Abstract
The observed hydrographic surveying data from multibeam echosounder system (MBES) contains sounding and backscatter intensity data that can be utilized in many coastal and marine applications such as marine geological and environmental investigations. In this paper, the seabed sediments map** for Sharm Obhur (Obhur Creek) was derived using backscatter intensity data. The backscatter data were radiometrically and geometrically corrected to produce a seabed backscatter mosaic for Sharm Obhur study area. Then, the angular response analysis was implemented to derive the seabed sediment’s grain size, classification (gravel, sand and mud) and associated confidence level values that identify the quality of the classification method implemented in this paper. It was shown that the mouth in the south of the Sharm Obhur mainly contains sand sediments, however, the north side of the Sharm Obhur contains mud sediments and gravel sediments can be seen in very small areas. Moreover, it was found that the successful rate of classification is 90% based on the estimated confidence values. To validate the derived seabed sedimentation map, a comparison was made between the grab sampling results reported in the literature and the seabed sediments types derived in this paper. The comparison showed that the derived seabed sediments results using angular response model agree with the grab sampling results. The advantage of map** the seabed sedimentation using multibeam backscatter data over the grab sampling method is that it can provide the seabed sediment map** for the entire area using the MBES due to its 100% coverage of the seabed.
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Acknowledgements
This work was supported by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, Saudi Arabia. The author, therefore, acknowledges with thanks DSR technical and financial support. In addition, many thanks to Abdullah Shaheen and Abdullah Alamoudy for their help in this manuscript.
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El-Diasty, M. Map** seabed sediments for Sharm Obhur using multibeam echosounder backscatter data. Model. Earth Syst. Environ. 6, 163–171 (2020). https://doi.org/10.1007/s40808-019-00668-x
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DOI: https://doi.org/10.1007/s40808-019-00668-x