Research and discussion for citizens and decision makers

Commuter pattern mapping software released

Uses CTTP 2000 data

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Harry Kao, a software engineer from the San Francisco area, released an online mapping tool for commuting patterns (via Human Transit).  It uses the Census Transportation Planning Package (CTTP 2000), so the data is already ten years old and employs organization by census tract.  The newer census tool, the American Community Survey (ACS) annually updates its estimates, but Kao says he needed “fine-grained” commuting data from the CTTP. 

Jarrett Walker issues a few caveats about this tool:

The visual representation encodes a dreadful bias, though:  It assigns these commutes graphically to the road network, as though everyone travels by car!  In so doing, it appears to give evidence that San Francisco needs an Embarcadero Freeway!

Be careful with maps!  Good maps are designed to tell a story.  But automated mapping tools such as this one can make maps that are incredibly detailed, scientific-looking, and utterly misleading.  This happened often enough when authors of maps actually looked at their own maps. But with automated mapping we face a world in which “authors” of an automated mapping scheme never even see the map they produced—until it shows up in somebody else’s argument.

Of course, Walker’s objection that this tool doesn’t distinguish a transit trip from a driving trip might not pose a problem for Houston, where we do a lot of driving.  This could be a measure of our roadway bottlenecks, at least, based on the old data.  The application converts the data from census tracts to zip codes, and the red circles are located at zip code centers.  The blue lines are thicker where there is more commuting to the destination zip code.  I captured a map representing commutes into zip code 77056, which includes the Uptown area.  Notice the colon-shaped, blue line created by I-610, Post Oak Boulevard, and Westheimer.  Near I-610, the blue line representing US 290 is a fatter than the one for I-10. 

(Image source: Harry Kao)

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