Better from Above: How Satellites Revolutionize Track Maintenance

Better from Above: How Satellites Revolutionize Track Maintenance
Address: LiveEO GmbH
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LiveEO GmbH

Better from Above: How Satellites Revolutionize Track Maintenance

A revolution of sorts is taking place in Earth observation. The number of satellites in orbit is going to increase from about 8,000 to 57,000 by 2029. Along with this expansion comes a massive increase in higher-quality data, leading to new use cases for satellite imagery analysis. One of those use cases is identifying threats to linear infrastructure, including vegetation encroachment and ground deformation.

Vegetation around infrastructure networks, such as railway tracks, can cause severe problems for operations. Equally concerning are ground movements, with landslides or even derailments the result.
Traditionally, networks dealt with these risks by hiring individuals to perform manual inspections of the track. This demands both significant time and staffing, resulting in much higher costs for operating. Satellite-based monitoring provides high-frequency overviews of the entire network along with actionable insights for segments that demand immediate attention.

Satellite Data & AI- Powered Vegetation Management Make a Difference

LiveEO analyses vegetation encroachment to railway tracks using satellite data. The approach makes grid-wide up-to-date overviews of vegetation risk along the asset a reality.

The company has developed a vegetation classification system based on state-of-the-art artificial intelligence, which enables the continuous updating of satellite data to monitor vegetation and provide a better assessment of risk. The insights are directly accessible through LiveEO’s web and mobile app.

As a result, in many cases, networks no longer require manual, on-site inspections, depending on the software’s risk assessment. What was once monitored on foot, by car, or even helicopter can now be recorded and viewed from space. The data used for railway monitoring features spatial resolutions down to the sub-metre range.

The distance between vegetation and the assets is determinable through satellite data analysis. So too are multiple other parameters, all of which improve the risk classification—even the height of trees or even trees outside of the right-of-way are captured. Satellite analysis can also determine healthy trees vs. sick trees. High-resolution and multispectral data allow the system to identify different vegetation species.

Condition-based vegetation management supports the careful removal of trees that present a risk to the operability of any network. Despite this, climate change is unpredictable, and the severity of storms will likely increase vegetation falling into the right-of-way.

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