Drone Photography and Video for Surveying Case Studies

Case Study 1 – Large Commercial Property Roof Survey

We were tasked with doing a condition survey of all roof sheet joints and gutters for debris as you can see from the image of the sheet, there is rust forming on the join of the edge of the steel sheet. We took over 1000 images during an extensive drone survey. Using our powerful reporting system we then went through every image, highlighting any defect we found – be it rust damage, vegetation or debris in the gutters.

Case Study 2 – Lighthouse Corrosion Damage Survey

In these set of images of the lighthouse dome we found that the dome had previous corrosion damage that had just been painted over. Although this will slow the corrosion, over time when the paint deteriorates, or if water ingress occurs, this will ultimately hold moisture and create more corrosion.

Case Study 3 – Surveying Harbour Walls

We were tasked with surveying the harbour walls at Falmouth for potential movement. We took a day to go down to the harbour and do a pre-flight site survey to get accustomed to the area and the challenges it presented. Whilst onsite we placed some GCP (ground control points) and collected their GPS location using Emlid Reach RS2, Emlid Reach RS+ and Emlid Reach M+ attached to our Phantom 4 Pro and M600 Pro drones.

We returned during a spring tide so that the water would be at its lowest point. On arrival we set up our Emlid RS2 as a base station so that it could start recording its GPS location. We then walked around the harbour walls laying down our GCPs and using our Emlid Reach RS+ as a rover to collect GPS Points from each GCP. As the tide went out we captured images of the entire harbour wall from sea bed to tarmac. We set the drone to fly over the site using specialist software for automated flight and capturing imagery of the harbour walls whilst logging its GPS location using the Emlid Reach M+. When combined with our other survey equipment this solution provides millimetre level accuracy!

We then sent all our data to the client. They then processed it to get an accurate RMS (Root Mean Square). Finally, they created a point cloud from the 48 megapixel images.