowing the community to explore the new possibilities that they can offer. The present paper introduces the interferometric capabilities of a new Ku-Band SAR system, called SARDrone, that has been completely developed and integrated into an RPA by DARES Technology. The document aims to present the first results obtained with the SARDrone system that demonstrate the inherent potential of multicopter platforms applied to SAR interferometry.

The application of differential synthetic aperture radar interferometry (DInSAR) techniques has been traditionally limited to the single-polarimetric case. The launch of satellites with polarimetric capabilities has triggered the synergy between polarimetric and interferometric algorithms, leading to a significant improvement in final DInSAR products. During the last years, the different polarimetric optimization techniques available have been successfully applied to the so-called classical phase quality estimators, i.e., the coherence and the amplitude dispersion estimators. In this context, a new estimator to evaluate the pixels' phase quality, referred to as temporal sublook coherence (TSC), has recently demonstrated to provide promising results in DInSAR applications. The nature of this estimator, which is based on exploiting the spectral properties of pointlike scatterers through the coherence evaluation of different sublooks of the image spectrum, allows its adaptation to the existing polarimetric optimization methods. This letter presents the benefits of extending the TSC estimator to work with fully polarimetric data. For this purpose, a fully polarimetric data set consisting of ten X-band ground-based SAR (GB-SAR) images is employed. The final DInSAR results obtained by means of TSC polarimetric optimization are compared with the ones obtained with its classical single-polarimetric approach, achieving up to more than a twofold increase in the pixels' density.

Prior to the application of any persistent scatterer interferometry (PSI) technique for the monitoring of terrain displacement phenomena, an adequate pixel selection must be carried out in order to prevent the inclusion of noisy pixels in the processing. The rationale is to detect the so-called persistent scatterers, which are characterized by preserving their phase quality along the multi-temporal set of synthetic aperture radar (SAR) images available. Two criteria are mainly available for the estimation of pixels' phase quality, i.e., the coherence stability and the amplitude dispersion or permanent scatterers (PS) approach. The coherence stability method allows an accurate estimation of the phase statistics, even when a reduced number of SAR acquisitions is available. Unfortunately, it requires the multi-looking of data during the coherence estimation, leading to a spatial resolution loss in the final results. In contrast, the PS approach works at full-resolution, but it demands a larger number of SAR images to be reliable, typically more than 20. There is hence a clear limitation when a full-resolution PSI processing is to be carried out and the number of acquisitions available is small. In this context, a novel pixel selection method based on exploiting the spectral properties of point-like scatterers, referred to as temporal sublook coherence (TSC), has been recently proposed. This paper seeks to demonstrate the advantages of employing PSI techniques by means of TSC on both orbital and ground-based SAR (GB-SAR) data when the number of images available is small (10 images in the work presented). The displacement maps retrieved through the proposed technique are compared, in terms of pixel density and phase quality, with traditional criteria. Two X-band datasets composed of 10 sliding spotlight TerraSAR-X images and 10 GB-SAR images, respectively, over the landslide of El Forn de Canillo (Andorran Pyrenees), are employed for this study. For both datasets, the TSC technique has showed an excellent performance compared with traditional techniques, achieving up to a four-fold increase in the number of persistent scatters detected, compared with the coherence stability approach, and a similar density compared with the PS approach, but free of outliers.

Urban subsidence and landslides are among the greatest hazards for people and infrastructure safety and they require an especial attention to reduce their associated risks. In this framework, ground-based synthetic aperture radar (SAR) interferometry (GB-InSAR) represents a cost-effective solution for the precise monitoring of displacements. This work presents the application of GB-InSAR techniques, particularly with the RiskSAR sensor and its processing chain developed by the Remote Sensing Laboratory (RSLab) of the Universitat Politecnica de Catalunya (UPC), for the monitoring of two different types of ground displacement. An example of urban subsidence monitoring over the village of Sallent, northeastern of Spain, and an example of landslide monitoring in El Forn de Canillo, located in the Andorran Pyrenees, are presented. In this framework, the key processing particularities for each case are deeply analyzed and discussed. The linear displacement maps and time series for both scenarios are showed and compared with in-field data. For the study, fully polarimetric data acquired at X-band with a zero-baseline configuration are employed in both scenarios. The displacement results obtained demonstrate the capabilities of GB-SAR sensors for the precise monitoring of ground displacement phenomena.

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.

Temporal phase wrapping may be an issue in Differential SAR Interferometry (DInSAR) for terrain displacement monitoring, especially when the deformation rate of the phenomena under observation is high and/or the temporal sampling of the SAR dataset is poor. This work proposes upgrades in the Coherent Pixels Technique in order to deal with these situations. They are based on an iterative method to reach the optimum solution and an approach to obtain an a priori model of the displacement phenomenon. Both methods are tested with an Envisat ASAR data-set over a mining area.

This paper seeks to demonstrate that radar-based remote sensing techniques are as effective as conventional geotechnical ones for geo-hazard assessment and mitigation. Concretely, this work encourages the proper combination of differential synthetic aperture radar (SAR) interferometry (DInSAR) results, using high-resolution X-band SAR data coming from orbital and ground-based SAR sensors, for the efficient monitoring of slow-moving landslides.

This paper presents an application example of the use of the Differential Interferometry Synthetic Aperture Radar technique (DInSAR) for monitoring ground movements in a geologically complex area around the village of Suria (Ebro Basin, Catalonia, NE Spain), associated to underground mining activities and to the presence of a salt dome.The analysis has been mostly performed in a rural environment affected by ground movements with different patterns, magnitudes and causes. A total of fifty SAR images recorded between 1995 and 2007 were processed to generate the interferograms. In order to study the non-linear trends or changes of the ground surface behavior, the DInSAR technique was applied in two sets of images.The interferometric results, in the form of vertical displacement rate maps, were checked against conventional surveying and GPS measurements. The results present a significant discrepancy in some location due to the wrapping of the phase when both fast and significant deformations occur. In order to avoid the latter effect and improve the accuracy of the results, all SAR images were reprocessed using topographic leveling and GPS data of different monitored points.To support the DInSAR interpretation, a detailed geological reconnaissance of the study area was carried out as well as an inventory of ground movement indicators. Four different patterns of ground movement have been identified: active shifting subsidence associated to the progression of the mining exploitation fronts; residual subsidence on abandoned galleries with a decreasing rate of closure; uplifting due to the intrusion of the salt dome; and sudden ground collapses (sinkholes) caused by the dissolution of soluble materials laying close to the ground surface. (C) 2013 Elsevier B.V. All rights reserved.

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.

In DInSAR processing it is possible to detect different kinds of targets at different resolutions. Point like scatters can be selected with high resolution selection methods, like amplitude dispersion. Distributed scatters can be selected with a coherence spatial window. The joint combination of two or more pixel selection methods can be useful to get a higher pixel density and identify, compare and evaluate distributed and point like scatters at the same time.

This paper seeks to demonstrate that radar-based remote sensing techniques, especially those based on orbital sensors, can be as effective as the conventional geotechnical and discrete GPS measurement ones for the detection and monitoring of well suited landslides. Unfortunately, deformation can only be retrieved for those landslides presenting a good orientation with respect the satellite orbit. In addition, many of the high mountain landslides are vegetated areas that decorrelate faster at X-band. As in these scenarios the number of persistent scatterers can be low and, at the same time, the area of interest is usually small, the processing can be benefited of the usage of high-resolution data that will maximize the chances of detecting persistent scatters coming from both natural targets and man-made structures. The high resolution Spotlight mode of TerraSAR-X is thus the perfect choice as it offers a fine resolution. In addition, its 11 days of revisit time and X-band carrier allows the monitoring of small variations in the landslide trend and deal with its variable dynamics. The landslide of study is ‘El Forn de Canillo’ (Andorra) where the deformation results will be compared and validated with those obtained with the deployed UPC's Ground-Based (GB-SAR) X-band sensor.

Orbital Differential SAR Interferometry (DInSAR) is a well-known technique to retrieve terrain deformation phenomena from wide areas with high resolution. Historically its application has been limited to single polarization SAR, mainly due to the unavailability of polarimetric data. Lately, the launch of several satellites with polarimetric capabilities, such as Radarsat-2 or TerraSAR-X, allows merging polarimetric and interferometric techniques in order to improve the results obtained in the DInSAR processing. This work will explore the existent analytical techniques in order to optimize the quality of the subsidence results. The dataset used contains 35 Fine Quad-Pol Radarsat-2 acquisitions over the city of Barcelona (Spain).

This paper aims to demonstrate that radar-based remote sensing techniques can be as effective as the conventional geotechnical ones for the detection and monitoring of well suited areas. Many of the high mountain landslides are vegetated areas that decorrelate faster at X-band. As in these scenarios the number of coherent scatterers is low and, in addition, the area of interest is usually small, the processing can be benefited of the usage of high-resolution data. This will maximize the chances of detecting persistent scatters coming from both natural targets and man-made structures. The high resolution Spotlight mode of TerraSAR-X is thus the perfect choice as it offers a fine resolution. On the other hand, its 11 days of revisit time and X-band carrier allows the monitoring of small variations in the landslide trend and deal with its variable dynamics.

This paper presents a full resolution pixel selection method, alternative to the traditional ones, which is based on the study of the spectral correlation coefficient along time among different Sublooks of the image spectrum. This pixel selection criterion has been developed from the concept of the so-called Coherent Scatters (CSs), which are characterized by a deterministic point-like scattering behaviour in each single acquisition, but now including its temporal stability. The proposed method presents the advantage that it does not require any radiometric calibration of the data as it only uses the spectral properties of a point-scatter but not relying on its amplitude.

This paper presents a full resolution pixel selection method, alternative to the traditional ones, that is based on the study of the spectral correlation coefficient along time between different Sublooks of the image spectrum. This pixel selection criterion has been developed from the concept of the so-called Coherent Scatterers, which are characterized by a deterministic point-like scatterering behaviour in a single acquisition, but now including its temporal stability. The proposed method presents the advantage that it does not require any radiometric calibration of the data as it only uses the spectral properties of a point-scatter but not relying on its amplitude. The method can perform a reliable selection of pixel candidates even with a reduced number of images and it is more suited for urban areas, where the density of temporal stable point-like scatterers is higher.