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首页> 外文期刊>Estuarine Coastal and Shelf Science >Acoustic mapping and classification of benthic habitat using unsupervised learning in artificial reef water
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Acoustic mapping and classification of benthic habitat using unsupervised learning in artificial reef water

机译：人工礁水中无监督学习的底栖生境声图绘制和分类

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摘要

Artificial reefs (ARs) are effective means to maintain fishery resources and to restore ecological environment in coastal waters. ARs have been, widely constructed along the Chinese coast. However, understanding of benthic habitats in the vicinity of ARs is limited, hindering effective fisheries and aquacultural management. Multibeam echosounder (MBES) is an advanced acoustic instrument capable of efficiently generating large-scale maps of benthic environments at fine resolutions. The objective of this study is to develop a technical approach to characterize, classify, and map shallow coastal areas with ARs using an MBES. An automated classification method is designed and tested to process bathymetric and backscatter data from MBES and transform the variables into simple, easily visualized maps. To reduce the redundancy in acoustic variables, a principal component analysis (PCA) is used to condense the highly collinear dataset. An acoustic benthic map of bottom sediments is classified using an iterative self-organizing data analysis technique (ISODATA). The approach is tested with MBES surveys in a 1.15 km(2) fish farm with a high density of ARs off the Yantai coast in northern China. Using this method, 3 basic benthic habitats (sandy bottom, muddy sediments, and ARs) are distinguished. The results of the classification are validated using sediment samples and underwater surveys. Our study shows that the use of MBES is an effective method for acoustic mapping and classification of ARs. (C) 2016 Elsevier Ltd. All rights reserved.
机译：人工鱼礁是维持渔业资源和恢复沿海水域生态环境的有效手段。增强现实已经在中国沿海地区广泛建造。然而，对ARs附近底栖生境的了解有限，这阻碍了有效的渔业和水产养殖管理。多波束回声测深仪（MBES）是一种先进的声学仪器，能够有效地以高分辨率生成海底环境的大规模地图。这项研究的目的是开发一种利用MBES对具有AR的浅海沿海地区进行表征，分类和绘制地图的技术方法。设计并测试了一种自动分类方法，用于处理MBES的测深和后向散射数据，并将变量转换为简单，可视化的地图。为了减少声学变量的冗余，使用主成分分析（PCA）来压缩高度共线的数据集。使用迭代自组织数据分析技术（ISODATA）对底部沉积物的底栖声学图进行分类。该方法已通过MBES调查在中国北方烟台沿海1.15 km（2）高AR密度的养鱼场进行了测试。使用此方法，可以区分3个基本底栖生境（沙质底部，泥泞的沉积物和ARs）。使用沉积物样本和水下调查验证了分类结果。我们的研究表明，MBES的使用是对AR进行声学映射和分类的有效方法。 （C）2016 Elsevier Ltd.保留所有权利。

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  • 来源
    《Estuarine Coastal and Shelf Science》 |2017年第5期|11-21|共11页
  • 作者

    Li Dong; Tang Cheng; Xia Chunlei; Zhang Hua;

  • 作者单位

    Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Zone Environm Proc & Ecol Remedia, Yantai, Shandong, Peoples R China|Univ Chinese Acad Sci, Beijing, Peoples R China;

    Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Zone Environm Proc & Ecol Remedia, Yantai, Shandong, Peoples R China;

    Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Zone Environm Proc & Ecol Remedia, Yantai, Shandong, Peoples R China;

    Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Zone Environm Proc & Ecol Remedia, Yantai, Shandong, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Artificial reef; Acoustic mapping; Automated classification; Multibeam echosounder;

    机译：人工礁;声波测绘;自动分类;多波束回声测深;

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