Quantifying Area Back Scatter of Marine Organisms in the Arctic Ocean by Machine Learning-Based Post-Processing of Volume Back Scatter

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Udgivet i:Sensors vol. 25, no. 10 (2025), p. 3121
Hovedforfatter: Misund Ole Arve
Andre forfattere: Nikolopoulos, Anna, Stürzinger Vegard, Hop Haakon, Dodd, Paul, Korneliussen, Rolf J
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MDPI AG
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100 1 |a Misund Ole Arve  |u Norwegian Polar Institute, Fram Centre, 9296 Tromsø, Norway; anna.nikolopoulos@npolar.no (A.N.); vegard.stuerzinger@gmail.com (V.S.); haakon.hop@npolar.no (H.H.); paul.dodd@npolar.no (P.D.) 
245 1 |a Quantifying Area Back Scatter of Marine Organisms in the Arctic Ocean by Machine Learning-Based Post-Processing of Volume Back Scatter 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a As the sea ice reduces in both extent and thickness and the Arctic Ocean opens, there is substantial interest in mapping the marine ecosystem in this remote and until now largely inaccessible ocean. We used the R/V Kronprins Haakon during surveys in the Central Arctic Ocean (CAO) in 2022 and 2023 to record the marine ecosystem using modern fisheries acoustics and net sampling. The 2022 survey reached all the way to the North Pole. In a first, principally manually based post-processing of these acoustic recordings using the Large-Scale Survey Post-processing System (LSSS), much effort was used to remove segments of noise due to icebreaking operations. In a second, more sophisticated post-processing, the KORONA module of LSSS with elements of machine learning was applied for further noise reduction and to allocate the area back-scattering recordings to taxonomic groups as order, families and even species of fish and plankton organisms. These results highlight the need for further advances in post-processing systems to enable the direct allocation of back-scattered acoustic energy to taxonomic categories, including species-level classifications. 
651 4 |a Arctic Ocean 
651 4 |a North Pole 
653 |a Research ships 
653 |a Plankton 
653 |a Machine learning 
653 |a Taxonomy 
653 |a Data collection 
653 |a Protocol 
653 |a Acoustics 
653 |a Fish 
653 |a Fisheries 
700 1 |a Nikolopoulos, Anna  |u Norwegian Polar Institute, Fram Centre, 9296 Tromsø, Norway; anna.nikolopoulos@npolar.no (A.N.); vegard.stuerzinger@gmail.com (V.S.); haakon.hop@npolar.no (H.H.); paul.dodd@npolar.no (P.D.) 
700 1 |a Stürzinger Vegard  |u Norwegian Polar Institute, Fram Centre, 9296 Tromsø, Norway; anna.nikolopoulos@npolar.no (A.N.); vegard.stuerzinger@gmail.com (V.S.); haakon.hop@npolar.no (H.H.); paul.dodd@npolar.no (P.D.) 
700 1 |a Hop Haakon  |u Norwegian Polar Institute, Fram Centre, 9296 Tromsø, Norway; anna.nikolopoulos@npolar.no (A.N.); vegard.stuerzinger@gmail.com (V.S.); haakon.hop@npolar.no (H.H.); paul.dodd@npolar.no (P.D.) 
700 1 |a Dodd, Paul  |u Norwegian Polar Institute, Fram Centre, 9296 Tromsø, Norway; anna.nikolopoulos@npolar.no (A.N.); vegard.stuerzinger@gmail.com (V.S.); haakon.hop@npolar.no (H.H.); paul.dodd@npolar.no (P.D.) 
700 1 |a Korneliussen, Rolf J  |u Institute of Marine Research, 5005 Bergen, Norway; rolf.korneliussen@hi.no 
773 0 |t Sensors  |g vol. 25, no. 10 (2025), p. 3121 
786 0 |d ProQuest  |t Health & Medical Collection 
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