[A-OS12] Ocean Science Revealed by Global Observation System

[AOS12-01] How should zooplankton be measured using image-based observing systems?

★Invited Papers

*Mitsuko Hidaka^1,2 (1.Kagoshima University, 2.Japan Agency for Marine-Earth Science and Technology)

Keywords:Zooplankton, Image-based observation, Artificial Intelligence, Global monitoring

Zooplankton is a crucial trophic conjunction between primary producers and predators in the ocean. Observing their variation is essential to elucidate the dynamics of ocean ecosystems. Conventional approaches to observe the zooplankton, net-based sampling system have been introduced for a long time. However, the net sampling system mainly depends on research vessels. Therefore, the spatiotemporal resolution of the sampling data is scarce. Recently, ocean model-driven frameworks, such as ocean digital twins, have been increasing in demand. Global observing systems on zooplankton should be established to respond to such new demands. Image-based plankton observing systems are expected to be applied to global observing networks, such as float or mooring systems. However, the data provided by the plankton image is not equal to net-sampled data. Based on that, we have to consider how zooplankton have to be measured by the new technologies. A technical overview of the image-based zooplankton observation and the issue will be shown in the present talk.