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    Seabed mapping and characterization of sediment variability using the usSEABED data base

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    CSR957_revised.pdf (3.867Mb)
    Date
    2007-03
    Author
    Goff, John A.  Concept link
    Jenkins, Chris J.  Concept link
    Williams, S. Jeffress  Concept link
    Metadata
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    Citable URI
    https://hdl.handle.net/1912/2252
    As published
    https://doi.org/10.1016/j.csr.2007.11.011
    Keyword
     Grain size; Continental shelf; Database; Semivariogram; Statistical analysis; Kriging 
    Abstract
    We present a methodology for statistical analysis of randomly-located marine sediment point data, and apply it to the U.S. continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses (“extracted”) and from word-based descriptions (“parsed”) are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionallydependent conversion factor between the two. Our analysis of sample regions on the U.S. continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained. Surprisingly, parsed and extracted noise magnitudes correlate with each other, which may indicate that some portion of the data variability that we identify as “noise” is caused by real grain size variability at very short scales. Our analyses demonstrate that by applying a bias-correction proxy, usSEABED data can be used to generate reliable interpolated maps of regional mean grain size and sediment character.
    Description
    Author Posting. © The Author(s), 2007. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Continental Shelf Research 28 (2008): 614-633, doi:10.1016/j.csr.2007.11.011.
    Collections
    • Coastal and Shelf Geology
    Suggested Citation
    Preprint: Goff, John A., Jenkins, Chris J., Williams, S. Jeffress, "Seabed mapping and characterization of sediment variability using the usSEABED data base", 2007-03, https://doi.org/10.1016/j.csr.2007.11.011, https://hdl.handle.net/1912/2252
     
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