Typologies of sprawl: investigating United States metropolitan land use patterns

Abstract

We investigate patterns of residential and nonresidential land use in 311 United States metropolitan (Extended Urban) areas in 2000 using four measures: intensity, compactness, mixing, and core-dominance. A cluster analysis revealed four distinctive groups of land use patterns: (1) Most-Intense, Least-Compact, Least-Mixed, More-Monocentric Development, (2) Less-Intense, Most-Compact, Less-Mixed, Less-Monocentric Development, (3) Least-Intense, Less-Compact, Most-Mixed, Most-Monocentric Development, (4) More-Intense, More-Compact, More-Mixed, Polycentric Development. Bivariate statistics demonstrated that geographic, historic, economic, demographic, and transport variables differentiate land use pattern types. Based on their multidimensional distinctions, we label the four types of metropolitan areas: Ascendants, Insulars, Redevelopers, and Cosmopolitans.

Keywords:

• metropolitan areas
• sprawl
• land use
• cluster analysis
• urban morphology

Notes

^1. See Grigg (1965) for a thorough discussion of classification schemes for regional geographic systems.

^2. Cluster analysis has become a commonly employed tool by geographers; for a recent illustration applied to the issue of neighborhood typologies, see the 2011 Special Issue of Urban Geography (vol. 32, 3). For an application to the delineation of distinctive sorts of suburbs in the United States, see Mikelbank (2004).

^3. We employ epochs delineated by Borchert (1967): pre-auto/steam and auto/electricity separated by 1920. Unfortunately, we had too few observations to subdivide the pre-auto era further, as did Borchert. Given the rise of limited-access, high-speed superhighways in metro areas just as Borchert was writing, we thought it appropriate to add an additional epoch beginning in 1970 to denote the latest transportation technology period that undoubtedly shaped land use patterns.

^4. Availability of rail transit as of 2000 from APTA (2012); railway miles (all types) calculated within ArcGIS using data from ESRI; total passenger enplanements calculated using data from the United States Federal Aviation Administration, available at http://www.faa.gov/airports/planning_capacity/passenger_allcargo_stats/passenger/; data on economic orientation and global connectivities from P.J. Taylor, Global Network Service Connectivities for 315 Cities in 2000, Data Set 12 of the Globalization and World Cities Research Network, available at http://www.lboro.ac.uk/gawc/datasets/da12.html, using the method reported in Taylor, 2001.