## 4 Results  
### Monitoring Data Processing  
In this chapter, we present the results of the topographic monitoring system installed by ARPA Piemonte from 2006. The monitoring network is composed of four topographic benchmarks and two laser distance meters that are periodically measured (up to 3/4 measurements per year) (Figure 9). The results of laser distance meters and topographic benchmarks are in agreement and show the long-term movement trend of block A toward NE, with a rate of 1/2 mm/year. We also consider the vertical displacement (downward) and the full displacement rate is 2/4 mm/year (Table 4) that are in good agreement with available Persistent Scatterer (PS) InSAR data of the Radarsat satellite (10 B). The time series of topographic data seems to show seasonal oscillations that are in agreement with the documented seasonal cycle: measurements made after the winter show higher displacement then summer measurements. However, due to the few and not constant measurements per year and  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Displacement Type** & **R** & **ST** & **GT** \\ \hline Short term (Hourly to daily) & \(\geq\)4 & \(\geq\)2\(\sigma\) & Not yet defined \\ Long term (Monthly to semester) & \(\geq\)4 & \(\geq\)2\(\sigma\) & \(>\)3 mm/100 days (\(\approx\)11 mm/year) \\ \hline \hline \end{tabular}
\end{table}
Table 3: The Ratio test (R) threshold, the statistical (ST), and the geological (GT) thresholds used for a Madonna del Sasso case study.  
Figure 8: An example, using a simulated dataset, of daily solution for vertical displacement (Delta h). In the Day of Year 324, the displacement (green dot) is an insight into the statistical threshold (\(\pm\)2\(\sigma\) on the regression line) and below the geological threshold (GT). This means that normal conditions (green light–flag = 1). The days 316 and 317 have no measure because the ratio test was \(<\)4.  
the limited displacement rate, it is hard to validate the seasonal oscillation because the entity of the oscillation is very close to the signal/noise limit (Figure 10A).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Instrument** & \multicolumn{3}{c}{**Topographic Benchmarks**} & \multicolumn{2}{c}{**Laser Distance**} & \multicolumn{2}{c}{**InSAR**} \\ \hline
**Name** & **T0** & **T3** & **T2** & **T1** & **D2** & **Radarsat PSVLOS** \\ \hline
**Temporal Span [Year]** & \multicolumn{3}{c}{**2006–2019**} & \multicolumn{3}{c}{**2009–2018**} & \multicolumn{2}{c}{**2003–2009**} \\ \hline Vel\({}_{\text{xy}}\) [ mm/year] & 1.4 & 1.2 & 2.1 & 1.7 & - & \\ Azimuth [\({}^{\circ}\)] & 55 & 73 & 55 & 64 & - & 80 LOS \\ Vel\({}_{\text{xyz}}\) mm/year & 2.9 & 2.6 & 3.2 & 3.4 & 2.7 (LOS) & 2.9 LOS \\ Dipl[\({}^{\circ}\)] & 61 & 63 & 50 & 58 & - & 56 LOS \\ \hline \hline \end{tabular}
\end{table}
Table 4: Displacement rate, azimuth, and dip measured by topographic benchmark, InSAR and laser distance meter monitoring of ARPA Piemonte (measured along the line of sight—LOS).  
Figure 9: Displacement rate map measured by ARPA Piemonte instruments: laser distance-meters (period 2009–2018), InSAR (2003–2009), and the topographic network (2006–2019). The map also shows the location of the new low-cost GNSS systems.  
Figure 10: (**A**) shows the Time Series of 2D (horizontal) displacement of the topographic benchmarks (T0, T1, T2, T3) and the linear regression represented as red dashed line for T2 (the equation is f(x) = 0.006\(\mathrm{x}-224.3\); R\({}^{2}\) = 0.97; (**B**) shows the 3D time-series displacement of: benchmark T2; the laser distance meters D2; the PS InSAR data (PS id: AO7 ND Radarsat ascending dataset) with its linear regression represented by the black dashed line (the equation is f(x) = 0.008\(\mathrm{x}-295.3\); R\({}^{2}\) = 0.77).