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    Author(s): Monica Lipscomb Smith; Weiqi Zhou; Mary Cadenasso; J. Morgan Grove; Lawrence Band
    Date: 2010
    Source: Journal of The American Water Resources Association. 46(2): 429-442.
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: View PDF  (972.99 KB)


    We compared the National Land Cover Database (NLCD) 2001 land cover, impervious, and canopy data products to land cover data derived from 0.6-m resolution three-band digital imagery and ancillary data. We conducted this comparison at the 1 km2, 9 km2, and gauged watershed scales within the Baltimore Ecosystem Study to determine the usefulness and limitations of the NLCD in heterogeneous urban to exurban environments for the determination of land-cover information for hydrological applications. Although the NLCD canopy and impervious data are significantly correlated with the high-resolution land-cover dataset, both layers exhibit bias at <10 and >70% cover. The ratio of total impervious area and connected impervious area differs along the range of percent imperviousness - at low percent imperviousness, the NLCD is a better predictor of pavement alone, whereas at higher percent imperviousness, buildings and pavement together more resemble NLCD impervious estimates. The land-cover composition and range for each NLCD urban land category (developed open space, low-intensity, medium-intensity, and high-intensity developed) is more variable in areas of low-intensity development. Fine-vegetation land-cover/lawn area is incorporated in a large number of land use categories with no ability to extract this land cover from the NLCD. These findings reveal that the NLCD may yield important biases in urban, suburban, and exurban hydrologic analyses where land cover is characterized by fine-scale spatial heterogeneity.

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    Smith, Monica Lipscomb; Zhou, Weiqi; Cadenasso, Mary; Grove, J. Morgan; Band, Lawrence. 2010. Evaluation of the National Land Database for Hydrologic Applications in Urban And Suburban Baltimore, Maryland. Journal of The American Water Resources Association. 46(2): 429-442.


    National Land Cover Database, Baltimore, land use/land cover, urban areas, remote sensing, lawn, impervious surface

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