Confronting turbidity, the major challenge for satellite-derived coastal bathymetry.

Monitoring the complex seafloor morphology that drives the functioning of shallow coastal ecosystems is vital for assessing marine activities. Satellite-derived bathymetry (SDB) can provide a crucial dataset for creating the bathymetry maps needed to understand hazards and impacts produced by climate change in vulnerable coastal zones. SDB is effective in clear water, but still has limitations in application to areas with some turbidity. Here, using the twin satellites Sentinel-2A/B, we integrate water quality information from the satellite with a multi-temporal compositing method to demonstrate a potential for comprehensively operational bathymetric mapping over a range of environments. The automated compositing method diminishes the turbidity impact in addition to inferring the maximum detectable depth and removing optically deep-water areas. Examining a wide range of conditions along the Caribbean and eastern coast of the U.S. shows detailed bathymetry as deep as 30 m at 10 m spatial resolution with median errors <1 m when compared to high-resolution lidar surveys. These results demonstrate that the model adopted can provide useful bathymetry in areas that do not have consistently clear water and can be extended across multiple geographic regions and optical conditions at local, regional, and national scales.