Abstract
This paper compares neighborhoods with more traditional features in two very different cities. As expected, in Portland the majority are socially diverse and in Atlanta they are low‐income. However, in both cities about a quarter are high‐income. In Atlanta the latter are located in older neighborhoods, whereas in Portland they are also in areas combining newer and older housing. A return to valuing a more traditional urbanism may explain the signs of revitalized central cities in both places. Our findings, however, indicate it may be accompanied by the relocation of low‐income neighborhoods to areas where activities are not readily accessible.
Acknowledgements
The authors wish to extend their thanks to Emily Talen for her helpful comments on an earlier draft of the paper, and to the anonymous reviewers for their thought‐provoking questions and suggestions. They also wish to acknowledge Asal Mohamadi for her assistance with the data analysis. Atlanta data were made available through the SMARTRAQ research program (http://www.act-trans.ubc.ca/smartraq) whose funders included the Georgia Department of Transportation and the Georgia Regional Transportation Authority.
Notes
1. Portland is known for its urban growth boundary (UGB). First established in 1979 and expanded little since then, the boundary encompasses 24 cities, parts of three counties, and approximately 1.3 million people. Under the requirements of Oregon’s land use statutes, all land outside the UGB – with exceptions – is designated for resource use and prohibited from urban development.
All land both inside and outside the UGB must be planned by the appropriate city or county. Zoning must correspond with plans. Portland is also known for its light‐rail transit system, established on the east side of the metropolitan area in 1986. The westside extension was placed in operation in 1998. To increase ridership and accommodate growth within the UGB, a number of policies were adopted to facilitate transit‐oriented development, including transit area overlay zones with minimum density requirements and several public/private partnerships established to encourage high‐density housing and employment growth around station areas.
2. Income categories are as below:
under 20,000
20,000–39,999
40,000–74,999
75,000 or more
3. We also created an Entropy Index following Galster and Booza (Citation2007). The analyses were carried out using both measures of social diversity. The Simpson index systematically classified between 5% and 11% more neighborhoods as socially diverse than the Entropy index, but the story they tell comparing the two cities is the same. For the sake of simplicity in presentation, we have reported only the findings based on the Simpson index. It is easier to interpret conceptually and has been used to assess the diversity of housing types criterion incorporated into the 2009 version of the LEED‐ND Rating System (http://www.cnu.org/leednd).
4. K‐means clustering is used here. K‐means clustering begins with a grouping of observations into a predefined number of clusters. It evaluates each observation and moves it into its nearest cluster. The nearest cluster is the one which has the smallest Euclidean distance between the observation and the centroid of the cluster. When a cluster changes by losing or gaining an observation, the cluster centroid is recalculated. In the end, all observations are in their nearest cluster. Due to space constraint, we do not present centroid values here. For more descriptions of the cluster analysis, see Song and Knaap (Citation2007), Miles and Song (Citation2009) and Wilson and Song (Citation2009).