Abstract
Advancing the sustainable use and conservation of marine environments is urgent. Tons of debris including macro- and microplastics generated on land are entering the oceans, marine resources are decreasing, and many species are facing extinction. Though satellite remote sensing techniques are commonly used for global environmental monitoring, it is still difficult to detect small objects such as floating debris on the vast ocean surface, and the ecosystems deep in the oceans where light does not reach are unobservable. An autonomous monitoring system consisting of optimally controlled robots is required for acquiring spatiotemporally rich marine data. However, object detection in marine environments, which is a necessary function the robots should have for underwater and aerial monitoring, has not been extensively studied. Here, we argue that state-of-the-art deep-learning-based object detection works well for monitoring underwater ecosystems and marine debris. We found that by using the deep-learning object-detection algorithm YOLO v3, underwater sea life and debris floating on the ocean surface can be detected with mean average precision of 69.6% and 77.2%, respectively. We anticipate our results to be a starting point for developing tools for enabling safe and precise acquisition of marine data to elucidate and utilize this last frontier.
Highlights
In 2015, the United Nations set 17 goals, known as sustainable development goals (SDGs),[1] to achieve a better and sustainable future for all life on this planet
We found that aerial marine monitoring using unmanned aerial vehicles (UAVs) that fly at lower altitudes, i.e., less than 30 m, provides sufficient image quality for capturing small targets
We found that Faster R-convolutional neural network (CNN) was not good at detecting small targets [e.g., schools of fishes shown in Fig. 3(b)] that you only look once (YOLO) v3 could successfully detect
Summary
In 2015, the United Nations set 17 goals, known as sustainable development goals (SDGs),[1] to achieve a better and sustainable future for all life on this planet. We can take measures to improve our society, such as developing new laws or technologies. Though we can take any measures to increase resilience against environmental changes and conserve nature, it will take several decades to evaluate their effectiveness. We can observe wide areas and collect information regarding the atmosphere, land, and ocean surface. The current constellation of satellites has enabled to observe the Earth improving temporal resolution. Satellites, such as WorldView-3 and 4, can take images with spatial resolutions on the submeter order enabling the reconstruction of the land surface in threedimensional. The satellite imagery products are still expensive, and it is difficult to obtain information from underwater and in dense forests where light cannot reach
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