Comparison of manual and semi-automatic underwater imagery analyses for monitoring of benthic hard-bottom organisms at offshore renewable energy installations

The construction of new offshore wind farms is one of the strategies to fulfill growing demands for ‘‘green’’ renewable energy. Underwater imagery is an important tool in the environmental monitoring of offshore renewable energy installations, especially in rocky benthic environment where traditiona...

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Published in:Hydrobiologia
Main Authors: Šaškov, Aleksej, Dahlgren, Thomas G., Rzhanov, Yuri, Schläppy, Marie-Lise
Format: Article in Journal/Newspaper
Language:English
Published: 2015
Subjects:
Online Access:http://ku.lvb.lt/KU:ELABAPDB8755576&prefLang=en_US
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spelling ftlithuaniansrc:oai:elaba:8755576 2023-05-15T17:47:06+02:00 Comparison of manual and semi-automatic underwater imagery analyses for monitoring of benthic hard-bottom organisms at offshore renewable energy installations Šaškov, Aleksej Dahlgren, Thomas G. Rzhanov, Yuri Schläppy, Marie-Lise 2015 http://ku.lvb.lt/KU:ELABAPDB8755576&prefLang=en_US eng eng info:eu-repo/semantics/altIdentifier/doi/10.1007/s10750-014-2072-5 http://ku.lvb.lt/KU:ELABAPDB8755576&prefLang=en_US Hydrobiologia, Dordrecht : Springer, 2015, vol. 756, iss. 1, p. 139-153 ISSN 0018-8158 eISSN 1573-5117 Underwater video Benthic cover estimation Features color Automatic image analysis Video mosaics info:eu-repo/semantics/article 2015 ftlithuaniansrc https://doi.org/10.1007/s10750-014-2072-5 2021-12-02T01:23:46Z The construction of new offshore wind farms is one of the strategies to fulfill growing demands for ‘‘green’’ renewable energy. Underwater imagery is an important tool in the environmental monitoring of offshore renewable energy installations, especially in rocky benthic environment where traditional techniques are not applicable. Underwater video from the high energy Norwegian Sea coast was used for this study. Traditional manual point-based benthic cover estimations from selected frames were tested against a semi-automatic approach which involved making mosaic images from underwater videos. The study demonstrates that results of manual and semiautomatic benthic cover estimations are similar, although the manual analysis has a much larger spread in the variability of the data with many outliers due to the limited amount of points used in the analysis. Although the number of benthic features that could be extracted by computer using color is fewer than those that can be detected with the human eye, the described semi-automatic method is less biased and less costly in terms of qualified staff. Implementation of the semiautomatic method does not require any programming skills and has the ability to quickly and simply process larger amount of underwater imagery which would be of decisive advantage to the industry. Article in Journal/Newspaper Norwegian Sea LSRC VL (Lithuanian Social Research Centre Virtual Library) Norwegian Sea Hydrobiologia 756 1 139 153
institution Open Polar
collection LSRC VL (Lithuanian Social Research Centre Virtual Library)
op_collection_id ftlithuaniansrc
language English
topic Underwater video
Benthic cover estimation
Features color
Automatic image analysis
Video mosaics
spellingShingle Underwater video
Benthic cover estimation
Features color
Automatic image analysis
Video mosaics
Šaškov, Aleksej
Dahlgren, Thomas G.
Rzhanov, Yuri
Schläppy, Marie-Lise
Comparison of manual and semi-automatic underwater imagery analyses for monitoring of benthic hard-bottom organisms at offshore renewable energy installations
topic_facet Underwater video
Benthic cover estimation
Features color
Automatic image analysis
Video mosaics
description The construction of new offshore wind farms is one of the strategies to fulfill growing demands for ‘‘green’’ renewable energy. Underwater imagery is an important tool in the environmental monitoring of offshore renewable energy installations, especially in rocky benthic environment where traditional techniques are not applicable. Underwater video from the high energy Norwegian Sea coast was used for this study. Traditional manual point-based benthic cover estimations from selected frames were tested against a semi-automatic approach which involved making mosaic images from underwater videos. The study demonstrates that results of manual and semiautomatic benthic cover estimations are similar, although the manual analysis has a much larger spread in the variability of the data with many outliers due to the limited amount of points used in the analysis. Although the number of benthic features that could be extracted by computer using color is fewer than those that can be detected with the human eye, the described semi-automatic method is less biased and less costly in terms of qualified staff. Implementation of the semiautomatic method does not require any programming skills and has the ability to quickly and simply process larger amount of underwater imagery which would be of decisive advantage to the industry.
format Article in Journal/Newspaper
author Šaškov, Aleksej
Dahlgren, Thomas G.
Rzhanov, Yuri
Schläppy, Marie-Lise
author_facet Šaškov, Aleksej
Dahlgren, Thomas G.
Rzhanov, Yuri
Schläppy, Marie-Lise
author_sort Šaškov, Aleksej
title Comparison of manual and semi-automatic underwater imagery analyses for monitoring of benthic hard-bottom organisms at offshore renewable energy installations
title_short Comparison of manual and semi-automatic underwater imagery analyses for monitoring of benthic hard-bottom organisms at offshore renewable energy installations
title_full Comparison of manual and semi-automatic underwater imagery analyses for monitoring of benthic hard-bottom organisms at offshore renewable energy installations
title_fullStr Comparison of manual and semi-automatic underwater imagery analyses for monitoring of benthic hard-bottom organisms at offshore renewable energy installations
title_full_unstemmed Comparison of manual and semi-automatic underwater imagery analyses for monitoring of benthic hard-bottom organisms at offshore renewable energy installations
title_sort comparison of manual and semi-automatic underwater imagery analyses for monitoring of benthic hard-bottom organisms at offshore renewable energy installations
publishDate 2015
url http://ku.lvb.lt/KU:ELABAPDB8755576&prefLang=en_US
geographic Norwegian Sea
geographic_facet Norwegian Sea
genre Norwegian Sea
genre_facet Norwegian Sea
op_source Hydrobiologia, Dordrecht : Springer, 2015, vol. 756, iss. 1, p. 139-153
ISSN 0018-8158
eISSN 1573-5117
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1007/s10750-014-2072-5
http://ku.lvb.lt/KU:ELABAPDB8755576&prefLang=en_US
op_doi https://doi.org/10.1007/s10750-014-2072-5
container_title Hydrobiologia
container_volume 756
container_issue 1
container_start_page 139
op_container_end_page 153
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