I’m able to get the latest American Community Survey data from 2014 down to a granular level for the first time so I’ve been playing around with it a bit. Since I made the graphics I figured I might as well post some of them.
For whatever reason, I ended up playing around with Boston.
Above is just a simple aerial to establish context with an overlay of the rail network.
This graphic is a mashup over various commuting patterns, and which census tracts commute most by car (purple), transit (aqua), foot (blue), and bike (celery? chartreuse? pear? light green.)
An interesting pattern emerges where you have blue nodes around the city. When looking closer these areas are the historic core/downtown, Back Bay/Fenway/Medical District, and the other three are the three major universities (MIT, Harvard, and BC). I’ll get back to these walkable nodes when I get into density.
Above are the rail transit lines simplified into simple corridors. What is pretty clear is that the aqua tracts (where transit usage is the highest form of commuting) correlates strongly with these rail lines, however these tend not to be in the core job areas, but the immediate surrounding areas such as Somerville, East Boston, and corridors of southern sector that I don’t know very well. One interesting contrast is Malden (high transit core) compared to Everett (no transit). I’ll get back to that.
Transit requires certain densities within about a half- to one-mile radius. I set the color codes to these varying pre-requisites. There’s a very light colored peach which is below the minimum threshold. The next lightest orange is roughly the absolute minimum for transit to function. The darker orange is more of an ideal. Brown is what I’ll call ‘peak density’ where the benefits of density are great without beginning to have some negative effects (design considerations excluded) as the benefits of density exist on an S-curve where they really rise between 20-40. If you’re being a stickler for numbers, call the categories 10, 20, and 40 units to the acre.
What’s interesting, if we go back to the commuting map (shown again below), the high walking areas are almost donut holes from a density perspective. Meaning their surroundings have a higher residential density. Because we know these are high employment areas (CBD, Med Center, Universities), they are still high density, but moreso from a destination standpoint than origins. Those that do live there (since residential can get crowded out by office/commercial, etc.) have a higher propensity to walk due to proximity. It’s probably a good assumption that the levels of connectivity are high between the residential density ‘envelope’ and the job centers. Meaning, probably not too many highway swaths between the two.
If we go back to transit, we’ll notice that all of the high transit ridership areas correlate with high density and the availability of a rail line. When looking at it from a density standpoint rather than ridership, there is one outlier.
If you scroll back up to the density map and look for brown clusters you’ll see Everett fits the bill for transit, but it doesn’t have a line. It’s the only place on the map that has high density, high car commuting. On the other hand, Malden with a similar density cluster rides the train line that it has.
The other strange outlier we haven’t discussed is the singular green tract where biking beats out all other commuting patterns. This happens to be Mission Hill, which I happen to know little more about than what I can play around with on Google Earth. However, twitter mentioned that a multi-modal bike path runs parallel to the orange line perhaps causing this spike in bicycling in this one part of the city.
I wonder if I can find anywhere else in the country where bicycling is THE primary mode of commuting for an area.
If for no other reason I decided to include a wealth map with a breakdown of working poor (under 40K household median), middle class, upper class, and wealthy (brown). The wealthy areas were cut off this map as they all exist west of Watertown.
