3D Classification of Cold-Water Coral Reefs: A Comparison of Classification Techniques for 3D Reconstructions of Cold-Water Coral Reefs and Seabed

Cold-water coral reefs are complex structural habitats that are considered biodiversity ‘hotspots’ in deep-sea environments and are subject to several climate and anthropogenic threats. As three-dimensional structural habitats, there is a need for robust and accessible technologies to enable more accurate reef assessments. Photogrammetry derived from Remotely Operated Vehicle video data is an effective and non-destructive method that creates high-resolution reconstructions of cold-water coral habitats. Here, three classification workflows (2D object-based image analysis, 3D support vector machine and 3D gradient-boosted trees) are presented and applied to photogrammetric reconstructions of cold-water coral habitats in the Porcupine Bank Canyon, NE Atlantic. In total, six point clouds, orthomosaics and digital elevation models, generated from Structure-from-Motion photogrammetry are used to evaluate each classification workflow. Our results show that 3D multiscale classification using Support Vector Machines outperforms colour and geometrical-based classifications with Gradient Boosted Tree methods. However, each method has advantages for specific applications pertinent to the wider marine scientific community. Results suggest that advancing from commonly employed 2D image analysis techniques to 3D photogrammetric classification methods is advantageous and provides a more realistic representation of cold-water coral habitat composition.