An efficient coral survey method based on a large-scale 3-D structure model obtained by Speedy Sea Scanner and U-Net segmentation.

Over the last 3 decades, a large portion of coral cover has been lost around the globe. This significant decline necessitates a rapid assessment of coral reef health to enable more effective management. In this paper, we propose an efficient method for coral cover estimation and demonstrate its viability. A large-scale 3-D structure model, with resolutions in the x, y and z planes of 0.01 m, was successfully generated by means of a towed optical camera array system (Speedy Sea Scanner). The survey efficiency attained was 12,146 m/h. In addition, we propose a segmentation method utilizing U-Net architecture and estimate coral coverage using a large-scale 2-D image. The U-Net-based segmentation method has shown higher accuracy than pixelwise CNN modeling. Moreover, the computational cost of a U-Net-based method is much lower than that of a pixelwise CNN-based one. We believe that an array of these survey tools can contribute to the rapid assessment of coral reefs.