In this study, we develop a methodology to evaluate and benchmark the European Ground Motion Service (EGMS) products. Our approach integrates Global Navigation Satellite Systems (GNSS) measurements and measurements at and around corner reflectors (CRs), targeting the three product levels of the EGMS. We employ statistical tests to identify significant differences in the comparisons, focusing on time series, velocity estimation, and geopositioning. The study applies this practical methodology to evaluate the first EGMS product from 2015 and 2021 over various European test sites with significant surface deformation. The results consistently demonstrate a solid time series and velocity correlation between EGMS and GNSS at the tested sites, with, e.g., most of the differences between velocities being below 2 mm/year. This methodology, implemented in Python notebooks, ensures reproducible results and allows for validating the EGMS over other locations.

Many PSInSAR algorithms are based on the phase difference of connected PSs, which are usually spatially integrated to recover the deformation gradients with respect to a common reference point. In the presence of noise this can lead to errors propagating throughout the whole PS network. In our work we adapt the concept of connectivity originally proposed in the DInSAR context as a way to estimate the quality of the phase integration for each PS. We simulate PS networks under a variety of noise conditions, and find that connectivity is consistently correlated with integration errors, and provides complementary information compared to local quality parameters such as temporal coherence. We discuss the use of connectivity to optimize the selection of spatial references, and to discard measurements, which are more likely to be affected by integration errors. Finally, we validate our methodology on a real data set from TerraSAR-X covering the greater Copenhagen area.

The application of Sentinel-1 interferometry to ice velocity measurements has until recently been limited by the significant horizontal scene motion associated with ice flow, which causes phase discontinuities (and associated unwrapping problems) at burst boundaries in Terrain Observation by Progressive Scans (TOPS) interferograms. Coregistering with a multiyear averaged external velocity mosaic based on offset-tracking can account for the bulk of the ice motion, but residual discontinuities sometimes remain, for example, due to seasonal variations in the ice velocity, or due to error sources such as azimuth shifts caused by ionospheric propagation. The presented method extends the external velocity coregistration with a local, spatially varying, coregistration in the burst overlap regions. This is based on the extended spectral diversity principle, which can only be applied in the overlap regions, but offers superior accuracy and resolution compared with traditional coregistration methods. The method considerably reduces phase discontinuities at burst boundaries, and potential new phase discontinuities at the overlap region edges are suppressed by an azimuth tapering of the applied coregistration shifts. An example scene is presented, and the phase discontinuities before and after application of the method are evaluated. The method is seen to remove phase discontinuities, with no adverse effects.

Differential synthetic aperture radar interferometry (DInSAR) allows for retrieval of ice velocity measurements of high resolution and accuracy. One of the main error sources in DInSAR is the phase unwrapping procedure. Unwrapping errors may be caused by several processes, including shear stresses associated with large motion gradients, which lead to loss of interferometric coherence. In many cases, unwrapping errors reach magnitudes corresponding to velocities of tens or even hundreds of meters per year. Traditional DInSAR implementations include pixel masking based on coherence thresholding; however, such a masking is not always sufficient. Consequently, the state-of-the-art for ice velocity retrievals involves either manual inspection of individual measurements or simply discarding measurements in regions where ice flow exceeds a predefined threshold. Here, we instead apply a masking based on thresholding of a pixel connectivity estimate with respect to a reference point, which aims to detect unwrapping errors based only on the estimated coherence pattern. The method is tested on both simulated and real data Sentinel-1 data from the Greenland Ice Sheet and effectively detects the majority of unwrapping errors (recall of 0.84 for the best performing threshold), although with a relatively low precision (0.52 for the best performing threshold). Importantly, higher magnitude unwrapping errors are associated with lower connectivity values, meaning that undetected errors have a significantly lower magnitude (median of 1.7 m/y, corresponding to a single phase cycle, compared with 40.5 m/y with no masking).

In view of the ESA-CONAE SAOCOM-CS L-band bistatic SAR mission this paper will present, analysis of geometric parameters impact on tomographic processing, discussing questions related to vertical resolution, baseline sampling and interferometric phase calibration in the context of bistatic acquisitions. L-band tomographic processing experiments on real data will be also presented exploiting available ESA SAR airborne campaign images. The amount of computational speed improvement when performing the tomographic algorithms in parallel environment will be also addressed. Furthermore, specific analysis concerning the extension to a possible similar bistatic mission for Sentinel 1 C-band data will be also addressed addressing the TOPS mode impact on tomographic processing.

We used a variety of SAR-based techniques to measure the crustal deformation associated to the Darfield and Christchurch earthquakes, New Zealand. We detected clear post-seismic signals of the Darfield earthquake, and a pre-seismic signal spatially and temporally associated to the Christchurch earthquake. The small pre-seismic signal (∼25 mm) has an opposite polarity of the much larger co-seismic one (∼150 mm) in the same area.

In this study, we performed a detailed survey of surface deformations occurred in two different regions in Italy. The first, located in Southern Italy, takes into consideration the causative fault of the 1908 Messina earthquake (Mw 7.1), that is an east-dipping normal-oblique fault lying under water along the Straits of Messina. The second site is the L'Aquila area (Central Italy), where a Mw 6.3 earthquake occurred on 6th, April 2009. The subsequent studies demonstrated that the best-fit solution for the main shock, retrieved by DInSAR data, is represented by a normal fault -16 km long and -12 km wide, with a small right-lateral component, dipping 47°SW with a maximum slip of -90 cm (Atzori et al., 2009) [1]. This study is completely carried out within the SiGRiS project, funded by the Italian Space Agency (ASI).

Several interferometric synthetic aperture radar applications could benefit from the availability of a closed-form model for the second-order statistics of atmospheric delay. Due to the variability of the latter, it would also be desirable for the model to be tunable to some acquisition-specific information, describing the atmospheric state. In this letter, a closed-form expression for the zenith delay structure function of tropospheric propagation delay is derived from a two-regime power spectral density function reported in the literature. The power at a specific spatial frequency is used as a free model parameter, which may be tuned to available measurements or, in the absence of these, to atmospheric statistics. The latter approach is used to compare the derived model with previously published results.

Synthetic aperture radar signal processing issues related to the exploitation of a pulse-to-pulse encoding transponder using pseudorandom codes discussed analytically. Namely the focusing algorithm, the code synchronization procedure and the properties of the code induced gain against non-encoding point scatterers and distributed ones. A time-domain processing algorithm and a code synchronization procedure are proposed and validated on simulated data and on a European Remote Sensing Satellite-2 data set containing prototypes of such a device. The interaction of the transponder signal with terrain backscattering is analyzed by deriving parameters that are useful for performance assessment. These are related to the relevant parameters in radiometric calibration, interferometric applications, and tagging.

Three of the major error sources in interferometric synthetic aperture radar measurements of terrain elevation and displacement are baseline errors, atmospheric path length errors, and phase unwrapping errors. In many processing schemes, these errors are calibrated out by using ground control points (GCPs) (or an external digital elevation model). In this paper, a simple framework for the prediction of error standard deviation is outlined and investigated. Inputs are GCP position,a prioriGCP accuracy, baseline calibration method along with a closed-form model for the covariance of atmospheric path length disturbances, and a model for phase unwrapping errors. The procedure can be implemented as a stand-alone add-on to standard interferometric processors. It is validated by using a set of single-frame interferograms acquired over Rome, Italy, and a double difference data set over Flevoland, The Netherlands.

This paper focuses on statistical modeling of water vapor fluctuations for InSAR. The structure function and power spectral density approaches are reviewed, summarizing their assumptions and results. The linking equations between these modeling techniques are reported. A structure function model of zenith tropospheric propagation delay is then derived from a two-regime power spectral density function presented in literature. The novelty lies in the fact that a closed form expression is derived and a free model parameter is allowed, which may be tuned to available measurements or, in the absence of these, to atmospheric statistics. The latter approach is used to compare the derived model with previously published results.

Applications which could benefit from the use of an artificial device capable of encoding the SAR signal have been recently presented in literature. In this paper an implementation of a processing algorithm suitable to exploit such a device is described. Two general purpose figures of merit are proposed for the algorithm and the preliminary results of their theoretical and experimental evaluation are presented.