A Comparison of Imperviousness Derived from a Detailed Land Cover Dataset (DLCD) versus the National Land Cover Dataset (NLCD) at Two Time Periods

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Date
2016-09-01
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Publisher
Virginia Tech
Abstract

To address accuracy concerns of the National Land Cover Dataset (NLCD), this case study compares impervious surface from the NLCD to a Detailed Land Cover Dataset (DLCD) for the Town of Blacksburg, Virginia over two time periods (2005/2006 and 2011) at spatial aggregation scales (fine to coarse) and scopes (site-specific to area-extent). When comparing the total impervious surface area, the NLCD overestimated the DLCD by appreciable amounts (12-27%) for the entire town and across all specified land use zones for both time periods examined. A binary pixel-wise accuracy assessment of impervious surface revealed that the NLCD performed well for all scopes except for the single family land use zone (user accuracy <40%). The spatial aggregation of pixels to 90-m led to improved agreement between the two datasets. Using the DLCD as a reference, an empirical normalization equation was successfully applied to the NLCD to further reduce overestimation and data skewness.

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Keywords
Land Cover, Impervious Surface, Land Use, Remotely Sensed Imagery, Stormwater
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