| Summary: | Cold-water coral reefs are complex structural habitats that represent one of the most important deep marine ecosystems. As three-dimensional habitats with high structural complexity, they provide ecosystem services that influence species abundance and biodiversity, being indicators of ecosystem health. These habitats are considered hotspots of biodiversity around the globe, especially in cold and deep waters between 50 and 4000 metres depth. Similar to their tropical counterparts, these habitats are subject to several climate and anthropogenic threats. Over the last two decades, research efforts to identify, map and manage these environments have increased along with the advances in data acquisition. Technologies such as remotely underwater vehicles are equipped with high-resolution sensors that generate gigabytes to terabytes of data. However, data analysis methods are being outpaced by acquisition technologies and there is a latency in the extraction of meaningful information from large datasets. Furthermore, the fine-scale heterogeneity promoted by the three-dimensional scleractinian coral branching structure is often overlooked, being reduced to a two-dimensional scale. This thesis explores methods that can advance seabed mapping to further understand cold-water coral reef habitat features in the deep sea considering their natural, three-dimensional structure and posed data analysis demands given the current technologies. The key aims of the research were to: i) develop an unprecedented 3D imaging classification workflow for CWC habitats of Ireland whilst analysing the suitability and transferability of 2D and 3D data to represent these habitats in high-resolution; ii) quantify facies distribution and spatial variability; iii) link image data to processes driving CWC reef development; iv) develop new forms of visualisation of 3D data of underwater environments; v) derive meaningful information from dense optical datasets. Here, CWC reef habitats in the Porcupine Bank Canyon and the Belgica Mound Province, in ...
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