An enhanced Angular Range Analysis workflow with multibeam backscatter for wider industrial impact and uptake of INFOMAR data
| dc.contributor.advisor | Lim, Aaron | |
| dc.contributor.advisor | Summers, Gerard | |
| dc.contributor.advisor | de Oliveira, Macedo | |
| dc.contributor.author | Brennan, Cara | en |
| dc.contributor.funder | Geological Survey of Ireland | |
| dc.date.accessioned | 2026-05-21T13:03:45Z | |
| dc.date.available | 2026-05-21T13:03:45Z | |
| dc.date.issued | 2025-12-31 | |
| dc.date.submitted | 2025-12-31 | |
| dc.description.abstract | The climate crisis, EU energy targets, along with the need for energy security are driving increased demand for renewable energy (RE). Given the constraints associated with onshore RE, there has been a push for offshore renewable energy (ORE), leading to intense geophysical and geotechnical investigations in marine environments. In Ireland, at the forefront of this is the South Coast Designated Maritime Area Plan (SC-DMAP), which proposes four ORE sites off Ireland’s south coast as part of a plan-led marine spatial planning approach. The demand for subsea infrastructure highlights the need for accurate, repeated seabed characterisation. Initiatives such as Seabed 2030 and national mapping programmes such as INFOMAR (Ireland) and MAREANO (Norway) have given way to vast quantities of data. Yet, freely available INFOMAR datasets for ORE development remain underutilised. Moreover, existing seabed characterisation methodologies are often fragmented, bespoke, and time-consuming, thereby underlining the need for scalable, repeatable approaches to support large-scale mapping programmes. Acoustic backscatter strength plays a crucial role in seabed characterisation, as backscatter intensity varies, in part due to sediment composition, enabling grain size estimations from acoustic returns. Traditionally, image-based backscatter processing has dominated seabed characterisation workflows. Signal-based approaches such as Angular Range Analysis (ARA) are gaining traction due to their robust characterisation. However, the latter is constrained by its low spatial accuracy, hindering its widespread use. While various attempts have been made to address this, many remain complex, resource-intensive and lack scalability. Therefore, requiring methods that are efficient, adaptable, and applicable under varying conditions. Moreover, a holistic understanding of seabed conditions in the Irish portion of the Celtic Sea is required to de-risk ORE development in the region, yet research on seabed dynamics, bedform mobility and seabed stability, in the context of ORE in this region, remain limited. Firstly, I aim to develop a more spatially comprehensive workflow for grain-size estimation utilising ARA. To address this, the high spatial accuracy of multibeam backscatter data is integrated with the high-fidelity sediment characterisation derived from ARA, through object-based image analysis (OBIA), to derive enhanced Angular Range Analysis (eARA). Applied to four sites with ranging depths, operating frequencies, sonars, and varying environments offshore Ireland, utilising freely available INFOMAR data. I investigate the influence of various geophysical characteristics, sediment sedimentological parameters and sediment sampling strategies to understand the influence of these parameters on the error of our grain size estimation. Secondly, building upon the previous aim, I aim to investigate the seabed dynamics and geological constraints at the proposed Tonn Nua ORE site and evaluate the implications for ORE. To address this, the latter methodology is applied to Tonn Nua, a proposed ORE site in the SC-DAMP. Here, high-resolution, time-lapse bathymetry datasets, grain size information via eARA and various theoretical formulae are employed to understand the spatio-temporal seabed change and investigate the hydrodynamics within Tonn Nua. Results addressing the first aim indicate strong correlations between observed and estimated grain size (Spearman’s ρ up to 0.75, p<0.01), overall accuracies up to 96.15% (k=0.84) and improved spatial accuracies compared to traditional ARA. Results addressing the second objective indicate that at the Tonn Nua Site, sandwaves are relatively stable, migrating at an average of 0.25 and 0.26 m yr-1, between 2007 - 2024 and 2013 - 2024, respectively. Additionally, results demonstrate an average residual current of 41 cm s-1, flowing NE - SW, is consistent with legacy measurements and bedform derived estimates. Moreover, providing evidence of mobile sediment, seabed scour, sandwaves and potential bedrock outcrops, that may influence ORE development. Overall the results presented in this thesis, demonstrate the capacity of eARA as a robust and spatially accurate sediment grain-size estimator, thereby providing a scalable and low-cost seafloor characterization approach, applicable to large-scale governmental programmes such as INFOMAR and MAREANO. By applying this methodology to a proposed ORE site, this research further illustrates the applicability of this methodology to ORE development, acting as a preliminary assessment of sediment grain size, seabed dynamics, and seabed stability. The constraints identified in this research at the Tonn Nua site provide critical baseline information to ensure the safe development and longevity of offshore subsea structures at this site. | en |
| dc.description.status | Not peer reviewed | en |
| dc.description.version | Accepted Version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Brennan, C. 2025. An enhanced Angular Range Analysis workflow with multibeam backscatter for wider industrial impact and uptake of INFOMAR data. MRes Thesis, University College Cork. | |
| dc.identifier.endpage | 144 | |
| dc.identifier.uri | https://hdl.handle.net/10468/18806 | |
| dc.language.iso | en | en |
| dc.publisher | University College Cork | en |
| dc.relation.project | Geological Survey of Ireland (Grant no. 2023-MC-015) | |
| dc.rights | © 2025, Cara Brennan. | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Multibeam backscatter | |
| dc.subject | Angular Range Analysis | |
| dc.subject | Sediments | |
| dc.subject | Object-based image analysis | |
| dc.subject | Offshore renewable energy | |
| dc.subject | Seabed characterisation | |
| dc.title | An enhanced Angular Range Analysis workflow with multibeam backscatter for wider industrial impact and uptake of INFOMAR data | |
| dc.type | Masters thesis (Research) | en |
| dc.type.qualificationlevel | Masters | en |
| dc.type.qualificationname | MSc - Master of Science | en |
