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Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore, Maryland 1
Author(s) -
Smith Monica Lipscomb,
Zhou Weiqi,
Cadenasso Mary,
Grove Morgan,
Band Lawrence E.
Publication year - 2010
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2009.00412.x
Subject(s) - impervious surface , land cover , environmental science , watershed , land use , hydrology (agriculture) , geology , ecology , geotechnical engineering , machine learning , computer science , biology
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 km 2 , 9 km 2 , 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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