# Review of Satellite Interferometry for Landslide Detection in Italy
## 7 Final Remarks
The density of measurement points over an area is uneven. Due to the dependency of radar coherence on the dielectric characteristics of the ground, vegetated, smooth and snow-covered surfaces have null to very low density of points. This is an unsolvable issue that can limit the number of landslides to be investigated, or the amount of information obtainable for a single phenomenon. * _The geometric effects_. Foreshortening, layover, and shadowing are common geometric distortions in mountainous areas. Depending on the slope orientation with respect to the LOS of the sensor, \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Authors** & **Type of analysis** \\ \hline \hline \multirow{5}{*}{**Pioneering Applications**} & [PERSON] et al. [25] & First application of a PSI approach to characterize the \\  & & Ancona landslide \\ \cline{2-3}  & [PERSON] \& Tesauro [141] & One of the first examples of integration between \\  & & ground and satellite data \\ \cline{2-3}  & [PERSON] et al. [33] & First example of landslide inventory update \\  & & supported by InSAR products at the basin scale \\ \cline{2-3}  & [PERSON] et al. [27] & First integration between C-band and X-band InSAR \\  & & data for landslide studies \\ \cline{2-3}  & [PERSON] et al. [121] & First example of integration of InSAR results in \\  & & landslide models \\ \cline{2-3}  & [PERSON] et al. [126] & Definition of the concept of a “landslide activity \\  & & matrix” for landslide state of activity and \\  & & intensity definition \\ \cline{2-3}  & [PERSON] et al. [132] & Definition of the concept of an InSAR “hot-spot” for \\  & & landslide mapping activities \\ \cline{2-3}  & [PERSON] et al. [185, 186] \& First approaches for time series analysis aimed to \\  & [PERSON] et al. [89] & manually and automatically detect trend changes \\ \cline{2-3}  & [PERSON] et al. [32] & First worldwide example of nation-wide \\  & & interferometric coverage \\ \hline \hline \multirow{5}{*}{**Recent Advancements**} & [PERSON] et al. [51] & Landsible susceptibility map refinement by means of \\  & & InSAR results \\ \cline{2-3}  & [PERSON] et al. [188] & LaDIS validation approach \\ \cline{2-3}  & [PERSON] et al. [97] & Earthquake-induced landslide mapping \\ \cline{2-3}  & [PERSON] et al. [160] & Definition of fragility curves derived from \\  & & InSAR data \\ \cline{2-3}  & & Landslide state of Activity Maps by \\  & [PERSON] et al. [84] & combining multi-temporal A-DInSAR data \\  & & (LAMBDA) approach \\ \cline{2-3}  & [PERSON] et al. [182] & Persistent Scatterers Interferometry \\  & & Hot Spot and Cluster Analysis (PSI-HCA) \\ \cline{2-3}  & [PERSON] et al. [139] \& & Amplitude-based techniques for landslide \\  & [PERSON] et al. [118] & post-event analysis \\ \cline{2-3}  & [PERSON] et al. [74] & Hot-spot approach aimed to landslide intensity \\  & & mapping at the regional scale \\ \cline{2-3}  & [PERSON] et al. [187] & Ground motion monitoring system based on a 12-day \\  & & update of InSAR products over the Tuscany region \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of the pioneering applications and of the most recent advancements of InSAR for landslide studies in Italy. some landslides could be detected, whereas others could not be in any case monitored. Thus, it is fundamental to know a priori whether our target landslides are measurable or not. The creation of a visibility map for the area of interest is a simple but effective way to estimate this before data processing [73,88]. * _The one-dimensional nature of the results._ InSAR provides the estimate of one component of the real displacement vector, i.e., along the LOS direction. This implies that the 3D motion of a landslide can be viewed from only one point of view. Since the kinematic of a landslide is complex, a good practice is to derive the vertical and the east-to-west horizontal components of motion from double geometry InSAR data [e.g., 96].