## 5 Satellite Remote Sensing Techniques for Infrastructure Monitoring
### Stand-Alone Applications of Satellite Remote Sensing for Infrastructure Monitoring
#### 5.3.1 Roadways  
Linear infrastructure in rural environment contexts are amongst the most reflective targets for SAR transmissions, triggering the formation of many PSs for the PSI analyses. This implies that the PSI technique can be inherently effective in the monitoring of major \begin{table}
\begin{tabular}{c c c c} \hline
**Roadways,** & **Research** & **Innovation** & **References** \\
**Highways** & **Motivation** & & \\ \hline \multirow{4}{*}{Road network monitoring} & Integration of an automated PSI processing chain and GIS to extract vertical deformations in urban road networks & [84] \\ \cline{2-4}  & Subsidence monitoring and displacement mapping & PSI to extract LOS deformations from road infrastructure assets & [85; 86; 87; 88; 89; 90] \\ \hline
**Bridges** & & & \\ \hline \multirow{4}{*}{Health monitoring} & Extended PSI to extract linear and seasonal components of bridge deformations/comparison with levelling measurements/model thermal and structural deformations & [91; 92; 93; 94; 95; 96; 97; 98] \\ \cline{2-4}  & Pre-failure assessment & PSI to evaluate possible pre-failure bridge deformations & [99; 100; 101; 102] \\ \hline
**Airport runways** & & & \\ \hline \multirow{4}{*}{Subsidence monitoring} & Displacement evaluation on runways & [103; 104; 105; 106] \\ \cline{2-4}  & Subsidence monitoring & Geostatistical analysis on PSI and comparison with levelling data & [107; 108] \\ \hline
**Railways** & & & \\ \hline \multirow{4}{*}{Health monitoring} & Health monitoring & Multi-geometry PSI to extract railway vertical/transversal deformations & [109; 110] \\ \cline{2-4}  & Displacement monitoring & Comparison between PSI-based railway LOS deformations and temperature data & [111] \\ \hline \end{tabular}
\end{table} 
Table 2: PSI Applications: Stand-alone use of satellite technology for transport infrastructure monitoring. pavement distresses (e.g., rutting, deformations and settlements) in roadways. Several studies on the implementation of PSI for road infrastructure monitoring are reported in the literature. This demonstrates the interest of the scientific community in applying PSI techniques for the detection of damage and the identification of sections affected by significant displacements. In [84], a DInSAR analysis implementing the PSI and the SBAS approaches was carried out to detect displacements in the LOS of several urban motorways in Rome, Italy, including Motorways A1, A12, A24, A90 and A91. Both Sentinel-1 and COSMO-SkyMed SAR images were processed to detect PSs on the motorways and to identify sections affected by high subsidence, and were classified based on the PSI results. [PERSON] et al. [85] implemented four widely used time-series deformation InSAR models (i.e., the multi velocity model (MVM), the permanent velocity model (PVM), the seasonal model (SM) and the cubic polynomial model (CPM) to measure the long-term ground deformation after construction of a road embankment on a soft clay subgrade. The SBAS-InSAR technique with TerraSAR-X satellite imagery was applied to generate the time series deformation data on the studied highway. Levelling data were also used to validate the experimental results, confirming that the InSAR method can reach a millimetre-level accuracy. [PERSON] et al. [86] demonstrated the potential of the high-resolution PSI approach \"SPINUA\" in assisting asset owners with the assessment of structural hazards. Examples of PSI applied to monitor post-construction performance of engineering structures in Italy are also presented, including case studies on buildings and on the motorway Florence-Livorno. [PERSON] et al. [87] implemented the SBAS InSAR technique for the detection of land subsidence and pavement structural monitoring. A comparison between the International Roughness Index (IRI) and the backscattering coefficient (dB) of CSK SAR images was conducted, proving a slight correlation between these parameters. Results also showed an urbanised area where buildings and 65 km of pavement sections are affected by the risk of land subsidence.