Application of novel 3D imaging techniques to quantify biomass associated with North Sea artificial structures (NS3D)
Objective 1: Generate benthic biomass estimates associated with offshore wind turbines and oil and gas platforms in the North Sea through the application of novel 3D imaging techniques and analysis of existing industry data held (ROV videos of infrastructure).
Objective 2: Train machine-learning algorithms to automatically identify North Sea epifaunal species within video footage. Combine auto-ID with 3D imagining techniques to enable rapid generation of accurate, high-resolution automated faunal identification to deliver a new monitoring tool for industry.
Objective 3: Use the outputs from 1&2 to quantify, using a linear statistical model, the relationship between biomass/identity of marine growth (response variable) and structure type, location, depth and age (predictors, North Sea data)
Objective 4: Use SAMS’ established knowledge exchange pathways to disseminate outputs to the academic community, regulators and the offshore energy industry. Embed new knowledge into current regulatory practices, and work closely with CEFAS to enable incorporation of taxa-specific predicted biomass into the North Sea food-web model.
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