Below water (bathymetric) survey data is a critical component of any hydraulic model as well as being critical for carrying out volumetric change analysis, however due to the difficulties involved in collecting this data at high resolutions, many practitioners rely on widely spaced cross section surveys to represent the below water surface.

With rapid advances taking place in drone technology as well as significant advances in the field of computer science relating to ‘artificial intelligence’ and ‘machine learning’, we have been actively exploring techniques to enable the rapid and cost effective capture of bathymetric data. The final output of our technique is an accurate, seamless DEM of the above and below water bed elevation.

CPW Intake Bathymetry - Vertical.png

Led by Matthew Gardner, who has been working professionally in the UAV sector since 2015, our team have developed a range of workflows and techniques for capturing bathymetric data using a standard drone equipped with only a high resolution digital camera.  The results are proving to be very promising with our techniques now having been used commercially throughout New Zealand.

We have several techniques which are suitable for different types of waterways.  Whilst the workflow for each job differs slightly, generally we are using two overall techniques, depending on the water characteristics.  These are:

Lake Coleridge Ortho.png
Resulting DEM from optical bathymetry technique

Resulting DEM from optical bathymetry technique

Optical Bathymetry

This technique works by finding a mathematical correlation between colour and depth.  Each pixel in a digital photograph has a Red (R), Green (G) and Blue (B) value.  In essence we find a correlation between R,G,B and depth and then apply this correlation to each pixel of the orthophoto creating a digital elevation model (DEM) of depth.

Our techniques are based on international research and literature however we have further developed these techniques by incorporating automatic image recognition tools and machine learning algorithms into our workflow in order to improve the overall quality and reliability of our results.



Ashley Correlation.png

Refraction:

For shallow water bodies with relatively clear water, such as braided river systems, we have found that we are able to utilise techniques which incorporate an allowance for refraction. These techniques utilise modern photogrammetric techniques (specifically the Structure from Motion Algorithms) and require the waterway to be flown at a lower altitude and with more overlap than is the case for the optical bathymetry technique.  In the right water conditions, we are able to achieve a very accurate bathymetric DEM using this technique.  To date, we’ve found these techniques are able to work well in depths up to 2m.

CASE STUDIES

Click on the following images to see more details about specific case studies.

Lake Coleridge, Canterbury

Lake Coleridge, Canterbury

Ashley River, Canterbury

Ashley River, Canterbury

CPW Intake Canal, Canterbury

CPW Intake Canal, Canterbury

We would love to have more opportunities to explore and develop these techniques further. If you are interested in learning more about these techniques or trialing them at your site, please get in contact with Matthew Gardner.