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In 2018 Sensat successfully digitised a 52 km stretch as a part of the Triton Knoll wind farm project. The project aims to deliver renewable ‘green’ energy from the offshore wind farm via a buried electricity onshore cable line running from The North Sea to connect with the National Grid.
 

The UK is the world leader in offshore wind, with more installed capacity than any other country. Already, offshore wind powers the equivalent of 4.5 million homes annually and will generate over 10% of UK electricity by 2020. Renewable energy is also an exciting industry for Sensat to be involved in, with growth predicted to increase by ⅕ by 2023.

The project and challenges

Sensat were commissioned to map the entire onshore portion of the cable route from landfall to the proposed Triton Knoll substation. The client needed highly accurate data to verify existing LiDAR survey data which had large degrees of variances of around +-100 mm. This needed to happen before Triton Knoll could go ahead with the construction of the electricity transmission cable for the onshore aspect of the Wind Farm development.

After assessing various survey options, including the viability of using a helicopter survey, it was determined that utilising UAVs was the most suitable way forward. 
 
Key stakeholders involved in this project were local farmers who owned a large proportion of the land that the works were going to take place on. As the land, and especially the soil around the Triton Knoll area was very valuable, a high priority was to recreate the surface accurately and efficiently, making sure the excavated areas were returned relatively undisturbed.

The solution

Sensat successfully digitised the whole 52 km utilising UAVs. This had some major advantages; compared to helicopters, UAVs produce 1000 fewer lifecycle emissions per km and have less impact on surrounding wildlife. The use of Sensat’s latest aerial mapping techniques also allowed to reduce time on site by over 200% and minimise health and safety risks, compared to traditional surveying. 
 
Making use of photogrammetry (click here to learn more), Sensat generated full-colour 3D and 2D models of the terrain that were far easier to visualise and interpret compared with the usual UAV LiDAR. Photogrammetry offered a greater range of data outputs, with increased accuracy of less than 50 mm on the XYZ values. This can be used at various stages of a project, whereas UAV LiDAR data can be confined to singular stages of a project due to its lack of versatility. 
 
A spot grid was also delivered to support the planning of the project and provide a better understanding of upcoming earthworks. Combined with the point cloud and orthomosaic, and the ability to visualise large data files easily within Sensat’s platform Mapp, the client was able to analyse and discuss the data in a wider context.

The benefits

Accurate: The various data sets gave the client a complete understanding of the terrain that can easily be more than 100 x more accurate than satellite data. Sensat’s industry-leading UAV capabilities and quality assessment allowed to deliver data with less than 50 mm accuracy.


Cloud-based collaboration: Sensat’s cloud-based platform Mapp allowed everyone to easily visualise and interact with the enormous datasets, made up of over 1.9 bn data points, in one place. This enabled a collaborative working environment, which allowed all stakeholders to view and discuss the data in the context of its real-world environment.

Moving forward

Mapp brings all stakeholders and clients closer together. Its ease of use and accessibility reduce communication barriers, improve collaborations, and ultimately allow for a more informed decision-making process based on real site data. Looking ahead, the client can also load the spot grid data onto their handheld GPS systems, allowing the team to measure the height of the land directly in the field to make sure the excavated area is returned to the same level.

Want to learn more on how to utilise UAV data for your project? 

Download the full case study below:

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