Seafloor classification from multibeam backscatter data using learning vector quantization neural network

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作者
Tang, Qiuhua
Zhou, Xinghua
Ding, Jisheng
Liu, Baohua
机构
[1] College of Marine Geosciences, Ocean University of China, 5 Yushan Road, Qingdao 266003, China
[2] First Institute of Oceanography, State Oceanic Administration, 6 Xianxialing Road, Qingdao 266061, China
[3] Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
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We utilize the seafloor backscatter strength data of each beam from multibeam sonar systems and the automatic classification technology to get the seafloor type identification maps. We primarily study on the seafloor classification using learning vector quantization (LVQ) neural network method. Using this classification method, we can rapidly identify all kinds of seafloor types, such as sand, gravel and rock in the experimental surveying areas.
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页码:229 / 232
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