ITERATIVE REFINEMENT FOR UNDERWATER 3D RECONSTRUCTION: APPLICATION TO DISPOSED UNDERWATER MUNITIONS IN THE BALTIC SEA

Extraction of polymetallic nodules will have negative impacts on the deep-sea ecosystem, but it is not known whether the ecosystem is able to recover from them. Therefore, in 1989 a sediment disturbance experiment was conducted in the Peru Basin to mimic deep-sea mining. Subsequently, the experimental site was re-visited 5 times to monitor the recovery of fauna. We developed food-web models for all 5 time steps and found that, even after 26 years, carbon flow in the system differs significantly.

Manganese nodules are a deep-sea mineral resource considered for mining. This paper provides insights into measuring the distribution of manganese nodules at meter resolution. Nodule abundance was determined by autonomous robots using cameras and echo sounders. Based on the meter-scale abundance measurements, environmental impacts of simulated deep-sea mining were assessed. The spatial extent of a sediment plume was determined and showed correlation to small variations in seafloor topography.

AUV hydro-acoustic and optical data enhance high resolution quantitative mapping of deep sea hard substrates such Mn-nodules. Machine learning algorithms predict with good accuracy the Mn-nodules abundances over large scale areas utilizing one third of ground truth optical data. Accurate maps of Mn-nodule abundances raise new questions about the role of fine scale geomorphology in nodule formation, provide new insights in deep sea ecological studies, and improve mineral assessment estimations.