Analysis of urban land cover and population density in the United States

In this study we investigate the question of whether urban and suburban areas in the United States can be defined on the basis of demographic and/or physical characteristics, in particular, population density and vegetation abundance. We investigate their relationship in the cities of Atlanta, Chicago, Los Angeles, New York, Phoenix, and Seattle and compare the results with the USGS National Land Cover Dataset's urban classes. The bimodal distribution of U.S. population density provides a demographic basis for distinguishing rural and suburban land use, while a distinct tail of high population densities (> 10,000 people/km(2)) corresponds to high intensity urban residential cores. Results show that the maximum vegetation fraction diminishes with increasing population density, but the spectral heterogeneity at pixel scales still results in a wide range of vegetation fractions within demographically urban and suburban areas. None of the USGS residential classes show a strong correspondence to either vegetation fraction or population density. However, quantitative characterization of vegetation abundance provides a basis for comparison of the physical environments Of suburban areas. We suggest that classification schemes based on spectral heterogeneity at multiple pixel scales, supplemented by auxiliary data sources, may provide a more accurate and self-consistent way to quantify urban land use and analyze urban growth than traditional thematic classification schemes.