## 3 Methods and Data
### PS-MTI Processing  
Table 1 presents the 35 CSK SAR images acquired between October 2013 and August 2015. All data have the same acquisition geometry, i.e., descending STRIPMAP HIMAGE H4-17 with a nominal spatial ground resolution of 3 m. Although the temporal resolution of CSK acquisitions using one satellite of the constellation is 16 days, it was not possible to obtain imagery systematically with these time-steps due to the CSK dual use (civil and military) policy, especially for some periods in 2013 and 2014. Figure 2: Flowchart of the methodology, divided into: (i) SAR image processing; and (ii) results interpretation and validation using ground-based GPS observations. PS-MTI processing was performed using the PSI module within SARscape(r) software [62]. The first step in the PSI module is called \"Connection Graph Generation\" and defines the combination of image pairs that will be processed choosing the appropriate master and slave images, after calculating their normal and temporal baseline (Figure 2). Then, a working area over the reference master is selected for the stack of Single Look Complex (SLC) images. Two steps of inversion are processed in order to estimate the displacement velocity. A back-and-forward step aims to select the appropriate coherence threshold (e.g., CC = 0.6) to remove topography and atmospheric contributions, and to create the final SAR coherence map. The coherence threshold selected in this step is a compromise between two opposite needs. In fact, the points used for the estimation of APS are only those with coherence over this threshold, that therefore should be small enough to grant a consistent and well distributed number of points, but also high enough to allow the selection of reliable points only. A comparison of the coherence values before and after the APS removal where the CRs are located is a possible way to evaluate the quality of the APS estimation. PS SARscape(r) algorithm is operating on the phase time-series of each highly stable target separately, without using any contextual spatial information. Results are obtained at maximal spatial resolution with the advantage of avoiding corruption of the signal by incoherent pixels, because only pixels with high coherence are selected for the analysis. According to particular coherence and amplitude dispersion index \(\upmu/\sigma\) thresholds (see Figure 2), final PS are selected and finally geocoded to estimate the LOS variation at the targets (i.e., artificial CRs). The coherence is a measure of the fitting to the linear model used by PS algorithm. Consequently, we choose a lower coherence threshold compared to the default value proposed by the software (i.e., CC = 0.75) because the landslide displacements display non-steady state accelerations or decelerations in some periods. This result encompasses the CRs considered as artificial PS and characterized by a high value of the amplitude dispersion index (\(\upmu/\sigma\) threshold). In the processing chain, the selection of a higher value of the \(\upmu/\sigma\) threshold allows us to avoid to select points with coherence comparable to that of the artificial CRs but not reliable as PS. Indeed, as the Corvara landslide does not feature prominent rocks or larger infrastructure such as houses that could act as PS, it was necessary to install artificial CRs to provide a backscatter signal visible in all SAR images. The CRs used derive from the design presented by [PERSON] et al. [45] with some specific changes for ground deformation monitoring in alpine environments [61]. The CRs consist of an aluminum trihedral reflector (with a side length of 56 cm) installed on stainless steel poles (1.5 m high, to avoid that the CRs are completely covered by snow during winter) that are anchored to the ground using concrete piles (1.5 m long, 0.2 m diameter). The aluminum plates are also perforated to minimize water accumulation, wind resistance and weight.