Monitoring rail infrastructure and trackside vegetation

• Trackside vegetation: Copernicus Sentinel-2 images have a resolution of 10 m and a revisit time of five days Source: ESAEuropean Space Agency (ESA), accessed 6 October 2026European Space Agency (ESA)Sentinel-2 (mission page)accessed 6 October 2026Open source (opens esa.int). Vegetation indices such as NDVI, calculated from red and near-infrared light, show vegetation density and changes in plant health Source: USGSU.S. Geological Survey (USGS), accessed 6 October 2026U.S. Geological Survey (USGS)Landsat Normalized Difference Vegetation Indexaccessed 6 October 2026Open source (opens usgs.gov). A time series shows where vegetation grows towards the line.
• Ground deformation: radar interferometry provides millimetre-scale measurements of the subsidence and landslides that affect railway lines, and the European Ground Motion Service provides these data free of charge Source: ESAEuropean Space Agency (ESA), 26 July 2022European Space Agency (ESA)Tap into Europe in motion (European Ground Motion Service)26 July 2022Open source (opens esa.int). How it works is explained in monitoring ground motion with InSAR.
• Flood risk: the European Flood Awareness System produces probabilistic flood forecasts with lead times of up to ten days, and its notifications go to national, regional and local authorities Source: EU SpaceEU Space Programme (Copernicus Observer), 29 January 2025EU Space Programme (Copernicus Observer)Observer: How the EU Space Programme supports flood preparedness, the role of the European Flood Awareness System (EFAS)29 January 2025Open source (opens eu-space.europa.eu). Flood hazard along a line can be mapped in advance, as in mapping flood risk.

Radar satellites such as Sentinel-1 acquire images day and night and through clouds Source: ESAEuropean Space Agency (ESA), 3 November 2025European Space Agency (ESA)Sentinel-1 mission… did you know?3 November 2025Open source (opens esa.int), so ground motion monitoring does not depend on the weather.

1. Define the corridor: the lines to monitor and a buffer on each side of the track.
2. Build the layers: a vegetation time series from optical images, ground motion points from radar, and hazard layers for floods and landslides.
3. Set thresholds: for example vegetation within a distance of the track, or movement above a rate in millimetres per year.
4. Rank the sections: each section of the line gets a priority from the layers it crosses.
5. Inspect and maintain: crews go first to the sections at the top of the list, and their findings flow back into the thresholds.

Satellite data complement the measurements the railway already makes. In-service trains equipped with sensors increasingly monitor track geometry, linked with GNSS for accurate location Source: EUSPAEU Agency for the Space Programme (EUSPA), 26 May 2026EU Agency for the Space Programme (EUSPA)EU Space Market Report 2026, Issue 126 May 2026Open source (opens euspa.europa.eu), and drones equipped with GNSS deliver high-resolution imagery of catenary lines, track geometry and vegetation; RFI in Italy, for example, integrates drones and GNSS to monitor catenary and track geometry Source: EUSPAEU Agency for the Space Programme (EUSPA), 26 May 2026EU Agency for the Space Programme (EUSPA)EU Space Market Report 2026, Issue 126 May 2026Open source (opens euspa.europa.eu).

Network-wide monitoring changes how inspections are planned, so it has to fit the maintenance process. In a strategy engagement we check which risks along your lines satellite data cover best. We then write the requirements: layers, thresholds, update rate and the interface to your asset management system.

More on requirements and procurement

The marketplace on Spacegraph, our discovery platform, has a use-case category for infrastructure integrity and an industry category for transport and logistics.