Thu 27 May 2010
Intersection density is the number of intersections in an area. It corresponds closely to block size — the greater the intersection density, the smaller the blocks. Small blocks make a neighborhood walkable. This diagram shows three street layouts — extremely walkable, moderately walkable, and unwalkable — with their counts of intersections per square mile:
Intersection density makes surprising news in a study by the formidable academic duo of Reid Ewing and Robert Cervero. They have published Travel and the Built Environment: A Meta-Analysis in the Summer 2010 issue of the Journal of the American Planning Association.
As the title notes, the study is a meta-analysis: a study of 50 other studies about travel and the built environment. The authors look at the results from each of the 50 studies, and then pool all of those results into ten built environment measurements, including intersection density.
Their findings? Of all the built environment measurements, intersection density has the largest effect on walking — more than population density, distance to a store, distance to a transit stop, or jobs within one mile. Intersection density also has large effects on transit use and the amount of driving. The authors comment,
This is surprising, given the emphasis in the qualitative literature on density and diversity, and the relatively limited attention paid to design.
In other words, intersection density is the most important factor for walking and one of the most important factors for increasing transit use and reducing miles driven, but gets relatively little attention in research and in public policy.
The authors report their built environment measures in terms of elasticity. Elasticity can be defined this way: when a built environment measurement changes by a certain percentage, that will cause walking, transit use, or driving measurements to change by a certain percentage. The ratio between the two is the elasticity.
For example, in “Travel and the Built Environment,” the elasticity of intersection density was found to be 0.39 for walking. That means if intersection density is increased 10 percent, walking will increase 3.9 percent. If intersection density is doubled (100 percent increase), walking will increase 39 percent. It was the biggest elasticity found for walking, and also the biggest elasticity found in the entire meta-analysis.
Also surprising was the effect of 4-way intersections on transit use. The number of 4-way intersections in an area can represent the level of street connectivity. But a street layout may provide 4-way intersections along with extremely large, unwalkable blocks. In that case, it may be easier to bike or take a short drive to the transit stop. And in fact, the study did find that 4-way intersections were much more significant for transit use than for walking. The elasticity of 4-way intersections for transit use was 0.29, which was the biggest elasticity for transit use (in a tie with the “distance to the nearest transit stop” measurement).
The study contains many caveats. It is actually a brief primer on the pitfalls and potential disadvantages of meta-analysis. The authors warn that:
- The sample size (number of studies examined) is small, so the results are only ballpark estimates.
- Owing to the nature of the studies examined, the level of statistical confidence could not be calculated.
- Some of the examined studies account for self selection* and some do not; the meta-analysis combines them.
- Due to all of the above, users should use caution when applying specific elasticities.
* Self selection: Do walkable places cause people to walk, or do people who like to walk chose to live in walkable places? Most nonacademics assume that both are happening, if they bother to think about it at all. But it’s important to academics to pin down these kinds of things.
In addition, intersection density and number of 4-way intersections are not necessarily the most accurate or rigorous measures of walkability and street connectivity. These measurements do not account for intersections that lead to dead ends, bottlenecks in the street layout, or inaccessible gated areas. There are better measurements available, but the intersection density and number of 4-way intersections measurements are relatively easy to compute and can use free databases that have broad geographic coverage. They are favored by academic researchers for those reasons.
Nevertheless, this meta-analysis does a huge service by providing ballpark estimates of the effects of built environment on travel. The study provides a core database, a “seed,” that can be strengthened as more and better research is produced. And it reports surprising, preliminary results about the very large effects of intersection density and connectivity on increased walking, increased transit use, and reduced amount of driving.