Ahmed Zaki, Bashar Bashir, Abdullah Alsalman, Basem Elsaka, Mohamed Abdallah, Mohamed El-Ashquer
{"title":"Evaluating the Accuracy of Global Bathymetric Models in the Red Sea Using Shipborne Bathymetry","authors":"Ahmed Zaki, Bashar Bashir, Abdullah Alsalman, Basem Elsaka, Mohamed Abdallah, Mohamed El-Ashquer","doi":"10.1007/s12524-024-01981-4","DOIUrl":null,"url":null,"abstract":"<p>Global bathymetric models derived from satellite altimetry are important for studying the Earth’s oceans. However, the accuracy of these models can vary across different geographic regions. This study evaluates four widely used global bathymetric models ETOPO 2022, GEBCO 2023, SRTM15 + V2.5.5, and DTU18BAT in the Red Sea using 268,071 reference shipborne bathymetric measurements. The analysis compares the models’ depth estimates to the shipborne measurements across different depth ranges between 0 and 3000 m. The results show that overall, the GEBCO 2023 model provides the highest accuracy with the lowest standard deviation of 43.774 m and root mean square error of 43.929 m relative to shipborne data. The ETOPO 2022 model ranks second in accuracy with a standard deviation of 45.316 m and root mean square error of 45.345 m. The frequency distribution of residuals indicates that GEBCO 2023 and ETOPO 2022 models have the most precise depth predictions concentrated tightly around zero difference, while SRTM15 + V2.5.5 and DTU18BAT ones show broader spreads. There is no systematic depth over or under-predictions. Finally, the GEBCO 2023 and ETOPO 2022 models show good accuracy in the Red Sea, outperforming SRTM15 + V2.5.5 and DTU18BAT.</p>","PeriodicalId":17510,"journal":{"name":"Journal of the Indian Society of Remote Sensing","volume":"53 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Indian Society of Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s12524-024-01981-4","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Global bathymetric models derived from satellite altimetry are important for studying the Earth’s oceans. However, the accuracy of these models can vary across different geographic regions. This study evaluates four widely used global bathymetric models ETOPO 2022, GEBCO 2023, SRTM15 + V2.5.5, and DTU18BAT in the Red Sea using 268,071 reference shipborne bathymetric measurements. The analysis compares the models’ depth estimates to the shipborne measurements across different depth ranges between 0 and 3000 m. The results show that overall, the GEBCO 2023 model provides the highest accuracy with the lowest standard deviation of 43.774 m and root mean square error of 43.929 m relative to shipborne data. The ETOPO 2022 model ranks second in accuracy with a standard deviation of 45.316 m and root mean square error of 45.345 m. The frequency distribution of residuals indicates that GEBCO 2023 and ETOPO 2022 models have the most precise depth predictions concentrated tightly around zero difference, while SRTM15 + V2.5.5 and DTU18BAT ones show broader spreads. There is no systematic depth over or under-predictions. Finally, the GEBCO 2023 and ETOPO 2022 models show good accuracy in the Red Sea, outperforming SRTM15 + V2.5.5 and DTU18BAT.
期刊介绍:
The aims and scope of the Journal of the Indian Society of Remote Sensing are to help towards advancement, dissemination and application of the knowledge of Remote Sensing technology, which is deemed to include photo interpretation, photogrammetry, aerial photography, image processing, and other related technologies in the field of survey, planning and management of natural resources and other areas of application where the technology is considered to be appropriate, to promote interaction among all persons, bodies, institutions (private and/or state-owned) and industries interested in achieving advancement, dissemination and application of the technology, to encourage and undertake research in remote sensing and related technologies and to undertake and execute all acts which shall promote all or any of the aims and objectives of the Indian Society of Remote Sensing.