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Application of acoustic remote sensing in seafloor sediment classification: opportunities and challenges
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AliReza Amiri-Simkooei *   |
| University of Isfahan |
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Abstract: (4318 Views) |
| Acoustic remote sensing is a commonly used method for seafloor and riverbed sediment classification. In comparison with the conventional method of grab sampling, this method not only is of limited cost but also provides a complete overview of the bottom composition for the entire surveyed area. The use of single- and multi-beam echo-sounders data as an efficient way for seafloor and riverbed sediment classification is studied. The intensity and the shape of the received signals can provide useful information, which indicate the high potential capability of this limited-cost method. Because the received signals are subject to high statistical noise, a few mathematical and statistical tools are to be used to properly encounter this issue. The method of least-squares subject to non-negative and bounded constraints can be used for classification of multi-beam echo-sounder (MBES) data, while the principal component analysis is useful for single-beam echo-sounder (SBES) data. Two data sets on SBES and MBES will be used to illustrate the high potential capability of the proposed method for seafloor classification. The opportunities and challenges of these methods will be discussed. |
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| Keywords: Single- and multi-beam echo-sounders, seafloor sediment classification, principal component analysis |
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Full-Text [PDF 1230 kb]
(1585 Downloads)
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Type of Study: Research |
Received: 2015/09/8 | Accepted: 2015/09/8 | Published: 2015/09/8
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