Using vessel acoustics to detect diving patterns of krill foraging predators automatically: development of a novel method for quantifying impact of krill fishing on seals and penguins
The aim of this work was to assess the possibilities of automatically generating a dataset of dive
behaviour of air-breathing predators, based on acoustic data from a monitoring survey and from
commercial krill fishing operations. Our results documents that some form of automatic detection of
diving predators in the data is feasible. A relatively low detection probability of our algorithms
compared to the manual detections, suggest that there is significant room for improvement. Given
the caveats of an imperfect methodology, the results document the possibilities to automatically
extract, with a reasonable level of precision, data on the dive behaviour of air-breathing predators
from the echo-sounder data
Klevjer, Thor Aleksander,Krafft, Bjørn Arne,Godø, Olav Rune. Using vessel acoustics to detect diving patterns of krill foraging predators automatically: development of a novel method for quantifying impact of krill fishing on seals and penguins. 2015-01-01.