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Coastal Case Study
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The use of unmanned aerial platforms to carry out photogrammetric surveys of coastal areas have many benefits, especially in the ability to capture a high density snapshot of a site within a small time window (for example between tides).

In this study we look at the processing considerations and requirements, specifically around the presence of vertical features in the survey area.

The survey was carried out using a fixed wing unmanned aircraft flying at 350ft, a methodology picked to maximise coverage whilst retaining an appropriate level of detail and accuracy. The adavantages/disadvantages of using, for example, a multirotor aircraft are not detailed in this study.

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The survey area

This case study was carried out on the sea wall and surrounding areas at Hartlepool in the north east of England. The site was chosen specifically for the sea wall and nearby road, to allow for comparison of aerial data with ground survey along vertical features of varying height.

Whilst studies often concentrate on the accuracies of easily identifiable features, this study concentrates on the accuracies which can be obtained/expected in more complicated scenarios.

Surface detail in open areas has been included as a comparison against areas of vertical features.

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Methodology

The aerial survey was carried out with a QuestUAV Q200 fixed wing SUA. Photographic data was stored onboard, along with camera position and flight data. A single 18 minute flight was required to cover the 1000m by 500m site, of which 10 mins was capturing imagery.

Before flying ground control points were identified and marked. These were placed across the survey area and were surveyed using GNSS equipment referencing an on-site base station. Over 100 check points were also taken across site, covering the beach, wall/footpath, road and vegetated areas. These points were to be used for accuracy analysis on the final models and were kept separate during the data processing stage.

After raw models had been produced from the aerial data, gridded data and string levels were extracted to produce various models for analysis.

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Findings

Two models were used for comparison. The first was a basic 1m grid generated from the original point cloud. For data analysis, heights at check point locations were interpolated from nearby grid points. The second model used this 1m grid as a starting point, but had additional string detail manually added from the aerial data.

These models were compared to the 100 ground surveyed check points. Check points were categorised by surface/feature type, the RMSE differences were calculated for each type. These figures were then tabulated and are presented in the table below.

RMSE
basic point cloudstrung model
Hard surface inc. beach*0.050.04
Hard surface exc. beach*0.040.04
Soft surface*0.050.05
Points close to tall vertical feature0.650.04
Points close to low vertical feature0.080.05

*categories exclude points near vertical features

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Conclusion

It is important to have a clear vision of what you are looking to achieve before commisioning a coastal survey using aerial methods.

If your concern is only for height data, the speed of data capture is important and accuracies of up to 5cm are suitable for your project, then a simple SUA survey will be the quickest and most cost effective solution. This may be provided as height gridded data or, with cost implication, as a combined spot height and stringed model.

For projects which require higher accuracy information for critical features, the addition of ground survey (for example for kerblines) may provide the optimal solution.

Consideration should also be given to the size of survey area. Very small or very large sites may be most effectively surveyed using alternative methods (especially if imagery/orthomosaic aren't required).