Seamless seafloor topography determination from shallow to deep waters over island areas using airborne gravimetry

We study the role of airborne gravimetry for seamless bathymetry modeling over the Paracel Islands in the northern South China Sea (SCS) and investigate the possibility of using Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) data and Satellite-derived bathymetry (SDB) to evaluate bathymetry models over shallow waters. We use ICESat-2 data for training Sentinel-2 imagery and derive the SDB data with a root-mean-squared error (RMSE) of 0.29–0.50 m, which is lower than 10% of the maximum depths. The local bathymetry is modeled by using a modified version of the S&S bandpass filter, and a partition-wise scheme is applied for determining the scaling factors. Numerical experiments verify the feasibility of using ICESat-2 and SDB data to assess bathymetry models. By utilizing the airborne gravity data, the fit between the computed bathymetry and the SDB data is significantly improved, by 18.7%–58.0% over different shallow waters compared with recently released bathymetry models. The bathymetry predicted from the airborne data has also higher performance in deep water areas, which performs best in all these depth ranges from 500 to 3000 m. In comparison with the existing models, the RMSEs of the misfits between the computed bathymetry and the National Oceanic and Atmospheric Administration depths are reduced by tens to hundreds of meters in different depth ranges. Our study highlights that using airborne gravimetry for bathymetry modeling over island areas is advantageous, in both shallow and deep waters, and that ICESat-2 and SDB data can largely alleviate the lack of in situ depths over shallow waters.