Posted by Evan Herrnstadt on April 18, 2008
The Center for Neighborhood Technology, in conjunction with the Brookings Urban Markets Initiative, has created an interactive map that displays the spatial distribution of affordable housing in 52 U.S. metropolitan areas. The two basic layers overlay either the traditional measure of affordability (rent 0-30% of area median income) or the project’s Housing + Transportation Index. The HTI (explained in some detail here) incorporates modelled transportation costs into the definition, such that the range of affordability becomes 0-48% of area median income.
Here are two maps centered on Columbia Heights, Petworth, Mt. Pleasant, and Shaw in DC, four neighborhoods that are often described as recently gentrified/gentrifying.
In the first map, blue designates unaffordable areas as defined by the 0-30% housing guideline. When we factor in transportation in the second map, little changes except that a small portion of Mt. Pleasant just left of center becomes affordable by this 0-48% definition (probably due to DC’s relatively comprehensive and cheap public transit system).
There are numerous advanced layers that provide a more finely-discretized representation of the above variables — one can also restrict the data to renters or homeowners. There are also layers for the component variables, such as average neighborhood income, average monthly rent (shown below), transit connectivity index, and so on.
Not only are these great for planners and policy wonks, but also for the DC citizenry. When I was new to DC and looking for a place with only craigslist to guide me, such graphics could have efficiently guided my search.
These maps also provide a valuable snapshot of gentrification and urban development. However, from what I can gather, the area median income is determined at the census block group level. Thus, it does provide an idea of how affordable housing is to the current residents of the neighborhood without allowing wealthy suburbs (e.g. Potomac, MD) to determine the affordability of poorer areas (SE DC). However, since it is only a snapshot, it suffers from massive selection problems. Obviously, people currently living in an area are more likely than not to be able to afford living there, at least to some extent. A big issue that often arises with regard to gentrification and urban development is that people are supposedly priced out of their homes. This static representation does not help determine whether this is happening. Hopefully, the project will continue and be able to trace trends in the future, because I think it’s a fascinating tool with amazing potential.