InSAR Deformation Analysis with Distributed Scatterers: A Review Complemented by New Advances

Abstract

Interferometric Synthetic Aperture Radar (InSAR) is a powerful remote sensing technique able to measure deformation of the earth's surface over large areas. InSAR deformation analysis uses two main categories of backscatter: Persistent Scatterers (PS) and Distributed Scatterers (DS). While PS are characterized by a high signal-to-noise ratio and predominantly occur as single pixels, DS possess a medium or low signal-to-noise ratio and can only be exploited if they form homogeneous groups of pixels that are large enough to allow for statistical analysis. Although DS have been used by InSAR since its beginnings for different purposes, new methods developed during the last decade have advanced the field significantly. Preprocessing of DS with spatio-temporal filtering allows today the use of DS in PS algorithms as if they were PS, thereby enlarging spatial coverage and stabilizing algorithms. This review explores the relations between different lines of research and discusses open questions regarding DS preprocessing for deformation analysis. The review is complemented with an experiment that demonstrates that significantly improved results can be achieved for preprocessed DS during parameter estimation if their statistical properties are used.on DInSAR is given in [2]). The initial approach consisted of using three images that were used to form interferograms and a DEM. The DEM served to calculate and remove the synthetic phase. Furthermore, phase unwrapping was applied to generate the DEM and to obtain the deformation field. An algorithm for phase unwrapping was developed somewhat earlier for DEM generation from InSAR data in [9]. During the following years, techniques for most of the basic challenges of InSAR were developed. Early work on phase statistics and the phenomenon of decorrelation can be found in [10][11][12][13][14][15]. Enhancement of signal quality by filtering was considered, e.g., in [16,17]. Investigations, where stacking of interferograms is used to mitigate atmospheric delay, are discussed in [18][19][20]. Theory and algorithms were based on DS until the existence of PS was observed in the late 1990s by Ferretti while working on DEM reconstruction from a stack of SAR images [21]. In the sequel, they developed the first Persistent Scatterer Interferometry (PSI) algorithm [22,23], which extended the applicability of InSAR to scenes where enough PS are found but large parts are strongly decorrelated and hence unwrapping on the full interferograms cannot succeed. For several years from this time on, DInSAR and PSI developed in parallel. The next big step for DInSAR was the small-baseline subset (SBAS) technique [24]. By considering a redundant graph of small baseline interferograms, the effects of decorrelation could be mitigated and the redundancy enhanced robustness of estimation. In this first version, only DS were considered (using boxcar multilooking), but the next step [25] was to include processing of PS: coherent targets in the full resolution interferograms were recognized as having small r...

Demonstration of Time-Series InSAR Processing in Beijing Using a Small Stack of Gaofen-3 Differential Interferograms

“…More and more in-orbit SAR sensors provide abundant data for InSAR applications. With the accumulation of repeat-pass SAR images, various advanced time series InSAR (TS-InSAR) approaches have been proposed [7][8][9][10]. The TS-InSAR approaches require multiple SAR images to extract high-precision surface deformation measurements.…”

“…Coherent Pixel Technique (CPT) [16] and Interferometric Point Target Analysis (IPTA) [17] have been proposed later in 2003. Subsequently, Spatio-Temporal Unwrapping Network (STUN) [18], Stanford Method for Persistent Scatterers (StaMPS) [19,20], SqueeSAR [21], Temporarily Coherent point InSAR (TCP-InSAR) [22], and other specific TS-InSAR approaches [7][8][9][10] have been proposed to extend the scope of application of TS-InSAR approaches.…”

Fusion of GNSS and Satellite Radar Interferometry: Determination of 3D Fine-Scale Map of Present-Day Surface Displacements in Italy as Expressions of Geodynamic Processes

“…This technique, which is called Differential Interferometric Synthetic Aperture Radar (DInSAR), has been improved by deformation analysis uses two main categories of backscatter: Persistent Scatterers (PS) and Distributed Scatterers (DS). While PS [9,10] are point solutions of sparse ground targets characterized by the long-term stability of the electromagnetic spectral backscattered signal and high reflectivity, DS [11,12] possess a medium-low electromagnetic spectral back-scatter signals derived by the reflection of a homogeneous group of pixels. PS and DS are both differential methods; all the SAR images involved in the determination of DInSAR displacements are aligned using reference points that are supposed to be stable and unmoving and by imposing the maximum coherence between pairs of SAR images.…”

PSInSAR Processing for Volcanic Ground Deformation Monitoring Over Fogo Island

“…However, the high temporal decorrelation in the interferograms caused by vegetation limits the capability of InSAR to estimate the deformation of natural terrains. The accuracy of the InSAR is also affected by the phase delay introduced by the atmospheric constituents, which are difficult to remove from the interferograms [2]. The PSInSAR technique utilizes a large number of interferometric pairs, compared to InSAR, to overcome these limitations.…”