I am working on a long-term research project studying changes in urban patterns in 59 of the largest metropolitan areas in the U.S. from 1950 to 2010. The research uses data on numbers of housing units by census tract. These data are used to delineate urban and exurban portions of the metropolitan areas for each census year and to study patterns and changes within those areas.

This page has links for downloading pdf documents related to this research. The papers are the more formal, complete pieces presenting the results in inquiries into various questions. The notes are informal descriptions of the data and examinations of issues arising in the course of the research.


Density of Large Urban Areas in the U.S., 1950–2010

Density is a fundamental, defining characteristic of urban areas that has important implications for many other aspects of urban life. Using census tract data for 1950 to 2010, the extent of the built-up urban areas is delineated in a consistent manner for 59 of the largest metropolitan regions in the United States. Contrary to common expectations of nearly universal decline in urban densities, many areas showed relatively stable densities or even significant increases over the period. The areas with stable or increasing densities were located in the South and, especially for increases in density, in the West. The larger declines in densities occurred in areas in the Northeast and Midwest. Density levels and changes in density were associated with the sizes of areas, prior densities, rates of growth, and the presence of barriers to urban expansion.


The Negative Exponential Decline of Density in Large Urban Areas in the U.S., 1950–2010

The monocentric model predicts the negative exponential decline of density with distance from the center, but employment in urban areas has become increasingly dispersed in multiple employment centers. Using census tract data from 1950 to 2010, the parameters of the negative exponential model are estimated for 43 large urban areas. Density gradients have declined consistently. Overall, central densities likewise declined, with exceptions for some areas that have seen more rapid growth. The average fit of the model across the areas, measured by R2, fell by nearly half after 1970, consistent with more polycentric employment patterns. Nevertheless, even for areas with extremely poor fit, negative exponential parameter estimates continued to be reasonable.


The Monocentric Model with Polycentric Employment: Ring versus Tract Estimates of the Negative Exponential Decline of Density

The increase in employment away from Central Business Districts raises questions about the continued applicability of the monocentric model and its prediction of the negative decline of density, yet the model continues to be used and produces reasonable results. This paper argues that while the development of multiple employment subcenters produces variation in density patterns resulting in declining goodness-of-fit of the negative exponential model when estimated using data for small areas, the overall pattern continues to be a general decline of density with distance. The negative exponential model is estimated using data on densities both for census tracts and concentric rings around the center for 43 large urban areas in the United States from 1950 to 2010. The R2 values for the estimates using the tract data decline steadily after 1970, while the ring estimates show only small decreases. It is further hypothesized that since more general measures of accessibility to employment may now better predict density at the tract level, distance to the center as a proxy incorporates increasing error, resulting in attenuation bias in the estimates of the density gradients, which was shown by comparing the tract and ring estimates.


The Degree of Centralization in Large Urban Areas in the U.S., 1950–2010

Levels of centralization of population and housing and the phenomenon of decentralization are an important aspect of large urban areas. A measure of centralization called the centralization ratio is developed that reflects the proportional reduction in the mean distance housing units are located from the center compared to a uniform distribution in the urban area. Values for this measure are computed using data on numbers of housing units by census tracts for 59 large urban areas defined for each census from 1950 to 2010. The results show that mean levels of centralization have declined steadily and significantly over the period. This decline was not universal, however, with 14 areas showing increases. Centralization varied by region of the country, highest in the Northeast and lowest in the South. Mean levels of centralization were also higher for the largest urban areas.


Negative Exponential Model Parameters and Centralization in Large Urban Areas in the U.S., 1950–2010

The change in the negative exponential density gradient has often been used as a measure of urban decentralization, with the gradient itself also being taken as a measure of the degree of centralization for comparing urban areas. Changes and levels of estimated negative exponential model parameters for 43 areas from 1950 to 2010 are compared with a “pure” measure of centralization, the centralization ratio. The proportional change in the density gradient is indeed significantly related to the change in the centralization ratio, while the relationship of the change in central density to centralization is inconsistent. However, the level of the density gradient is not significantly related to the level of centralization, except that controlling for the size of the urban area produces a significant relationship. The central density is related to the level of centralization.


Negative Exponential Model Parameters and the Size of Large Urban Areas in the U.S., 1950–2010

The density of urban development tends toward a negative exponential decline with distance from the center. The density gradient has been observed to be inversely related to the size of the urban area, while the central density is directly related. If the negative exponential density decline holds, the size of the urban area, the density gradient, and the central density are necessarily mathematically related. This relationship is derived, and a simplified approximation is compared with the sizes of large urban areas and the estimated density gradients and central densities. The results generally confirm the expectations, although the coefficient for the central density is larger than expected, possibly because of the use of gross rather than net residential density in estimating the parameters for the negative exponential model.


On the Choice of Combined Statistical Areas

Some Metropolitan Statistical Areas (MSAs) fail to encompass the full extent of metropolitan areas. Combined Statistical Areas (CSAs), combinations of Core-Based Statistical Areas, are larger and may be more a more appropriate choice for certain analyses. Differences between MSAs and CSAs (and some MSAs are not even included in CSAs) range from minor to the combination of large MSAs, with population increases ranging from a few percent more than doubling. The sharing of transportation infrastructure in the form of commuter rail service and shared airports demonstrates the integration of areas combined into CSAs. In addition, the extent of the MSAs defined for the 2000 census are comparable to current CSAs, which arise from a subsequent change in how metropolitan areas are defined.


Defining Exurban Areas for the Analysis of Urban Patterns Over Time

This paper addresses the issue of defining exurban areas around 59 large urban areas from 1950 to 2010. The ideal definition would include contiguous census tracts meeting a minimum density threshold and showing integration with the urban area based on commuting. Since data on the latter are not available throughout the period, only a density criterion could be used. A density minimum was selected such that the areas of contiguous exurban density in 2010 would be largely contained within the urban area’s metropolitan area boundaries, indicating a likelihood of integration with the urban area. An assessment of the resulting exurban areas shows a high degree of containment for metropolitan areas. A brief examination of the 2010 exurban areas shows they vary greatly in terms of size.



Urban Patterns Dataset Description

This note is provides a description and documentation of the data used for the Urban Patterns dataset and the methods used to delineate urban and exurban areas for each census year.


Year-Built Estimates Analaysis

The Urban Patterns dataset has estimates of the numbers of housing units in census tracts for the earlier years derived from the Census data on housing units by year-built, primarily from the 1970 census. This note provides estimates of the error associated with this estimation.


Urbanized Area Comparison

The delineation of the urban areas in the Urban Patterns dataset was modeled on the procedures currently used by the Census for delineating Urbanized Areas. This note is a comparison of the urban areas in the dataset with the Urbanized Areas.


The Effect of the Changed Definition of Metropolitan Statistical Areas

A greatly changed metropolitan area definition was first used to delineate areas in 2003. In many cases, areas considered to be single metropolitan areas in 2000 were split into multiple Metropolitan Statistical Areas in 2003. This note compared the extent of the 2000 areas with the 2003 areas to examine the effect of the change in the definition.


Problems with the Urban and Metropolitan Area Definitions

The previous note showed how changes in the metropolitan area definition resulted Metropolitan Statistical Areas in 2003 that were frequently much smaller then before. This note examines the changes to the urban and metropolitan area definitions that caused this, finding that these had become fundamentally circular definitions. For 2010, the Census Bureau compounded the problem by making the inexusable decision to freeze the set of Urbanized Areas as they were delineated for 2000. This note concludes with some initial ideas on better approaches for defining these areas.