How Drone Topographic Survey Increase The Efficiency of Solar Plant Construction

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How Drone Topographic Survey Increase The Efficiency of Solar Plant Construction

In recent years, drones have become an indispensable surveying tool for everyone. Drone survey is the most efficient and quickest method to obtain topographical data. Drone accuracy can rival the traditional RTK survey technique and proven to rival the point density TLS technique. As the authorized distributor and service center of senseFly in the MENA area, we have in our possession the most comprehensive drone fleet capable of covering large areas in the shortest amount of time.

energiasolar
The construction of the Noor Abu Dhabi solar plant is one of our most significant projects. During the construction, each zone had its own pace, and various activities such as groundwork preparation, topographic survey, construction, screw and panels installation were happening simultaneously. Following the fully automated ground screen installation methodology, the construction speed increased tremendously.

The solar plant construction project was utilizing the fully automated Krinner ground screw installation to increase time efficiency. The Krinner ground screws come with a fully integrated software that could reduce solar installation time by 10-30%. The solution uses computer-aided design to plan the location and depth of each screw, then using the fully automated RTK-guided machinery, the screw is installed.

The Krinner solution requires a highly detailed topographic model to work on, but the ground point density must be more than 5 per square meter. Traditional surveying techniques would be tedious, inefficient, and lacking the accuracy necessary. Terrestrial laser scanning (TLS) could provide the required point density, but it is time-consuming and less flexible than a drone survey.

Ground Screws



The Drone Topographic Survey

Once all the initial ground preparation work is completed, the blocks are ready to be 3D constructed. The data was acquired by using senseFly eBee Plus drone at a GSD of less than 3 cm. In each flight, we can cover 3-5 blocks depending on the size and shape of each block. The data is then processed and delivered phase by phase, usually a day for each phase. Depending on the data's urgency, it is also possible to provide the data on the same day. Coordinating with multiple construction zones, many blocks from different zones could be covered on the same day; this flexibility is one of the critical advantages of a drone-powered solution.


senseFly eBee flight planning



The accuracy of 1 cm RMSEz

Following the latest data accuracy standard guidelines, developed by the American Society of Photogrammetry and Remote Sensing (ASPRS), in which RMSEx and RMSEz determines the vertical accuracy. At the project's initial stage, we delivered an elevation accuracy of 6 cm RMSEz. With the improved standard of operating procedures, we were able to improve the result to 1 cm RMSEz. The result of one of the flights for block 180 is shown below, where 24 checkpoints are used.

RMSE is the statistical verifiable measure of accuracy but, how does the actual accuracy look like in the real world?


Implementation of Drone Data

Using the topographic drone model, automated vehicles will start with screw location marking on the ground; this is where the ground elevation will be checked and compared with the drone data. The colours show the difference between drone topographic data and automated vehicles measured data. As shown in the colour table below, the points from light blue to yellow indicate the accuracy of 5 cm, which is a fascinating 89.4%! There are 313 points where the error is greater than 5 cm. From the orthomosaic, we can conclude that some of these errors are caused by the trenching activities along the road (North-East of the block). According to the contractor, the errors were also caused from soil movement from the automated vehicles moving about and from the robotic arm during the marking process. With our improved standard operating procedures, we reached an astounding 83% data accuracy on average for all the blocks.


Total of 2954 ground screw points, the errors are represented by using different colours.

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