Over four years, DTU Aqua researchers have investigated how to develop the best technology to keep an eye on the ocean's forests, the eelgrass. Drone overflights in particular have been tested, and drones prove to be able to deliver precision and a large overview of e.g. Natura 2000 areas, concludes the final report.
Eelgrass is an absolutely crucial part of the coastal marine environment – it is the ocean's forest, which provides habitats for fish and small animals and stabilizes the seabed. But the marine environment and thus eelgrass are under pressure and should be helped. Now researchers from DTU Aqua have found the best way to use new technology to map eelgrass areas in the sea around Denmark.
In the new DTU Aqua report Development of new tools for eelgrass monitoring in Natura 2000 areas the researchers conclude that "drones can contribute significantly to monitoring large areas of eelgrass habitats, as the drones deliver data with high spatial resolution and accuracy in a labor- and time-efficient manner."
Drones have been tested against the current method, where the spread of eelgrass is assessed based on point observations in the sea. In a test in an area of 100 hectares in the southern part of Lovns Bredning in the Limfjord, the researchers obtained over 100 percent more data on the eelgrass with drone observations than with point observations:
"What we have done is to compare how widespread eelgrass is calculated using traditional methods - that is, where you have point observations, which you then interpolate to the entire area - with drone flights, which actually look at the entire area.
That means that there is no interpolation here, everything is actually mapped. And here we find 111 percent more eelgrass in the test area than with the old methods," explains lead author of the report and senior researcher Mette Møller and elaborates:
"It is an example of how inaccurate the "old" methods can be in an area where the eelgrass is very dynamic and not necessarily easy to predict by simple interpolation of points."
Research and development over four years
The report's results come from the four-year project Development of techniques for cost-effective monitoring of eelgrass in Natura-2000 areas.
The project is financed by the European Maritime and Fisheries Fund and by the Ministry of Food, Agriculture and Fisheries under the program Fisheries, nature and environment - marine biodiversity and ecosystems.
The project was launched in June 2019 and completed in May 2023. Along the way, the project has also spawned a PhD thesis, which will be defended on Friday 12 January 2024
Easier assessment of eelgrass cover
Traditionally, spot observations of eelgrass and other underwater vegetation are made with divers and video surveys. It is important to monitor the condition of the eelgrass regularly and implement various measures, as eelgrass is vulnerable to the man-made impacts that occur in the coastal areas.
Divers and video surveys provide good data, but they are both time- and labor-intensive and, not least, what they can contribute on a larger scale is limited.
This is where recent years of technological development and the use of drones for environmental monitoring have come into play. In the report, the researchers explain how drones can now be used to develop a much more precise and area-based approach to mapping eelgrass.
An example of where drones are far easier to use than more demanding diver-based surveys to visualize eelgrass cover is in the work of restoring eelgrass. Here, drones can easily assess how transplanted eelgrass shoots are able to grow.
Higher accuracy and resolution
Concretely, the project has dealt extensively with flying drones, but underwater drones have also been investigated and work has been done to optimize eelgrass models, among other things. by implementing drone data instead of the traditional point measurements.
The underwater drones are used, among other things, in deep water, where drones in the air can have difficulty seeing through the water.
Important new knowledge is that the drone-based mapping of eelgrass delivers much higher accuracy and resolution compared to the current point observations. When the point observations are interpolated, they do not always agree with the actual eelgrass distribution.
It has also been found that you can optimize previously developed GIS tools by e.g. to implement drone-based data. It is a significant advance because the GIS tool is used to determine the potential distribution of eelgrass in connection with making impact assessments of fishing in Natura 2000 areas.
In the overall project, it has been investigated how well it works to use object-based image analysis, OBIA=object-based image analysis, to analyze the data that the drones collect over areas with eelgrass
The results showed that this type of image analysis is particularly useful for analyzing high-resolution drone-based data.
PhD thesis on drone monitoring of eelgrass
It is postdoc Aris Thomasberger from DTU Aqua who has written the PhD thesis Development of drone-based tools for the monitoring of submerged aquatic vegetation, as an offshoot of the four-year project on monitoring eelgrass.
The PhD's studies therefore coincide with the project report, but Aris Thomasberger is in his Ph.D. among other things more thoroughly into the image analysis part and the underlying in-depth methods for processing the image material that the drones collect.
In his Ph.D thesis, Aris Thomasberger has had the goal of investigating how to monitor larger areas more efficiently than current methods without compromising the level of detail in the data.
"We shed light on some of the most prominent uncertainties surrounding this rather new monitoring tool, which is drones, including aspects of data collection and analysis, ground validation procedures and the spatial extent in that the presented methods can be efficiently applied," says postdoc and PhD defender Aris Thomasberger, emphasizing that he has had particular focus on in his PhD:
"We for example tested and compared the performance of different machine learning algorithms used to analyze the obtained drone-based imagery. The result is a robust documentation of the analysis workflow for images obtained under different monitoring conditions, which will significantly reduce the time and effort spent on choosing the most appropriate data analysis set-up,” says Aris Thomasberger.
Drone-based methods should be part of future programs
Overall, in the drone monitoring of eelgrass project, it has been documented that when analyzing the data collected by the drones over areas with eelgrass, object-based image analysis, OBIA = object-based image analysis, works extremely well for high-resolution drone data.
The concurring conclusion from the report and the PhD is that drones can provide much more accurate data and that the work of monitoring eelgrass can be done with much fewer resources in shallow areas than with traditional monitoring methods.
Therefore, the report's authors, including PhD writer Aris Thomasberger, recommend that the developed drone-based methods be included in future programs for monitoring eelgrass.
The researchers point to possible applications within, among other things, 3rd generation water plans and impact assessments of fishing in Natura 2000 areas.
In the report, you can read recommendations for the necessary setup for drone surveillance, which ensures data comparability and high user-friendliness, and which is also robust and cost-effective.
The researchers also point to the future, where the focus is exclusively on large-scale monitoring in fixed surveillance programs, and here systems such as fixed-wing drones or hybrid drones should also be investigated.
PHOTO at top: Aris Thomasberger with drone, by Anne Trap-Lind
ILLUSTRATION of different techniques: Diving surveys, video, drones, satellites, ortho-photo and sonar for monitoring marine bottom vegetation. Copyright: Lønborg, C.; Thomasberger, A.; Stæhr, P.A.U.; Stockmarr, A.; Sengupta, S.; Rasmussen, M.L.; Nielsen, L.T.; Hansen, L.B.; Timmermann, K. Submerged aquatic vegetation: Overview of monitoring techniques used for the identification and determination of spatial distribution in European coastal waters. Integral Environment. Assess. Manage. 2022, 18, 892–908.