Mapping Ultrahigh-Spatial-Resolution Bathymetry for a Wide Range of Coastal Optically Shallow Waters Without In Situ Bathymetric Data

Mapping bathymetry with satellite-based imagery for optically shallow waters is important for the management of coastal areas. However, mapping ultra-high-spatial-resolution bathymetry (spatial-resolution < 5 m) for a wide range of coastal optically shallow waters is limited by high cost and the absence of in situ data. Therefore, in this study, a new downscaled bathymetric mapping approach (DBMA-RGB) was established using freely accessed Landsat-8 (spatial-resolution = 30 m) and cost-effective Google Earth Pro-exported ultra-high-spatial-resolution red-green-blue (RGB) imagery. The new approach introduced the scale-invariance assumption that the log-ratio model (LRM) which is calibrated at a high scale is valid at a low scale. To reduce the inversion errors from Landsat-8 imagery, a theoretical maximum detection depth (MDD) model was proposed for the optimization-based inversion method, which is the foundation of DBMA-RGB for working without in situ bathymetric data. The theoretical MDDs overall matched the true MDDs except for the abnormal values, with root mean square error and correlation coefficient values of 3.30 m and 0.68, respectively. Additionally, a set of correction coefficients was obtained to improve the accuracy of the water depth derived from Landsat-8 imagery. Finally, the DBMA-RGB was applied to the RGB imagery of sixteen coastal areas around the world, incorporating the bathymetric results from Landsat-8 imagery. The comparison results indicated that the DBMA-RGB yielded similar results to the LRM calibrated using in situ bathymetric data. In summary, DBMA-RGB demonstrated its feature in accurately mapping ultra-high-spatial-resolution bathymetry for a wide range of coastal optically shallow waters without in situ bathymetric data.