  Corals are the primary habitat-building life-form on reefs that support a
quarter of the species in the ocean. A coral reef ecosystem usually consists of
reefs, each of which is like a tall building in any city. These reef-building
corals secrete hard calcareous exoskeletons that give them structural rigidity,
and are also a prerequisite for our accurate 3D modeling and semantic mapping
using advanced photogrammetric computer vision and machine learning. Underwater
videography as a modern underwater remote sensing tool is a high-resolution
coral habitat survey and mapping technique. In this paper, detailed 3D mesh
models, digital surface models and orthophotos of the coral habitat are
generated from the collected coral images and underwater control points.
Meanwhile, a novel pixel-wise semantic segmentation approach of orthophotos is
performed by advanced deep learning. Finally, the semantic map is mapped into
3D space. For the first time, 3D fine-grained semantic modeling and rugosity
evaluation of coral reefs have been completed at millimeter (mm) accuracy. This
provides a new and powerful method for understanding the processes and
characteristics of coral reef change at high spatial and temporal resolution
under climate change.
