# The Use of Earth Observation Data for Railway Infrastructure Monitoring--A Review
## 3 EO-Based Railway Infrastructure Monitoring: Literature Review
### Comparative Analysis of EO Data Use in Railway Infrastructure Monitoring
The proposed tunnel monitoring and stability assessment method forecasts the tunnel's stress condition, aiding in assessing its stability and providing guidance for engineering construction and geological prediction. [PERSON] et al. [55] jointly applied time-series InSAR (TSInSAR) and BeiDou Navigation Satellite System (BDS) technologies to identify and monitor side slope deformations in TZ along high-speed railways based on Sentinel-1A data. It was observed that TSInSAR can effectively identify unstable side slopes, while TSInSAR, BDS, and UAV monitoring results showed good agreement. Rainfall was found to significantly influence side-slope deformation. The concept of displacement thermal sensitivity (elastic displacement response to a unit change in temperature) can be used to monitor bridge structural behavior. It was introduced by [PERSON] et al. [19] and tested on bridges that link the cities of Montreal and Longueuil and the cities of Montreal and Saint-Lambert in Canada. Both bridges had decks and superstructures of similar thermal expansion coefficients. Displacement thermal sensitivity was monitored using InSAR technology applied to satellite data obtained over two selected bridges and a comparison of displacement measurements from different satellite platforms (RadarSat-2 vs. Sentinel-1) and different sources (e.g., GPS elevation measurements). The authors also developed a visualization and early warning tool that uses defined threshold levels for issuing alerts. [PERSON] et al. [53] investigated the possibility of persistent scatterer interferometry (PSI) technology as an innovative monitoring technology for monitoring the structural integrity of a railway bridge. The study used X-Band COSMO-SkyMed images provided by the Italian Space Agency to detect structural displacements in the Rochester Railway Bridge (UK). The results identified the presence of multiple persistent scatterers (PSs) over the bridge, which proved useful to achieve a more comprehensive monitoring methodology. [PERSON] et al. [32] applied SBAS-InSAR technology and Sentinel-1A data for monitoring deformation of a large-span railway bridge (Ganjiang Super Bridge, China). The deformation results were combined with bridge structure, temperature, and riverbed sediment scouring data. The dataset included Sentinel-1A images from September 2018 to September 2020 with a month's image-sampling interval. Results from SBAS-InSAR and PS-InSAR methods were compared to verify the experimental results. [PERSON] et al. [59] used high-resolution Cosmo-SkyMed satellite imagery and the DInSAR technique for monitoring the stability of a railway bridge over the Volturno river at Triflisco (Campania) in Italy. The results obtained showed fairly stable conditions on the studied railway and railway bridge. It was observed that most of the line of sight (LOS) changes were because of seasonal temperature variations. To get a detailed inventory of the railway area in the southeast of Berlin for urban ecological monitoring and VG assessment, geometrically corrected panchromatic and multispectral QuickBird satellite data were used [39]. This was accomplished by extracting rail tracks, separating different states of vegetation succession, or differentiating between surface types with varying degrees of impermeability based on spectral information. Optical satellite image data were also used by [PERSON] and [PERSON] [34] to determine and evaluate the degree of threat to railway infrastructure from falling trees in the Liberec Region of the Czech Republic. The degree of threat was identified according to three parameters:the height of tree stands, species composition, and vegetation health. Data for the first parameter were provided by the Forest Management Institute of the Czech Republic, while the species composition was assessed using LANDSAT-7 satellite images. Vegetation health was assessed based on the NDMI index extracted from Sentinel-2 images. The result of analyzing these three parameters was a compound Vegetation Threat Index for Railways (VTIR).