## 1 Introduction  
Satellite SAR (Synthetic Aperture Radar) interferometry (InSAR) is a modern technique used for generation of digital elevation models (DEM), deformation estimation using differential interferometry (DInSAR) and estimation of surface deformation applied to time series analysis using multitemporal InSAR techniques (PSI, SBAS). It has the potential to provide ground surface deformation rate with millimetre accuracy [1]. The DInSAR technique is suitable in the analysis of single deformation episode caused by rapid movements of the earth's crust [2] and has limitations related to temporal and geometric decorrelations, estimation of phase unwrapping, estimation of phase ambiguity and reduction of the atmospheric component. Because of the need to process many SAR images and the above-mentioned limitations, more advanced InSAR techniques are used. These techniques also known as advanced differential interferometry synthetic aperture radar techniques (A-DInSAR) [3] use two main categories of backscatter [4]: Persistent Scatterers (PS) and Distributed Scatterers (DS). PS is characterized by high signal-to-noise ratio and usually occurs as a single pixel. Most often, it is the dominant scatterer (e.g., trihedral engineering object, plane, rock) in the resolution cell. Persistent scatterers exhibit stable amplitude and signal phase in all images [5]. Persistent scatterers (PS) are typically infrastructure objects and buildings and therefore their spatial distribution is usually irregular and might show high and low density values in different parts of urban area. DS have mean or low signal-to-noise ratio and are analyzed if they form a homogeneous group of pixels. DS are a sufficiently large group of adjacent pixels having a similar scattering mechanism and noise can be statistically mitigated. Usually, these are pixels with many small scatterers or similar size (e.g., natural scatterers like forests, agricultural fields, arid areas with low vegetation). The term Persistent Scatterers Interferometry (PSI) is used to refer to various techniques based on PSs, DSs and other hybrid approaches [6]. The main outcomes of a PSI are time series of displacement values and velocities of displacements over the analysed PSs or DSs. In the PSI technique, the interferograms are formed between one common image (master image) and each of the other images (slave images) in the stack. However, it is related to the extension of temporal baseline and the temporal decorrelation. The first PSI algorithms were developed by [PERSON] et al. [1,7], which were patented under the trademark PSInSAR. In the following years, further modifications of this technique were created and adapted to various applications. Among the various modifications, new solutions such as the STUN algorithm developed by [PERSON] [8] and an approach adapted to monitor volcanoes and other natural areas called StaMPS (Stanford Method for PS) developed by [PERSON] et al. [9] can be mentioned. StaMPS allows joint processing of PS and DS. In 2011, [PERSON] et al. also proposed an extension of the PSInSARTM algorithm under the name \(\text{SqueeSAR}^{\text{TM}}\) including DS processing. [PERSON] et al. [10] proposed a different approach assuming the formation of possible combinations of interferograms from SAR images stack. Datasets characterized by relatively small spatial distances between orbits referred as small baselines (SB) separated by large baselines form a common system of equations solved by the Singular Value Decomposition (SVD) method and the criterion of the minimum norm of the displacement velocity vector. The InSAR method is commonly employed to investigate ground surface displacements due to tectonic movements [11; 12; 13], volcanic activity [14; 15], mining and post mining activities [16; 17], landslide processes [2; 11; 18; 19] as well as land subsidence due to intensive groundwater extraction [20; 21].