A regional digital bathymetric model fusion method based on topographic slope: A case study of the south China sea and surrounding waters
Xiaoguang Ruan,
Meijing Guo,
Zhaojie Zhan
Affiliations
Xiaoguang Ruan
College of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China; Ministry of Education Key Laboratory of Land and Sea Security Decision Technology, Nanjing University, Nanjing 210023, China; Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China; Digital Twin Watershed Technology and Equipment Zhejiang Engineering Research Center, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China; Corresponding author. College of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China.
Meijing Guo
College of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China; The Academy of Digital China, Fuzhou University, Fuzhou 350108, China
Zhaojie Zhan
College of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China; Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
High-resolution seafloor topography is important in scientific research and marine engineering in regard to marine resource development and environmental protection monitoring. In this study, multi-dimensional comparisons were made between GEBCO_2022, SRTM15_V2.5.5, SRTM30_PLUS, SYNBATH_V1.0, ETOPO_2022, and topo_25.1 in the South China Sea and surrounding waters (SCS). This study has found that ETOPO_2022 had the best overall accuracy and reliability. Based on the results of the model accuracy analysis and by considering the topographic slope, ETOPO_2022, GEBCO_2022, and SRTM15_V2.5.5 were weighted and fused to form a fusion model. The error of the fusion model was 94.80% concentrated in (−100–100 m). When compared with GEBCO_2022, SRTM15_V2.5.5, SRTM30_PLUS, SYNBATH_V1.0, ETOPO_2022, and topo_25.1, the RMSE was reduced by 2%, 9%, 62%, 15%, 1%, and 73%, respectively. The slope-based weighted fusion method has been shown that it can overcome the limitations of a single data source and provide a reference for timely reconstruction and updating of large-scale seafloor topography.
