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 Politècnica 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.