Evaluation of Four Global Bathymetry Models by Shipborne Depths Data
Publication: Journal of Surveying Engineering
Volume 148, Issue 2
Abstract
More and more global digital bathymetric models (DBMs) have been developed using different kinds of data and have played a great role in navigation, national military defenses, tsunami predictions, marine resource developments, and so on. In order to select appropriate DBMs for usage in different ocean areas, it is necessary to verify their accuracies. In this study, the accuracy of four recent global DBMs, i.e., DTU18BAT, ETOPO1, GEBCO_2020Grid, and SRTM15 + V2.0, are evaluated by shipborne bathymetry data. By setting the shipborne depths data as true values, the error statistics and spatial distribution of the models are firstly analyzed both in spatial and frequency domains. The results show that SRTM15 + V2.0 has the highest accuracy. After removing gross errors, the error standard deviations of SRTM15 + V2.0 are smaller than 50 m, and 90% of the evaluation points have errors smaller than 100 m except in the Indian Ocean. The four models were fused together to obtain a new DBM with higher accuracy. This was done using a weighted combination algorithm based on iterative search to determine the combination parameters. The results showed that compared with the initial four models, the new model has an improved standard deviation of 2.816 m. Also, in a area in the Indian Ocean where initial mean error and error standard deviation were, respectively, and 94.041 m, the average error has decreased by 8.527 m, and the error standard deviation has decreased by 13.528 m. The results of this study can provide a reference for the selection and optimization of the seabed topography model.
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Data Availability Statement
Some data and models used during the study were provided by a third party. Direct request for these materials may be made to the provider as indicated in the Acknowledgments. The shipborne depth data and ETOPO1 model were downloaded from NCEI (https://www.ncei.noaa.gov/maps/bathymetry/) and (https://topex.ucsd.edu/pub/archive/srtm15/V2/). The DTU18BAT model was downloaded from DTU SPACE (https://ftp.space.dtu.dk/pub/DTU18/1_MIN/). The GEBCO_2020Grid model was downloaded from GEBCO (https://www.gebco.net/data_and_products/historical_data_sets/). The SRTM15 + V2.0 model was downloaded from SIO (https://topex.ucsd.edu/pub/archive/srtm15/V2/). All of data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors would like to thank NCEI for providing shipborne depths data and ETOPO1 model. The authors also want to thank DTU SPACE for providing the DTU18BAT model, thank GEBCO for providing the GEBCO_2020Grid model, and thank SIO for providing the SRTM15 + V2.0 model. This study was funded by the National Natural Science Foundation of China (Nos. 42074017 and 41674026); China Geological Survey (No. 20191006); Fundamental Research Funds for the Central Universities (No. 2652018027); and Open Research Fund of Qian Xuesen Laboratory of Space Technology, CAST (No. GZZKFJJ2020006).
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Journal of Surveying Engineering
Volume 148 • Issue 2 • May 2022
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© 2021 American Society of Civil Engineers.
History
Received: Jul 25, 2021
Accepted: Nov 10, 2021
Published online: Dec 27, 2021
Published in print: May 1, 2022
Discussion open until: May 27, 2022
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