Abstract
Because the seafloor is a complex ecosystem, a multidisciplinary approach must be adopted in order to produce comprehensive habitat maps. Such multidisciplinary projects have been lacking for the Dutch area of the North Sea. To address this lack, the Distribution, structure and functioning of low resilience seafloor communities and habitats of the Dutch North Sea (DISCLOSE) project, funded by the Gieskes- Strijbis Fonds, was initiated. The consortium for the project included three research institutes, as well as the North Sea Foundation. The first of the research institutes was the Delft University of Technology, tasked with the large-scale mapping of the seafloor, using acoustic systems such as the multibeam echosounder (MBES). The second research institute, the University of Groningen (UG), focused on the use of photography and videography to study the seafloor and the epifauna at a smaller, yet more detailed, spatial scale. Finally, the Royal Netherlands Institute for Sea Research (NIOZ), studied the seafloor from both the perspective of particle size and macrofauna using grab-sample data. All of these measurement methods were utilized for the same research areas, in order to maximize the possibility to established links between the sampling methods, and thereby create detailed habitat maps. The work in this thesis focuses specifically on the acoustic results generated within the DISCLOSE project. In recent years the MBES has become the standard tool for the large-scale mapping of the ocean floor. With the MBES, large swaths of the seafloor can be covered in short periods of time. The use of the two-way travel time to measure the bathymetry of the ocean has become very standardized. In addition to measuring the bathymetry, the MBES can also deliver the collocated backscatter product. The appropriate use of backscatter for the classification of seafloor properties and habitats is much less well understood than bathymetry. As such, this is an active field of research. Within Dutch waters, most research has taken place using datasets from the area of the Cleaverbank. Other areas have not been well studied, for example, the southern sandy area. Utilizing MBES backscatter-based seafloor classification in sandy areas is a major focus in this thesis. A dataset from the Brown Bank area of the North Sea was used in order to study seafloor classification over mega ripple structures. A big part of the Southern North Sea is covered in nested sand waves of different sizes. The largest of these is the tidal ridge, with some ten kilometers from crest to crest. The second largest is the sand wave, and the smallest is the mega ripple. Obviously, the main sediment type in this area is sand. Previous research suggests that a difference in grain size is to be expected between the crest of the tidal ridge to the trough. It was not known if a difference in grain size from the crest to the trough of the sand wave or the mega ripple is present, or detectable using MBES backscatter. As such, for this research a few things were very important. Firstly, it was necessary to accurately correct the backscatter for the seafloor slopes in the research area. Next, it was important to have a high spatial resolution for the final classification results. Additionally, a high geo-acoustic resolution was also needed. This final resolution is needed because it is expected that the difference in sediment properties from the trough to crest of a mega-ripple may be just slightly coarser or finer sand. From our research, it was found that it is possible to use MBES backscatter in order to classify the sediment types at the scale of mega ripples. It was found that the coarsest sediments were in the troughs, finer sediments on the stoss side slopes, and a mixture of sediments on the lee side slopes of the mega ripples...
Original language | English |
---|---|
Qualification | Doctor of Philosophy |
Awarding Institution |
|
Supervisors/Advisors |
|
Award date | 7 Feb 2022 |
Print ISBNs | 978-94-6384-297-6 |
DOIs | |
Publication status | Published - 2022 |
Funding
Stichting Gieskes-Strijbis FondsKeywords
- Multibeam Echosounder
- Sediment Classification
- Dutch North Sea
- Object-based image analysis
- Backscatter
- Bathymetry,
- Bathymetric derivatives
- Grab samples
- Bayesian classification
- Seafloor mapping
- Benthic habitats
- Marine geology
- Sandbanks
- Tidal ridges
- Sand waves
- Mega ripples
- Sand ripples