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Hydrographic survey or seabed mapping plays an important role in achieving better maritime safety, especially in coastal waters. Due to advances in survey technologies, it becomes important to choose well-suited technology for a specific area. Moreover, various technologies have various ranges of equipment and manufacturers, as well as characteristics. Therefore, in this paper, a novel method of a hydrographic survey, i.e., identifying the appropriate technology, has been developed. The method is based on a reduced elimination matrix, decision tree supervised learning, and multicriteria decision methods. The available technologies were: remotely operated underwater vehicle (ROV), unmanned aerial vehicle (UAV), light detection and ranging (LIDAR), autonomous underwater vehicle (AUV), satellite-derived bathymetry (SDB), and multibeam echosounder (MBES), and they are applied as a case study of Kaštela Bay. Results show, considering the specifics of the survey area, that UAV is the best-suited technology to be used for a hydrographic survey. However, some other technologies, such as SDB come close and can be considered an alternative for hydrographic surveys.

A Novel Method on Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning