## 2 I-Pro MONALISA: A New Semiautomatic GIS Approach
### Detection of ground instability kinematics  
To characterize kinematics of slope instability phenomena, starting from geological and geomorphological settings, and available landslide inventory maps, a knowledge of the main characteristics, such as velocity and boundary, is required. In particular, as to define landslide intensity parameter, the mean displacement annual rate measured in the last year through the processing of SAR images has been taken into account.  
The procedure to detect landslides kinematics interacting with linear infrastructures is developed according to the following phases:  
1. DInSAR processing: SAR images dataset has been processed by means of Coherence Pixels Technique [44]. The analysis has been carried out by exploiting the Temporal Sublook Coherence (TSC) approach [45] for pixel selection. Such technique (CPT-TSC), based on the analysis of phase difference in interferometric stacks, identifies reliable scatterers by measuring their multitemporal coherence related to the phase stability. The interferograms, defined as the phase difference between two different acquisitions, are generated to further reduce decorrelation effects associated with possible coherence losses, typically due to topographic distortions, atmospheric patterns, and radiometric distortions. The exploitation of DInSAR methods, using multi-temporal stacks of SAR images, allows to remove all these contributions and to isolate the phase related to the displacement occurring between the two acquisitions. As a result, displacement annual rate and time series along \"LoS' direction of each identified scatterer have been obtained. Subsequently, the real slope displacement is calculated through the ratio between 'LoS' value and \"C\" correction factor;
2. creation of a \"buffer\" zone and a \"fishnet\" grid: A buffer zone has been created along the linear infrastructure defined from the available digital topographic map and only scatterers identified within such area have been considered to investigate landslides intensity also in the surrounding areas; furthermore, inside it a \"fishnet\" grid with pixel size depending on the spatial resolution of interferometric products, has been implemented;
3. geostatistical analysis: Post-processing of SAR data is a crucial step for the identification of the anomalous areas [46]. Aimed to discriminate stable from unstable targets, a displacement rate threshold has been assessed by calculating a coefficient of variation (CV) of each target, given by the ratio between the standard deviation \(\sigma\) and the mean velocity module \(\left|\mu\right|\), for all selected scatterers identified inside the buffer zone. From the analysis of the CV distribution it is possible to detect velocity threshold as a value for which standard deviation is higher than the mean velocity value [20]. The comparison of velocity threshold value with the movement rate of each radar target identified inside the fishnet grid provides scatterers which can be considered unstable;
4. cluster analysis: As for the optimization of the results, a clustering process is also very useful. DInSAR processing results, in fact, consist of a high amount of points related to a deformation measurement: Such post-processing allows to identify, within fishnet grid, possible \"anomalous\" areas where similar displacement rate values tend to be clustered, by defining an \"Homogeneity Index\" (HI) which is the ratio between the number of moving targets and the total number of targets within each pixel of fishnet. Only pixels of fishnet grid with at least the 50% of \"moving\" targets inside have been considered as unstable, thus obtaining a map of stable/unstable pixels [20];- Level I (green color): Pixel stable and outside from the officially mapped landslide;
- level II (yellow color): Pixel stable within the officially mapped landslide;
- level III (orange color): Pixel unstable and outside from the officially mapped landslide;
- level IV (red color): Pixel unstable and within the officially mapped landslide.