Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast
Without knowledge of basic seafloor characteristics, the ability to address any number of critical marine and/or coastal management issues is diminished. For example,management and conservation of essential fish habitat (EFH), a requirement mandated by federally guided fishery management plans (FMPs), requires among other things adescription of habitats for federally managed species. Although the list of attributes important to habitat are numerous, the ability to efficiently and effectively describe many, and especially at the scales required, does not exist with the tools currently available. However, several characteristics of seafloor morphology are readily obtainable at multiple scales and can serve as useful descriptors of habitat. Recent advancements in acoustic technology, such as multibeam echosounding (MBES), can provide remote indication of surficial sediment properties such as texture, hardness, or roughness, and further permit highly detailed renderings of seafloor morphology. With acoustic-based surveys providing a relatively efficient method for data acquisition, there exists a need forefficient and reproducible automated segmentation routines to process the data. Using MBES data collected by the Olympic Coast National Marine Sanctuary (OCNMS), andthrough a contracted seafloor survey, we expanded on the techniques of Cutter et al. (2003) to describe an objective repeatable process that uses parameterized local Fourierhistogram (LFH) texture features to automate segmentation of surficial sediments from acoustic imagery using a maximum likelihood decision rule. Sonar signatures andclassification performance were evaluated using video imagery obtained from a towed camera sled. Segmented raster images were converted to polygon features and attributedusing a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999) for use in a geographical information system (GIS). (PDF contains 41 pages.)
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Format: | monograph biblioteca |
Language: | English |
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NOAA/National Ocean Service/National Marine Sanctuary Program
2007
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Subjects: | Ecology, Management, Fisheries, Environment, Benthic, Habitat mapping, Sediment classification, Multibeam echosounder, Local Fourier histogram texture features, Essential fish habitat, Olympic Coast National Marine Sanctuary, |
Online Access: | http://hdl.handle.net/1834/20082 |
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dig-aquadocs-1834-200822021-07-12T03:27:05Z Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast Intelmann, Steven S. Cutter, George R. Beaudoin, Jonathan D. Ecology Management Fisheries Environment Benthic Habitat mapping Sediment classification Multibeam echosounder Local Fourier histogram texture features Essential fish habitat Olympic Coast National Marine Sanctuary Without knowledge of basic seafloor characteristics, the ability to address any number of critical marine and/or coastal management issues is diminished. For example,management and conservation of essential fish habitat (EFH), a requirement mandated by federally guided fishery management plans (FMPs), requires among other things adescription of habitats for federally managed species. Although the list of attributes important to habitat are numerous, the ability to efficiently and effectively describe many, and especially at the scales required, does not exist with the tools currently available. However, several characteristics of seafloor morphology are readily obtainable at multiple scales and can serve as useful descriptors of habitat. Recent advancements in acoustic technology, such as multibeam echosounding (MBES), can provide remote indication of surficial sediment properties such as texture, hardness, or roughness, and further permit highly detailed renderings of seafloor morphology. With acoustic-based surveys providing a relatively efficient method for data acquisition, there exists a need forefficient and reproducible automated segmentation routines to process the data. Using MBES data collected by the Olympic Coast National Marine Sanctuary (OCNMS), andthrough a contracted seafloor survey, we expanded on the techniques of Cutter et al. (2003) to describe an objective repeatable process that uses parameterized local Fourierhistogram (LFH) texture features to automate segmentation of surficial sediments from acoustic imagery using a maximum likelihood decision rule. Sonar signatures andclassification performance were evaluated using video imagery obtained from a towed camera sled. Segmented raster images were converted to polygon features and attributedusing a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999) for use in a geographical information system (GIS). (PDF contains 41 pages.) 2021-06-24T15:18:24Z 2021-06-24T15:18:24Z 2007 monograph http://hdl.handle.net/1834/20082 en Marine Sanctuaries Conservation Series http://sanctuaries.noaa.gov/science/conservation/pdfs/ozette.pdf application/pdf application/pdf NOAA/National Ocean Service/National Marine Sanctuary Program Silver Spring, MD http://aquaticcommons.org/id/eprint/2277 403 2011-09-29 19:20:16 2277 United States National Ocean Service |
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Ecology Management Fisheries Environment Benthic Habitat mapping Sediment classification Multibeam echosounder Local Fourier histogram texture features Essential fish habitat Olympic Coast National Marine Sanctuary Ecology Management Fisheries Environment Benthic Habitat mapping Sediment classification Multibeam echosounder Local Fourier histogram texture features Essential fish habitat Olympic Coast National Marine Sanctuary |
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Ecology Management Fisheries Environment Benthic Habitat mapping Sediment classification Multibeam echosounder Local Fourier histogram texture features Essential fish habitat Olympic Coast National Marine Sanctuary Ecology Management Fisheries Environment Benthic Habitat mapping Sediment classification Multibeam echosounder Local Fourier histogram texture features Essential fish habitat Olympic Coast National Marine Sanctuary Intelmann, Steven S. Cutter, George R. Beaudoin, Jonathan D. Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast |
description |
Without knowledge of basic seafloor characteristics, the ability to address any number of critical marine and/or coastal management issues is diminished. For example,management and conservation of essential fish habitat (EFH), a requirement mandated by federally guided fishery management plans (FMPs), requires among other things adescription of habitats for federally managed species. Although the list of attributes important to habitat are numerous, the ability to efficiently and effectively describe many, and especially at the scales required, does not exist with the tools currently available. However, several characteristics of seafloor morphology are readily obtainable at multiple scales and can serve as useful descriptors of habitat. Recent advancements in acoustic technology, such as multibeam echosounding (MBES), can provide remote indication of surficial sediment properties such as texture, hardness, or roughness, and further permit highly detailed renderings of seafloor morphology. With acoustic-based surveys providing a relatively efficient method for data acquisition, there exists a need forefficient and reproducible automated segmentation routines to process the data. Using MBES data collected by the Olympic Coast National Marine Sanctuary (OCNMS), andthrough a contracted seafloor survey, we expanded on the techniques of Cutter et al. (2003) to describe an objective repeatable process that uses parameterized local Fourierhistogram (LFH) texture features to automate segmentation of surficial sediments from acoustic imagery using a maximum likelihood decision rule. Sonar signatures andclassification performance were evaluated using video imagery obtained from a towed camera sled. Segmented raster images were converted to polygon features and attributedusing a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999) for use in a geographical information system (GIS). (PDF contains 41 pages.) |
format |
monograph |
topic_facet |
Ecology Management Fisheries Environment Benthic Habitat mapping Sediment classification Multibeam echosounder Local Fourier histogram texture features Essential fish habitat Olympic Coast National Marine Sanctuary |
author |
Intelmann, Steven S. Cutter, George R. Beaudoin, Jonathan D. |
author_facet |
Intelmann, Steven S. Cutter, George R. Beaudoin, Jonathan D. |
author_sort |
Intelmann, Steven S. |
title |
Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast |
title_short |
Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast |
title_full |
Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast |
title_fullStr |
Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast |
title_full_unstemmed |
Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast |
title_sort |
automated, objective texture segmentation of multibeam echosounder data - seafloor survey and substrate maps from james island to ozette lake, washington outer coast |
publisher |
NOAA/National Ocean Service/National Marine Sanctuary Program |
publishDate |
2007 |
url |
http://hdl.handle.net/1834/20082 |
work_keys_str_mv |
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_version_ |
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