Seabed classification from acoustic profiling data using the similarity index SCIE SCOPUS

Cited 18 time in WEB OF SCIENCE Cited 0 time in Scopus
Title
Seabed classification from acoustic profiling data using the similarity index
Author(s)
Kim, HJ; Chang, JK; Jou, HT; Park, GT; Suk, BC; Kim, KY
Alternative Author(s)
김한준; 주형태; 박건태; 석봉출
Publication Year
2002-02
Abstract
We introduce the similarity index (SI) for the classification of the sea floor from acoustic profiling data. The essential part of our approach is the singular value decomposition of the data to extract a signal coherent trace-to-trace using the Karhunen-Loeve transform. SI is defined as the percentage of the energy of the coherent part contained in the bottom return signals. Important aspects of SI are that it is easily computed and that it represents the textural roughness of the sea floor as a function of grain size, hardness, and a degree of sediment sorting. In a real data example, we classified a section of the sea floor off Cheju Island south of the Korean Peninsula and compared the result with the sedimentology defined from direct sediment sampling and side scan sonar records. The comparison shows that SI can efficiently discriminate the bottom properties by delineating sediment-type boundaries and transition zones in more detail. Therefore, we propose that SI is an effective parameter for geoacoustic modeling. (C) 2002 Acoustical Society of America.
ISSN
0001-4966
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/5744
DOI
10.1121/1.1433812
Bibliographic Citation
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, v.111, no.2, pp.794 - 799, 2002
Publisher
ACOUSTICAL SOC AMER AMER INST PHYSICS
Subject
SONAR
Type
Article
Language
English
Document Type
Article
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