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The protocol set out by Stehman and others (2008) establishes a pixel-by-pixel assessment of the NLCD percentage tree canopy and impervious data that meets several MRLC objectives.
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We elected to match the impervious surface data and census data closest in time to the tree canopy data.
Tree canopy and impervious cover data provide essential information related to natural resources and development planning and policies at the local to national scale.
While the NLCD tree canopy cover and impervious surface data are a free and easily accessible data set created with consistent methodology that may be used effectively in comparisons across the United States, users of the NLCD tree canopy cover maps should be aware of the overall and variable underestimation of tree canopy and impervious cover.
One approach to overcome some of these problems is to use the 2001 impervious cover data, which is provided as a complement to the 2001 NLCD land cover data.
Impervious surface data is important for urban planning and environmental and resources management.
Impervious area data were derived from the Landsat images using superior ensemble learning method of rotation forest.
Combined with built-up densities derived from the impervious surface data, the classification produces morphological/functional maps that clearly show the urban dynamics in Dublin between 1988 and 2001.
Finally, the percent forest and percent impervious surface data are available for each watershed within the study area and may be reported as such if a resource manager is interested in a particular portion of the park(s).
While a formal accuracy assessment of NLCD land cover estimates has been conducted (Wickham and others 2010), a formal accuracy assessment of NLCD tree canopy and impervious cover data has yet to be completed (Stehman and others 2008; US EPA 2010).
The potential of the impervious surface fraction data for hydrological modeling is illustrated by a case study for the Kleine Nete catchment, Belgium.
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