20 research outputs found

    Quantitative Inter-channel Calibration of SHOALS Signals for Consistent Bottom Segmentation and Characterization

    Get PDF

    On the Horizon: Better Bottom Detection for Areas of Sub-Aquatic Vegetation

    Get PDF
    Bottom detection methods in single beam echo sounding (SBES) are often less robust in areas with subaquatic vegetation. Due to current mapping efforts emphasizing near shore coverage for safety of navigation and the mission for alternative uses of hydrographic quality data with the Integrated Ocean and Coastal Mapping (IOCM) Center, there is a requirement for both robust bottom detection in areas with complex vegetation and delineation of the vegetated areas themselves. Vegetation can often be found growing in close proximity to rocks and other features of navigational significance and would provide valuable information to fisheries if prime fish habitats like eelgrass could also be mapped with the navigational hazards. A bottom detection algorithm implemented in the program TracEd is being evaluated for handling bottom detections on eelgrass in the water column. This algorithm allows for detections of multiple returns in a full waveform trace for each ping. Each of these returns is then tagged as being associated to seafloor or water column features. Should this algorithm prove to be more robust in recognizing returns from vegetation and identifying the underlying bottom, a systematic approach for NOAA to more accurately determine depth in areas of sub-aquatic vegetation might be possible. A full waveform SBES dataset collected in New Hampshire’s Great Bay Estuary is under analysis to determine whether bare earth can be distinguished from the eelgrass canopy in this area where eelgrass is common and well studied. Additionally, characteristics of the waveform necessary for bottom detection are also being evaluated for eelgrass mapping

    Mapping and Characterizing Subtidal Oyster Reefs Using Acoustic Techniques, Underwater Videography and Quadrat Counts

    Get PDF
    Populations of the eastern oyster Crassostrea virginica have been in long-term decline in most areas. A major hindrance to effective oyster management has been lack of a methodology for accurately and economically obtaining data on their distribution and abundance patterns. Here, we describe early results from studies aimed at development of a mapping and monitoring protocol involving acoustic techniques, underwater videography, and destructive sampling (excavated quadrats). Two subtidal reefs in Great Bay, New Hampshire, were mapped with side-scan sonar and with videography by systematically imaging multiple sampling cells in a grid covering the same areas. A single deployment was made in each cell, and a 5-10-s recording was made of a 0.25-m2 area; the location of each image was determined using a differential global position system. A still image was produced for each of the cells and all (n = 40 or 44) were combined into a single photomontage overlaid onto a geo-referenced base map for each reef using Arc View geographic information system. Quadrat (0.25 m2 ) samples were excavated from 9 or 10 of the imaged areas on each reef, and all live oysters were counted and measured. Intercomparisons of the acoustic, video, and quadrat data suggest: (1) acoustic techniques and systematic videography can readily delimit the boundaries of oyster reefs; (2) systematic videography can yield quantitative data on shell densities and information on reef structure; and (3) some combination of acoustics, systematic videography, and destructive sampling can provide spatially detailed information on oyster reef characteristics

    TracEd: A Remote Acoustic Seafloor Characterization System for Use with Vertical Incidence Echosounders

    No full text
    TracEd is a tool developed for the assessment of the performance of several seafloor characterization methods. It is attempted to give the user a full understanding of the various aspects of collected data through simultaneous visualization in various data spaces

    Waveform characterization, clustering and segmentation of SHOALS

    No full text

    Mapping Benthic Habitat at Various scales in the Olympic National Marine Sanctuary, WA

    No full text

    Bottom Segmentation and Classification Using Expectation-maximization Clustering Methods on SHOALS Data

    No full text
    corecore