Pixel-level bathymetry mapping of optically shallow water areas by combining aerial RGB video and photogrammetry

Abstract

Combining geometric and optical methods based on a low-cost UAV platform can achieve high-resolution bathymetry mapping without ground-truth data in optically shallow water areas. However, with the increasing spatial resolution, water surface fluctuation interferes with the imaging. In this study, we propose a bathymetry mapping approach that combines video and geometric-optical principles. The multi-sampling of the video data allows for a temporal averaging window of each pixel. A motion-based frame registration method was developed to compose an image from a video acquired by UAV push-broom sampling to mitigate the instantaneous changes caused by water surface fluctuations. The composite images were used for bathymetry mapping using data from the photometric point clouds from the UAV images for calibration. Then, the improved effect of video multi-sampling on the optical bathymetric model was evaluated by comparing the results of bathymetric inversion based on single images and video composite images. An evaluation case in the coastal area of Hainan Island demonstrates that results based on composite images processed with three optical bathymetric models of different complexity increased the coefficient of determination from 0.8111, 0.8652, 0.9255 to 0.8652, 0.8750, 0.9363, and reduced the root mean square error from 0.234 m, 0.192 m, 0.143 m to 0.197 m, 0.178 m, 0.133 m, respectively. Qualitatively, using composite images from aerial RGB videos for bathymetry mapping effectively removes radiative anomalies due to wave focusing or reflection and provides a more accurate description of underwater objects' shape than single images.