I've been working on generalizing my code so that I can make comparisons for dozens (or hundreds) of cities. And of course, I've found a ton of bugs, mostly related to my own poor understanding of Python data structures and functions. But I also found a fundamental issue with the calculations I used in my thesis.

Distance thresholds

After looking at the job connectivity maps, I was curious to explore the idea that densities above a certain level led to walking more than cycling. I don't have enough data to make a definitive statement, but I did find an interesting phenomenon related to connectivity in Columbus. Columbus has three disconnected zones where jobs are very close, broken up by areas of low job access.

Image depicting river systems with three different drainage densities (fine, medium, and coarse)

Intersection density

OSMnx makes it easy to generate statistics on street networks. Again these aggregated stats show very strong correlations, especially between bike mode share and intersection density. One of the problems of cycling advocacy is that there's often not much that can be done to change this indigenous condition.

Density = destiny?

One striking result from the target area analysis is the correlation between residential density and cycling rates in the target area. For these four data points, the correlation between density and bicycle mode share is dramatic (r=0.97), which seems to speak to the importance of indigenous conditions in people's mode choices. Unfortunately, the effect disappears when examined at the census tract level.

Maps of network connectivity to jobs

One of the factors I'm trying to measure in valuing facilities is their usefulness; do they actually go where utility cyclists want to ride? One of the factors I used was access to jobs within 1.5 miles along the cycling network. These maps really visualize the differences in density of the street networks.

Maps of commute biking and value-added facilities

Combining my concepts of target area and value-added facilities, I developed maps for each city which select the circle of census tracts near the central city which have the great number of commute cyclists. One thing that's visibly notable is the relatively weak connection of value-added facilities to cycling rates; only in Columbus are they well-connected. Part of what I conclude is that cultural factors and the indigenous qualities of the street network are more important than value-added facilities in cycling mode choice. The methodology is potentially interesting for other kinds of analysis; you could easily optimize for any other census data.


I've been too busy with thesis work to post any updates here, but now it's actually done! And I'll have some time to start sharing bits of it. The most common reaction I've gotten from bike-identified people I've shared the work with is, "that's interesting, I haven't thought about it that way before," which I will accept as an indication that the project has been successful.

Bike mode share, facilities, and crashes within 4-mile radius circle in central Austin (1:100,000)

Target area data analysis

One problem I noticed while doing field research is that the city extents vary greatly; Austin, for example, has over six times Minneapolis' land area, which means that Austin includes some sprawling, low-density areas with low cycling rates that are excluded from Minneapolis' mode share numbers. I looked at creating a 4-mile radius circle to encompass the highest-cycling area of each city (by ACS mode share data), to be able to develop more comparable metrics from city to city. There are still a lot of issues with the data, but at least I'll be comparing rotten apples to rotten apples.

Roads vs. streets

Urbanists like to distinguish streets from roads. The somewhat distasteful neo-liberal conception is that roads exist to connect productive places, and streets exist as a platform for building wealth. A similar dichotomy exists with bike infrastructure; bike roads get us from place to place efficiently, and bike streets are interesting places to be.

Scioto River Valley

Columbus is the host of the Tour of the Scioto River Valley (TOSRV), one of America's longest-standing large group rides. TOSRV makes the claim, with some credibility, that its popularity led to the original U.S. bike boom back in the 1970s. So, social riding is part of the culture around Columbus, and I was able to hook up with the regular Tuesday night social ride. The leader of the ride, Ray George, is one of the founders of Yay Bikes!, and he was more than happy to talk about the organization.

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