## 3 Material and Methods
### InSAR Dataset and Processing  
In this work, synthetic aperture radar images captured by Copernicus Sentinel 1 A-B satellites were used. These images are acquired in C-Band (5.6 cm radar wavelength). The acquisition intervals are 12 days before August 2016 and reach 6 days after the launch of Sentinel 1 B. Interferogram processing was done using GMTSAR [53], and interferograms were unwrapped with the statistical-cost network-flow algorithm SNAPHU [46]. We studied the period between January 2015 and December 2019 by analyzing two ascending and two descending orbits (for a total of four datasets for each landslide). The orbits used are the following: track 15 and 117 (ascending); Track 168 and 95 (descending). In general, we obtained better quality results in terms of coherence from tracks 117 and 95, which is why the results described here are obtained from those datasets. We performed an areal InSAR analysis over the whole study area to identify landslides showing deformation signals with a certain temporal continuity. Then, to analyze the extent and time interval of the deformation in more detail, a site-specific analysis was developed for each landslide. The topographic phase was calculated and subtracted [11; 45] by using a digital surface model (2 \(\times\) 2 m\({}^{2}\) DSM, provided by the Emilia Romagna Region Services). Large-scaleatmospheric noise was treated and reduced by selecting a stable reference area as close as possible to each investigated landslide. All the stable reference areas used in the different analyses were selected in areas outside the deforming regions, typically w.r.t. anthropic features (e.g., stable buildings) located near the landslides of interest. In addition, Gaussian and Goldstein filters [54] were applied to reduce the noises, eliminate phase differences related to other factors (atmospheric, etc.) and enhance the deformation signals due to landslide displacements. In periods characterized by high displacement rates, unwrapping problems continued to occur despite the acquisition frequency of six days. Only in these cases, we adopted a method proposed by [PERSON] et al. 2015 [22], which consists of using a deformation model to aid the unwrapping problem. Both for the areal and the site-specific InSAR analyses, approximately 3000 interferograms were processed and inspected carefully. The inspection is accompanied by a coherence measurement, which is generally satisfactory given the small size of the temporal baseline. Based on our experience, the evaluation of the average coherence is only partially helpful, and the visual inspection of the interferograms is crucial. In fact, interferograms with high coherence values may contain noticeable residual noise and be discarded, while interferograms with low coherence values may contain displacement information that includes them in the selected dataset. Only the interferograms, where residual noise was relatively low and where the phase ambiguity was correctly solved, were used in the final analyses. The temporal baselines of selected interferograms have intervals of 6, 12 and 24 days, while the spatial baselines never exceed 200 m.