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Mapping of demersal fish and benthos by Autonomous Underwater Vehicle equipped with optical and acoustic imagers at 600 meters depth in Trondheimsfjorden

机译:在Trondheimsfjorden用装备有光学和声像仪的自主水下航行器绘制水下鱼类和底栖动物的地图,深度为600米

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摘要

The marine environment is largely under-sampled both in time and space. There is a growing need for more automated approaches to provide a better understanding, identification, mapping and monitoring of biogeochemical processes for future environmental management of biological resources present in or around the seafloor. This thesis aims at identifying and mapping demersal fish and benthos by means of an autonomous underwater vehicle (AUV) for establishing non-invasive measurements on abundance of fish and benthos. Future prospects include implementing these findings for future nature management and decision-making. A soft bottom community compiling demersal fish and benthos in the Agdenes deep water basin was surveyed using the HUGIN HUS AUV at a depth of approximately 600 m. Imagery provided by a photomosaic camera (high spatial resolution) and a synthetic aperture sonar (high spatial coverage) covering 39 200 m2 of seafloor were used for identification and mapping biological objects of interest (OOI).The findings indicates relatively high abundance of Herring smelts (Argentinidae spp.) and Rabbit fish (Chimaera monstrosa) and a wide spread distribution of other demersal fish species. Benthos, including sea stars, anemones and crabs, were relatively numerous. The sonar provided imagery of high spatial coverage, but the spatial resolution was considered to be too low for detection of biological OOI under present conditions. The photomosaic camera provided imagery of high spatial resolution enabling identification of fish species and other benthos to family or order. The AUV is considered to be a suitable tool for mapping biological habitats, being an efficient and adaptable platform for surveying features of biological significance.
机译:海洋环境在时间和空间上都采样不足。越来越需要更自动化的方法来更好地理解,识别,标测和监测生物地球化学过程,以便对海底或周围存在的生物资源进行未来的环境管理。本文旨在通过自动水下航行器(AUV)识别和绘制深海鱼类和底栖生物的图,以建立鱼类和底栖生物丰度的非侵入性测量方法。未来的前景包括将这些发现用于未来的自然管理和决策。使用HUGIN HUS AUV在大约600 m的深度对阿格德内斯深水盆地中一个沉没的鱼类和底栖生物进行了调查,调查了一个软底群落。由光镶嵌相机(高空间分辨率)和合成孔径声纳(高空间覆盖率)提供的图像覆盖了39200平方米的海底,用于识别和绘制感兴趣的生物对象(OOI)。研究结果表明鲱鱼熔炼物(Argentinidae spp。)和兔子鱼(Chimaera monstrosa)的丰度相对较高,而其他海底鱼类的分布也很广泛。包括海星,海葵和螃蟹在内的Benthos相对较多。声纳提供了高空间覆盖率的图像,但是在当前条件下,空间分辨率被认为对于检测生物OOI而言太低。光电照相机提供了高空间分辨率的图像,从而能够识别鱼类和其他底栖生物的家庭或秩序。 AUV被认为是绘制生物栖息地的合适工具,是一种有效且适用于调查生物学意义特征的平台。

著录项

  • 作者

    Håpnes Sverre Julian H;

  • 作者单位
  • 年度 2015
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  • 原文格式 PDF
  • 正文语种 eng
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