Monitoring fish using imaging sonar: Capacity, challenges and future perspective

IF 5.6 1区 农林科学 Q1 FISHERIES
Yaoguang Wei, Yunhong Duan, Dong An
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引用次数: 15

Abstract

The demand for fish products, which provide crucial protein for humans, is rising as the global population grows. In contrast, fish stock is declining due to human activity, environmental changes and overfishing. Fish monitoring provides valuable support data for effective fishery management and ecosystem conservation. The common monitoring methods are based on manual sampling, which is time-consuming, laborious and intrusive. Imaging sonar is a hydroacoustic system that produces acoustic images similar to optical images by transmitting and receiving sound waves, allowing for in situ monitoring of fish non-intrusively in the dark and turbid water environments where optical cameras are limited. In the last decade, imaging sonar, especially high frequency multibeam forward-looking sonar and side-scan sonar, has been widely used in fish monitoring. We reviewed the literature from the previous decade on the use of these two types of imaging sonar in fish species identification, abundance estimation, length measurement and behaviour analysis, as well as the sonar imagery processing concerning fish. The review results show that these imaging sonars are efficient and effective tools for fish monitoring in complex environments. The challenges include (1) the recognition of small fish forming dense aggregations; (2) species identification, which limits their use in species-specific studies; (3) time-consuming massive data processing. Therefore, advanced algorithms for sonar imagery processing and integrations with other sampling technologies are needed for future development.

利用成像声纳监测鱼类:能力、挑战和未来展望
随着全球人口的增长,对为人类提供重要蛋白质的鱼类产品的需求正在上升。相比之下,由于人类活动、环境变化和过度捕捞,鱼类资源正在减少。鱼类监测为有效的渔业管理和生态系统保护提供了宝贵的支持数据。常用的监测方法是基于人工采样,耗时、费力且侵入性强。成像声纳是一种水声系统,通过发射和接收声波产生类似于光学图像的声学图像,允许在光学摄像机有限的黑暗和浑浊水环境中对鱼类进行非侵入性的原位监测。近十年来,成像声纳尤其是高频多波束前视声纳和侧扫声纳在鱼类监测中得到了广泛的应用。本文综述了近十年来这两种成像声纳在鱼类种类识别、丰度估算、长度测量和行为分析以及声纳图像处理方面的研究进展。研究结果表明,这些成像声纳是复杂环境下鱼类监测的有效工具。面临的挑战包括:(1)识别形成密集聚集的小鱼;(2)物种鉴定,这限制了它们在物种特异性研究中的应用;(3)耗时的海量数据处理。因此,未来的发展需要先进的声纳图像处理算法,并与其他采样技术相结合。
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来源期刊
Fish and Fisheries
Fish and Fisheries 农林科学-渔业
CiteScore
12.80
自引率
6.00%
发文量
83
期刊介绍: Fish and Fisheries adopts a broad, interdisciplinary approach to the subject of fish biology and fisheries. It draws contributions in the form of major synoptic papers and syntheses or meta-analyses that lay out new approaches, re-examine existing findings, methods or theory, and discuss papers and commentaries from diverse areas. Focal areas include fish palaeontology, molecular biology and ecology, genetics, biochemistry, physiology, ecology, behaviour, evolutionary studies, conservation, assessment, population dynamics, mathematical modelling, ecosystem analysis and the social, economic and policy aspects of fisheries where they are grounded in a scientific approach. A paper in Fish and Fisheries must draw upon all key elements of the existing literature on a topic, normally have a broad geographic and/or taxonomic scope, and provide general points which make it compelling to a wide range of readers whatever their geographical location. So, in short, we aim to publish articles that make syntheses of old or synoptic, long-term or spatially widespread data, introduce or consolidate fresh concepts or theory, or, in the Ghoti section, briefly justify preliminary, new synoptic ideas. Please note that authors of submissions not meeting this mandate will be directed to the appropriate primary literature.
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