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Seafloor sediment classification based on multibeam sonar data

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Geo-spatial Information Science

Abstract

The multibeam sonars can provide hydrographic quality depth data as well as hold the potential to provide calibrated measurements of the seafloor acoustic backscattering strength. There has been much interest in utilizing backscatters and images from multibeam sonar for seabed type identification and most results are obtained. This paper has presented a focused review of several main methods and recent developments of seafloor classification utilizing multibeam sonar data or/and images. These are including the power spectral analysis methods, the texture analysis, traditional Bayesian classification theory and the most active neural network approaches.

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Authors and Affiliations

  1. the First Institute of Oceanography of State Oceanic Administration, 6 Xianxialing Road, 266061, Qingdao, China

    Zhou Xinghua (professor)

Authors
  1. Zhou Xinghua
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  2. Chen Yongqi
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Additional information

Funded by the Hong Kong Polytechnic University (No. G-V931), Hong Kong RGC Project (No., BQ 734) and the National 863 Program of China (No. 2001AA613040).

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Xinghua, Z., Yongqi, C. Seafloor sediment classification based on multibeam sonar data. Geo-spat. Inf. Sci. 7, 290–296 (2004). https://doi.org/10.1007/BF02828555

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  • DOI: https://doi.org/10.1007/BF02828555

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