For major metropolitan areas, rail networks are vital for daily commutes and transportation. One lost day of rail activity can have a large economic impact on major cities such as London. Because of this, GIS has been of interest to rail companies, NGOs, and governments attempting to minimize a variety of hazards that may affect the rail network. Common hazards include derailment, suicides by individuals on tracks, dangerous car crossings, and chemical spills.
Using GIS to Predict the Likelihood of Rail Hazards
One recent approach is GeoSRM, which is a collaboration between Southampton University and the Rail Safety and Standards Board in the UK, where the project is mapping a variety of hazards and uses stochastic methods to predict where likely hazards could occur. The approach uses high-resolution detail of the rail network and a large number of historical data collected to get a more precise understanding of where exactly on tracks given hazards could occur. Estimating risk is also critical for rail companies and insurance in transporting hazardous freight via rail, such as different types of chemicals.
Modeling Impact of Rail Hazards on Groundwater
GIS has been used to estimate what would happen to groundwater supplies and the estimated costs of cleanup by integrating groundwater data and chemical release rates to estimate how much contaminants are likely being spilled in given areas based on where freight trains are traveling. This provides a more sophisticated analysis since it looks at traffic for train travel along with physical environmental data and chemical release data. Forecasts also consider costs of cleanup given spillage in different regions and levels of contamination. Published industry models in this method were integrated with spatial factors such as groundwater and rail traffic to determine better estimates than standard industry estimates.
Other approaches utilize more generic hazards and apply network theory to determine how accidents or hazards affecting specific nodes, including those with high or low degrees of connectivity, could have larger impacts on the wider network. This is a type of vulnerability or resilience assessment of networks such as rail, as it identifies where the network is likely to be more or less disrupted by a given event. Such an approach could raise awareness with authorities to understand where resources should be placed that can best respond to hazards, given the wider network impact that some accidents may have in certain places.
 For more on the GeoSRM project, see: Gilchrist, Alex, Jay Heavisides, David Griffin, Oles Kit, Jason Sadler, and Jeremy Austin. 2016. “GeoSRM – Online Geospatial Safety Risk Model for the GB Rail Network.” IET Intelligent Transport Systems 10 (1): 17–24.
 For more on how hazard spill estimates are determined for given regions and effect on the environment, see: Saat, Mohd Rapik, Charles J. Werth, David Schaeffer, Hongkyu Yoon, and Christopher P.L. Barkan. 2014. “Environmental Risk Analysis of Hazardous Material Rail Transportation.” Journal of Hazardous Materials 264 (January): 560–69.
 For more on the approach to assess hazards using network theory, see: Dunn, Sarah, and Sean Wilkinson. 2017. “Hazard Tolerance of Spatially Distributed Complex Networks.” Reliability Engineering & System Safety 157 (January): 1–12.