Environmental Management (2010) 46:378–390 (MRLC) (MRLC 2009; Homer and others 2007). The 2001 NLCD provides 30-m resolution classiﬁed land cover and percentage tree canopy and impervious cover estimates for the conterminous United States derived from circa 2001 Landsat 7 imagery. Twelve mapping teams employed by the MRLC used standardized data preparation, classiﬁca- tion, and quality control to process the Landsat imagery within 65 distinct mapping zones (Huang and others 2001; Yang and others 2003; Homer and others 2004, 2007). Mapping zones were delimited to represent relative geo- graphic homogeneity with consideration of economy (cost), physiography, land-cover distribution, spectral uni- formity, and optimal edge-matching (Homer and Gallant 2001). High resolution tree canopy and impervious cover maps, derived from 1-m resolution digital orthoimagery quarter quadrangles, were used to develop unique algo- rithms for each mapping zone to estimate percentage tree canopy and impervious cover from raw Landsat 7 imagery (c. 2001). Each cover layer is accompanied by metadata documenting error estimates based on a cross-validation technique utilizing the algorithms and training data for each mapping zone (MRLC 2009; Homer and others 2007). According to these preliminary error estimates, the tree canopy cover values have an average error ranging from 6 to 17% and impervious cover has an average error ranging from 4 to 17% (MRLC 2009; Homer and others 2007). With an early and limited release of the 2001 NLCD, Walton (2008) found potential underestimation of tree canopy cover in 36 cities and villages in NLCD mapping zone 63 (western New York State). A later study was developed to compare 2001 NLCD cover estimates with photo-interpreted estimates of Google Earth imagery from randomly sampled and geographically dispersed Census- designated places (e.g., cities, villages; hereafter referred to as places) and counties in the United States (Greenﬁeld and others 2009). Results of this comparison revealed that 2001 NLCD underestimates tree canopy cover by an average of 9.7% and underestimates impervious cover by an average of 5.7% within places and 1.3% in counties. The under- estimate appeared to be consistent across the country with no statistical differences among physiographic regions. However, there were statistical differences in the degree of underestimation of tree canopy cover among mapping zones and of impervious cover by population density class. The study reported here continues this work by expanding the analysis to the entire conterminous United States to further explore the differences between NLCD-derived and photo-interpreted percentage tree canopy and impervious cover among all 65 mapping zones. Google Earth imagery is used as a reference data source for tree canopy and impervious cover estimates because of its national aerial imagery coverage. Google Earth imagery has been used to augment existing geographic data and 379 when other data sources speciﬁc to a particular application are incomplete, inconsistent, or nonexistent. For example, Google Earth has been used to evaluate the spatial distri- bution of insurance risk and natural disaster mapping and crisis management (Slingsby and others 2008; Nourbakhsh and others 2006), as reference data to validate land cover maps (Cha and Park 2007), to enable the use of volunteered geographic information to post, reference and verify geo- graphic data (Goodchild 2007; Wood and others 2007), for NLCD land cover accuracy assessments when other media were unavailable (Wickham and others 2010), and to make applications of geographic visualization and decision- making support available to the public (Sieber 2006; Butler 2006; Goodchild 2007; Sheppard and Cizek 2009). Stehman and others (2008) designed of a formal accu- racy assessment of the 2001 NLCD, which includes rec- ommended evaluation protocols to meet six deﬁned objectives. However, only the ﬁrst objective, which assesses the per-class thematic accuracy of the classiﬁed land cover, has been completed (Wickham and others 2010). The protocol set out by Stehman and others (2008) establishes a pixel-by-pixel assessment of the NLCD per- centage tree canopy and impervious data that meets several MRLC objectives. Results reported here differ in that the analysis was not designed to be a pixel-by-pixel accuracy assessment, rather it was designed to test differences between NLCD-derived and photo-interpreted estimates of overall percentage tree canopy and impervious cover for each of the 65 mapping zones. This assessment was con- ducted to provide a better understanding of the potential limitations of NLCD tree canopy and impervious cover estimates for each mapping zone. Methods The comparison between NLCD-derived and photo-inter- preted tree canopy and impervious cover percentages was conducted within the boundaries of the 65 NLCD mapping zones (MRLC 2009). The NLCD 2001 percentages for tree canopy and impervious cover for each zone were derived from zone boundary maps registered with the NLCD 2001 layers in a U.S. Geologic Survey USA Contiguous Albers Equal Area Conic projected coordinate system. The NLCD percentage tree canopy and impervious cover for the entire mapping zone polygon was extracted using GIS software (zonal statistics). Overall percentage cover in each zone was calculated as the total NLCD cover in the zone divided by the total area in each zone. These same mapping zone boundaries were used to randomly draw a sample of 1,000 points within each zone. These points then were converted and transformed into a Google Earth compatible format (Google Inc. 2007) for 123