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 (30 m and 90 m) and scopes (site-specific to area-extent). When comparing the total impervious surface area, the NLCD overestimated significant amounts (12 to 27 percent) for the entire town and across all specified land use zones (single family, multi-family, and non-residential) for both time periods examined. A binary pixel-wise accuracy assessment of impervious surface revealed that the NLCD performed well for the multi-family and non-residential land use zones. However, accuracy level was quite low (user’s accuracy <40 percent) for the single family land use zone. Percent impervious surface of NLCD and DLCD was further compared at 30 m and 90 m spatial scales. The spatial aggregation of pixels to 90 m led to improved agreement between the two datasets, although NLCD still showed an underestimate of high values and an overestimate of low values. An empirical normalization equation was successfully applied to the NLCD to further reduce such data skewness.