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Acoustic Sediment Classification Using High-Frequency (400 kHz) Multibeam Data in Pari Water of Seribu Island, Indonesia

1Marine Technology Study Program, Department of Marine Science and Technology, Faculty of Fisheries and Marine Sciences, IPB University, Indonesia

2Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University, Indonesia

3Department of Computer Science, Faculty of Mathematics and Natural Science, IPB University, Indonesia

4 Department of Generative AI, Faculty of Artificial Inteligence, Universiti Teknologi Malaysia, Malaysia

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Received: 3 Nov 2024; Revised: 26 Jan 2025; Accepted: 5 Feb 2025; Available online: 1 Mar 2025; Published: 8 Mar 2025.

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Abstract

Seafloor classification is essential for understanding sediment distribution, marine habitat characteristics, and resource management. Therefore, this study aimed to classify seafloor sediment in the Pari water, Indonesia using high-frequency (400 kHz) backscatter data obtained through the Multibeam Echosounder T-50P. The Angular Range Analysis (ARA) method was applied to analyze backscatter intensity variations across different incidence angles, to enhance the accuracy of sediment classification in this shallow marine environment. Data acquisition was collected using the T-50P, which captured high-resolution acoustic signals from varying angles to generate angular response curves. Analysis was conducted in the curves were then analyzed to differentiate sediment types, with ground-truth sediment samples collected to validate classification outcomes. The result showed that backscatter intensity mosaic had an intensity range of -27 dB to -37.5 dB. Applying ARA enabled the identification of 12 sediment classes, including sandy silt, coarse silt, and clayey sand. Sediment distribution maps, generated via FMGT and visualized with ArcGIS, indicated a predominance of fine-grained sediments. The FMGT-based classification tended to prioritize finer sediment categories, likely due to the acoustic limitations in detecting granular details. Conversely, the in-situ analysis of 15 sediment samples revealed medium sand as the predominant sediment type, accompanied by smaller proportions of coarse sand and coral fragments. The discrepancies between the in-situ sampling and FMGT results were primarily due to the operational frequency of the MBES system, which limits the acoustic signal's penetration to the surface of the seabed. This highlights the importance of in-situ sampling to complement acoustic data, especially in accurately seabed characterization. 

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Keywords: Pari Island; Multibeam Echosounder System (MBES); Backscatter; Seafloor Classification
Funding: PDD IPB under contract 22133/IT3.D10/PT.01.03/P/B/2024.

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