Regional income distributions: spatial segregation by class
From their inception after the first agricultural revolution cities have always had “good areas” and “bad areas.” “Good areas” often provide an array of goods and services and offer aesthetically pleasing landscapes. The real estate markets have taught us that renters can charge more to live in “good areas,” which can perpetuate the income and tax base with which to keep these areas “good.” Today’s cities are increasingly geographically polarized by class and may continue to be so due to social, political and economic structures preventing inter-class interaction.
A series of interactive maps use Census data to spatially depict regional variations of household income and/or rents. Although the original link allows users to search for certain areas in the United States using States or specific addresses, other maps were created for specific urban centers, including Washington, DC. Geographic class-based clustering is evident in many cases. Some clusters are surrounded by gradually lower or higher income classes, but others are spatially proximate (in some cases bordering) populations with much larger differences on the SES scale. These later instances may suggest areas of current or near-future gentrification, or disinvestment and out-migration from previously “good” areas (perhaps the “vote with your feet” model).
The Google-based maps allow users to examine surrounding physical and human characteristics of the landscape, including national parks, mountain ranges, river, travel infrastructure, services and points of interest. Such landscapes may influence the SES and rent distributions in the regions. For example, the map of Washington, DC explicitly overlays the Metro station locations with rent data, showing certain train lines correspond to certain levels of economic development.
Aside from all the geographic, social, political and economic analysis these maps spur, they’re also just a great way to decide where to rent an apartment!
As a complement to the data provided through the income and rent maps, here you can find ESRI maps that show the spatial distribution of household income, unemployment and demographic information at the State level. The unemployment map shows the percent change in unemployment from 2009 – 2012, during Obama’s first administration.
