## 1 Introduction
In contrast, the PS approach is mainly employed for the detection of deterministic point-like targets, such as man-made structures, which are not affected by geometrical decorrelation and speckle noise, as there is a single dominant scatter within the resolution cell. There is hence a clear limitation when the full-resolution of SAR images requires being preserved to exploit the point-like scatters within the the illuminated scenario and the number of images available is small. A clear example of this appears when SAR images of the so-called new family of X-band SAR sensors, like the German TerraSAR-X and TanDEM-X satellites [22, 23] or the Italian constellation Cosmo-Skymed [24], are ordered for area monitoring. During the last few years, this new family of SAR sensors has led to a scientific breakthrough presenting low revisiting times (up to few days) and improved spatial resolutions (up to the meter), which are providing scientists outstanding amounts of unprecedented X-band SAR data. Nonetheless, the acquisition of these products has become considerably more expensive compared with its predecessors, such as ERS-1/2 or ENVISAT. This fact compromises in many cases the acquisition of a large number of SAR images with the lowest time lapses, since it considerably increases the cost of the monitoring and can make PSI techniques lose a competitive advantage against other surveying techniques. This is clearly the case of slow-moving phenomena monitoring, because large numbers of SAR images acquired in a short period of time do not provide new information. In addition, the high-resolution of the images, the shorter swaths and the multiple modes available make these data be acquired \"under demand\". This implies that it will be very unlikely to have a historical archive of images of a particular area of interest. Finally, it must be pointed out that in the presence of large spatial baselines, understanding large as closer to the critical baseline, a big amount of coherence maps under the coherence stability approach cause some interferograms to be useless due to the geometrical decorrelation [6]. A full-resolution PSI processing is mandatory in all of these cases in order to benefit from the high-resolution provided by these sensors, even when a reduced set of SAR data is available. Another interesting example arises from the use of ground-based SAR (GB-SAR) sensors when these are employed to carry out a discontinuous monitoring of affected areas. This operation mode consists of revisiting the area of interest during different measurement days at regular intervals, and it is typically addressed for the monitoring of slow-displacement rate phenomena, where performing a continuous monitoring is inefficient and costly. Once again, improving the performance of full-resolution PSI techniques when a reduced number of GB-SAR images is available is clearly interesting. In order to overcome this limitation of classical PSI techniques, a new approach based on exploiting the spectral properties of point-like scatterers has been recently presented in [25]. This method takes advantage of the so-called coherent scatterers (CS), presented in [26], but including the temporal axis in the detection. The rationale is to estimate which targets exhibit a high spectral correlation coefficient along the multi-temporal set of SAR images available. This estimation is referred to as temporal sublook coherence (TSC). Those targets fulfilling this condition will be directly related to as point-like scatterers with reliable phases or following the nomenclature used in [25], as temporally stable coherent scatterers (SCS). To date, the application of PSI techniques by means of TSC has been demonstrated for urban subsidence monitoring using a large number of orbital SAR data. In that case, results have shown a similar performance if compared with the PS approach [25]. The objective of this paper is to demonstrate the applicability of the TSC approach for PSI purposes when a reduced number of SAR images is available.