Articles | Volume 17, issue 5
https://doi.org/10.5194/gmd-17-2039-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-2039-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
08 Mar 2024
Model experiment description paper |
| 08 Mar 2024
| 08 Mar 2024
High-precision 1′ × 1′ bathymetric model of Philippine Sea inversed from marine gravity anomalies
Dechao An
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
Xiaotao Chang
Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China
Zhenming Wang
Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China
Yongjun Jia
National Satellite Ocean Application Service, Ministry of Natural Resources, Beijing 100081, China
Xin Liu
College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
Valery Bondur
AEROCOSMOS Research Institute for Aerospace Monitoring, Moscow 105064, Russia
Heping Sun
State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430071, China
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Cited
19 citations as recorded by crossref.
- Comparative Study of Seafloor Topography Prediction from Gravity–Geologic Method and Analytical Algorithm Y. Tian et al. https://doi.org/10.3390/rs16173154
- Enhancing bathymetry estimation from altimeter-derived gravity in shallow to intermediate seas by integrating coastline and SDB constraints X. Chen et al. https://doi.org/10.1016/j.asr.2025.07.094
- Enhancing Seafloor Topography Inversion Based on Marine Gravity Data Using Robust Weighted Total Least Squares F. Zhu et al. https://doi.org/10.1109/JSTARS.2025.3649032
- Improving High-Frequency Marine Gravity Anomaly Recovery: The Efficacy of SWOT Wide-Swath Altimetry J. Wang et al. https://doi.org/10.1109/LGRS.2024.3431694
- Uncertainty analysis of bathymetry inversion in the South China Sea: a comparison of deep learning and Bayesian approaches S. Zhou et al. https://doi.org/10.1093/gji/ggag093
- Estimating Seafloor Topography of the South China Sea Using SWOT Wide-Swath Altimetry Data F. Zhu et al. https://doi.org/10.1109/JSTARS.2025.3526683
- Enhanced gravity-geologic method to predict bathymetry by considering non-linear effects of surrounding seafloor topography X. Jiang et al. https://doi.org/10.1093/gji/ggae301
- PSO-optimized dual-channel BP neural network for bathymetric prediction using multisource marine geodetic data: A case study of the gulf of Mexico J. Yuan et al. https://doi.org/10.1016/j.srs.2025.100274
- Advancing Coral Reef Bathymetry: A GAN-Augmented and Stratified CNN Analysis of Fused ICESat-2 and Sentinel-2 Dataset Z. Chen et al. https://doi.org/10.1109/TGRS.2026.3659873
- HHU24SWDSCS: a shallow-water depth model over island areas in the South China Sea retrieved from satellite-derived bathymetry Y. Wu et al. https://doi.org/10.5194/essd-17-2463-2025
- Preliminary Results of Marine Gravity Anomaly and Bathymetry From SWOT Wide-Swath Altimeter Data M. Sun et al. https://doi.org/10.1109/JSTARS.2025.3588419
- SDUST2023BCO: a global seafloor model determined from a multi-layer perceptron neural network using multi-source differential marine geodetic data S. Zhou et al. https://doi.org/10.5194/essd-17-165-2025
- Bathymetry of the Philippine sea with convolution neural network from multisource marine geodetic data J. Guo et al. https://doi.org/10.1016/j.isci.2025.114285
- Analysis of the shallow water bathymetric accuracy of ICESat-2 in combination with marine environmental factors S. Chu et al. https://doi.org/10.1080/01490419.2025.2508771
- Predicting bathymetry using multisource differential marine geodetic data with multilayer perceptron neural network S. Zhou et al. https://doi.org/10.1080/17538947.2024.2393255
- Evaluating the Accuracy of Global Bathymetric Models in the Red Sea Using Shipborne Bathymetry A. Zaki et al. https://doi.org/10.1007/s12524-024-01981-4
- Seabed Depth Prediction Using Multi-Scale Gravity Anomalies and Fully Connected Deep Neural Networks: A Novel Approach Applied to the South China Sea J. Yuan et al. https://doi.org/10.3390/rs17030412
- Trans-UNet Network for Predicting Bathymetry in South China Sea From Gravity and Geological Data S. Zhou et al. https://doi.org/10.1109/JSTARS.2025.3579250
- Impact of Seafloor Morphology on Regional Sea Level Rise in the Japan Trench Region M. Idzikowska et al. https://doi.org/10.3390/w17233433
19 citations as recorded by crossref.
- Comparative Study of Seafloor Topography Prediction from Gravity–Geologic Method and Analytical Algorithm Y. Tian et al. https://doi.org/10.3390/rs16173154
- Enhancing bathymetry estimation from altimeter-derived gravity in shallow to intermediate seas by integrating coastline and SDB constraints X. Chen et al. https://doi.org/10.1016/j.asr.2025.07.094
- Enhancing Seafloor Topography Inversion Based on Marine Gravity Data Using Robust Weighted Total Least Squares F. Zhu et al. https://doi.org/10.1109/JSTARS.2025.3649032
- Improving High-Frequency Marine Gravity Anomaly Recovery: The Efficacy of SWOT Wide-Swath Altimetry J. Wang et al. https://doi.org/10.1109/LGRS.2024.3431694
- Uncertainty analysis of bathymetry inversion in the South China Sea: a comparison of deep learning and Bayesian approaches S. Zhou et al. https://doi.org/10.1093/gji/ggag093
- Estimating Seafloor Topography of the South China Sea Using SWOT Wide-Swath Altimetry Data F. Zhu et al. https://doi.org/10.1109/JSTARS.2025.3526683
- Enhanced gravity-geologic method to predict bathymetry by considering non-linear effects of surrounding seafloor topography X. Jiang et al. https://doi.org/10.1093/gji/ggae301
- PSO-optimized dual-channel BP neural network for bathymetric prediction using multisource marine geodetic data: A case study of the gulf of Mexico J. Yuan et al. https://doi.org/10.1016/j.srs.2025.100274
- Advancing Coral Reef Bathymetry: A GAN-Augmented and Stratified CNN Analysis of Fused ICESat-2 and Sentinel-2 Dataset Z. Chen et al. https://doi.org/10.1109/TGRS.2026.3659873
- HHU24SWDSCS: a shallow-water depth model over island areas in the South China Sea retrieved from satellite-derived bathymetry Y. Wu et al. https://doi.org/10.5194/essd-17-2463-2025
- Preliminary Results of Marine Gravity Anomaly and Bathymetry From SWOT Wide-Swath Altimeter Data M. Sun et al. https://doi.org/10.1109/JSTARS.2025.3588419
- SDUST2023BCO: a global seafloor model determined from a multi-layer perceptron neural network using multi-source differential marine geodetic data S. Zhou et al. https://doi.org/10.5194/essd-17-165-2025
- Bathymetry of the Philippine sea with convolution neural network from multisource marine geodetic data J. Guo et al. https://doi.org/10.1016/j.isci.2025.114285
- Analysis of the shallow water bathymetric accuracy of ICESat-2 in combination with marine environmental factors S. Chu et al. https://doi.org/10.1080/01490419.2025.2508771
- Predicting bathymetry using multisource differential marine geodetic data with multilayer perceptron neural network S. Zhou et al. https://doi.org/10.1080/17538947.2024.2393255
- Evaluating the Accuracy of Global Bathymetric Models in the Red Sea Using Shipborne Bathymetry A. Zaki et al. https://doi.org/10.1007/s12524-024-01981-4
- Seabed Depth Prediction Using Multi-Scale Gravity Anomalies and Fully Connected Deep Neural Networks: A Novel Approach Applied to the South China Sea J. Yuan et al. https://doi.org/10.3390/rs17030412
- Trans-UNet Network for Predicting Bathymetry in South China Sea From Gravity and Geological Data S. Zhou et al. https://doi.org/10.1109/JSTARS.2025.3579250
- Impact of Seafloor Morphology on Regional Sea Level Rise in the Japan Trench Region M. Idzikowska et al. https://doi.org/10.3390/w17233433
Saved (final revised paper)
Latest update: 21 Jul 2026
Short summary
Seafloor topography, as fundamental geoinformation in marine surveying and mapping, plays a crucial role in numerous scientific studies. In this paper, we focus on constructing a high-precision seafloor topography and bathymetry model for the Philippine Sea (5° N–35° N, 120° E–150° E), based on shipborne bathymetric data and marine gravity anomalies, and evaluate the reliability of the model's accuracy.
Seafloor topography, as fundamental geoinformation in marine surveying and mapping, plays a...
