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    Potential contribution of residuals for better prediction of soil salinity from remote sensing data

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    Citable Link(s)
    https://hdl.handle.net/10217/200640
    http://dx.doi.org/10.25675/10217/200640
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    CONF_HydroDays_EldeiryGarcia_2006.pdf (457.2Kb)
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    Abstract
    Soil salinity predictions derived from Ikonos and Landsat satellite images are compared with field-collected soil salinity data for a study area in Colorado's lower Arkansas River Basin. The accuracy of the predictions is compared and issues of price, resolution, and coverage area are considered. Stepwise regression is used to select the combination of bands in the satellite images that best correlate with the field data. The Ordinary Least Squares (OLS) model is used to predict soil salinity using the combination of bands that resulted from the stepwise regression. The residuals for the OLS ...
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    Author(s)
    Eldeiry, Ahmed; Garcia Luis A.

    Date Issued
    2006
    Format
    born digital; proceedings (reports)
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    • Hydrology Days
    • Hydrology Days - Department of Civil and Environmental Engineering

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