Delivering the UK's largest digitisation job
January 17, 2019
In 2018 Sensat has safely mapped the entire Phase One route of the proposed HS2 rail line from London to Birmingham to create a fully digital simulation, supporting the planning of the project. The corresponding data set is made up of 18.4 billion data points, producing visuals of the terrain which are more than 100 times more accurate than satellite data.
High Speed Two (HS2) is the new £53bn high speed railway being built in the UK. It will comprise more than 530 km of new track. Phase One is scheduled to open in 2026 and Phase Two, with additional stations in Manchester, near Nottingham and in Leeds, in 2033.
The project and challenges
A digital, topographical visualisation was required to plan enabling works for Phase One. However, using traditional static 3D laser scanners would have taken several months. The client also wanted to avoid the need for constant landowner engagement to perform the data capture, which had already caused hold-ups. Also, some areas were completely inaccessible for information gathering purposes using traditional means. This posed high health and safety risks to ground based survey teams. Moreover, the existing site imagery and topography data was also out of date, and therefore, misleading.
Above all, being able to work collaboratively on such a large, complex job, involving many different contractors, was key.
The corresponding data sets for HS2 were made up of a staggering 18.4 billion data points, giving the client a complete understanding of the terrain that can easily be more than 100x more accurate than satellite data.
Sensat’s latest aerial mapping techniques allowed to reduce the time on site by over 200%
Sensat was uniquely positioned to map the route because of its permission from the Department for Transport to fly drones up to 12 km away from a pilot, where legislation normally limits this to 500 m, or “within line of sight”. This made it possible to capture data much more efficiently, covering over 23km per day to a width of 200 m, and an accuracy of 50 mm.
To support detailed engineering design, 2D orthomosaics were also delivered, from which ancillary datasets for the Digital Terrain Model (DTM) and other CAD outputs could be produced.
The vast linear nature of the project meant the curvature of the earth had to be reflected in the data output. A snake grid projection system converted the data into the correct format. An internal team at Sensat, led by an ex-GIS professor, worked on quality assurance to ensure that the corrections were accurate and satisfied all project requirements.
Sensat’s cloud based platform Mapp allowed everyone to easily visualise and interact with the enormous datasets in one place, and thus enabling a collaborative working environment between all stakeholders involved.
Faster: To digitise 147 km of land using a traditional data capture method would have taken many months, including high-risk works like walking and climbing across difficult rural terrain. The use of Sensat’s latest aerial mapping techniques allowed to reduce the time on site by over 200% and minimise health and safety risks.
More accurate: The corresponding data sets for HS2 were made up of a staggering 18.4 billion data points, giving the client a complete understanding of the terrain that can easily be more than 100x more accurate than satellite data. Visualised on Mapp, interaction with the large data sets was made easy and intuitive.
147 km point cloud hosted on Mapp
Mapp brings all the contractors and clients closer. Its ease of use and accessibility reduce communication barriers, improve collaborations, and ultimately allow for more informed decision-making process based on real HS2 data. Looking ahead, HS2 can make use of the drone-captured data to calculate the volume of earthworks faster and cheaper than traditional methods where surveyors have to walk the route. They can also be deployed to make accurate comparisons of “as-designed” versus “as-built” structures to optimise project control and minimise cost and time overruns.
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