| Abstract | 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 thesis, a proposed 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: SBES (research vessel), SBES+SSS (research vessel), MBES (research vessel), MBES (research vessel)+SBES (small boat), LIDAR (UAV), SDB (satellite sensors) and they are applied as a case study of Kaštela Bay. The optimal technology for Kaštela Bay study case was MBES (research vessel) and MBES (research vessel) + SBES (small boat) with a score of 0.97. Then with a score of 0.82 follows the SDB technology. Other available alternatives have a significantly lower score. It is a small evident difference between the three alternatives SBES (research vessel), SBES+SSS (research vessel), and LIDAR, which have a WSM score in the range from 0.58 – 0.65. |
