## 1 Introduction  
Glaciers and paraglacial processes, as landslides and rock glaciers, play an important role in the short- and long-term landscape evolution of high mountain regions [1; 2; 3]. Changes in climatic conditions, as well as human activity, can have a severe influence on such geomorphological processes, and increase the frequency and intensity of catastrophic mass wasting events [4; 5]. In alpine regions, glaciation has been recognized as one of the most important agents influencing the regional geomorphology [6; 7]. Indeed, several geological and geomorphological studies have outlined the relation between large slope instabilities and deep-seated gravitational slope deformation located in glacial valleys, likely due to the debuttressing caused by glacier retreat [8; 9; 10; 11]. In this scenario, monitoring surface deformation in high mountain regions can help to better interpret the kinematic behavior of mass wasting processes, and to infer potential influences of meteo-climate variables on their evolution [12; 13; 14]. This information is crucial to increase our capability to assess landslide hazards, and to manage the associated risks [15; 16; 17; 18]. In recent decades, surface deformation in mountain environments has been measured by means of diverse monitoring approaches, ranging from classical in situ instruments [19; 20; 21; 22; 23; 24] to more advanced remote sensing methods [25; 26; 27; 28]. In situ instruments are typically installed to obtain a time series with high temporal resolution, which allows for a better analysis of local phenomena over time, while remote sensing techniques are more suitable for the evaluation of deformation trends at regional scales. Among different techniques, space-borne differential synthetic aperture radar (SAR) interferometry (DInSAR) has gained an important role in measuring ground displacements over the last few years [29]. DInSAR is a consolidated method used to provide data with extensive spatial coverage and to investigate different types of phenomena simultaneously, including those hindered by limited or difficult access. For example, DInSAR was successfully applied to detect and monitor slow movements of mountain slopes in the order of few centimeters/year in the Austrian and Swiss Alps, and the Pyrenees, confirming its operational potential in high mountain areas [30; 31; 32]. Advanced DInSAR methods have been developed to derive ground velocity maps and displacement time series [33; 34; 35]. The small baseline subset (SBAS) technique [34], which combines sets of interferograms with small orbital separation (baseline) and short revisiting time to reduce the temporal decorrelation and maximize the number of coherent SAR targets, has proven to be suitable in different deformation scenarios [36; 37; 38; 39]. Accuracies are in the order of 1 mm/year for mean surface velocities and 5 mm for displacement measurements [40]. Nowadays, the increasing availability of multi-temporal satellite acquisitions allows for the generation of time series of ground deformation spanning periods as long as 20 years. This information is particularly suitable for studying the long-term behavior of landslides, rock glaciers, and glaciers. However, the analysis of surface deformation via DInSAR is challenging for several reasons, including (i) the high topographic gradients associated with the complex orography; (ii) abundant vegetation affecting the temporal correlation of the SAR signal; and (iii) unsuitable valley flank orientations relative to the SAR view angle [41; 42; 43; 44]. Moreover, DInSAR ground deformation monitoring for systematic analyses is complicated due to the intrinsic limitations of the technique (i.e., coherence loss due to large revisit time, phase decorrelation due to large or rapid displacement, and line-of-site (LOS) measurements only) [33; 45; 46; 47]. Additional issues are caused by the atmospheric phase screen (APS), which is amplified by high topographic gradient in high mountain regions.