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Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore,Maryland1
Authors:Monica Lipscomb Smith  Weiqi Zhou  Mary Cadenasso  Morgan Grove  Lawrence E Band
Institution:1. Respectively, Doctoral Candidate, Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, 9601 50th Place, College Park, Maryland 20740;2. Post-Doctoral Research Fellow, Department of Plant Sciences, University of California at Davis, Davis, California 95616;3. Assistant Professor, Department of Plant Sciences, University of California at Davis, Davis, California 95616;4. Research Forester, Unit, Northern Research Station, U.S. Forest Service South Burlington, Vermont 05403;5. Director, Carolina Institute for the Environment and Voit Gilmore Distinguished Professor, Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
Abstract:Smith, Monica Lipscomb, Weiqi Zhou, Mary Cadenasso, Morgan Grove, and Lawrence E. Band, 2010. Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore, Maryland. Journal of the American Water Resources Association (JAWRA) 46(2):429-442. DOI: 10.1111/j.1752-1688.2009.00412.x Abstract: 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.
Keywords:National Land Cover Database  Baltimore  land use/land cover  urban areas  remote sensing  lawn  impervious surface
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