Topography prediction from marine gravity and satellite imagery and ship soundings

Marine observation data are plentiful for constructing seafloor topography, and the integration of multi-sources data to construct a more accurate topography model remains a significant subject that continues to be explored and studied. In this study, we use geoid height (GH), gravity (VG) and vertical gravity gradient (VGG) derived from a single rectangular prism to establish the foundational observation equations for predicting topography. The effectiveness of the foundational observation equations is verified through study cases without the use of the ship measurement depth data. Additionally, the single- and multibeam soundings data are employed as control points to integrate into the foundational observation equations for predicting topography. The prediction results demonstrate that the prediction accuracy of combined VG anomalies with ship soundings is better than GH and VGG anomalies, which is primarily because VG anomalies are effective than GH amplify high-frequency signals of topography and stronger than VGG anomalies in suppressing high-frequency errors. Additionally, considering the limited accuracy of marine gravity in sea region with islands and reefs, this study incorporates satellite imagery data to identify the location and size of the islands. Then, the topography of the islands is introduced and the control equations is established to jointly predict topography. The prediction results reveal the RMS errors between prediction results and single- and multibeam sounding data are 67.4 m, which is 37.4, 57.8 and 62.8 per cent higher than that of SRTM 15+, DTU and ETOPO-1 models, respectively. Notably, compared with the STRM 15+ model, the algorithm improves the topography accuracy of the sea area near the islands by nearly 60.8 per cent.