Urban Heat Islands

Yesterday was the first day of 32º+C (90º+F) in Philadelphia in October in 78 years. Gross. But it made me remember this piece last month from NPR that looked at the correlation between extreme urban heat islands and areas of urban poverty. In addition to the narrative—well worth the read—the piece makes use of choropleths for various US cities to explore said relationship.

My neighbourhood's not bad, but thankfully I live next to a park.
My neighbourhood’s not bad, but thankfully I live next to a park.

As graphics go, these are effective. I don’t love the pure gradient from minimum to maximum, however, my bigger point is about the use of the choropleth compared to perhaps a scatter plot. In these graphics that are trying to show a correlation between impoverished districts and extreme heat, I wonder if a more technical scatterplot showing correlation would be effective.

Another approach could be to map the actual strength of the correlation. What if the designers had created a metric or value to capture the average relationship between income and heat. In that case, each neighbourhood could be mapped as how far above or below that value they are. Because here, the user is forced to mentally transpose the one map atop the other, which is not easy.

For those of you from Chicago, that city is rated as weak or no correlation to the moderately correlated Philadelphia.

I lived near the lake for eight years, and that does a great deal for mitigating temperature extremes.
I lived near the lake for eight years, and that does a great deal for mitigating temperature extremes.

Granted, that kind of scatterplot probably requires more explanation, and the user cannot quickly find their local neighbourhood, but the graphics could show the correlation more clearly that way.

Finally, it goes almost without saying that I do not love the red/green colour palette. I would have preferred a more colour-blind friendly red/blue or green/purple. Ultimately though, a clearer top label would obviate the need for any colour differentiation at all. The same colour could be used for each metric since they never directly interact.

Overall this is a strong piece and speaks to an important topic. But the graphics could be a wee bit more effective with just a few tweaks.

Credit for the piece goes to Meg Anderson and Sean McMinn.

Author: Brendan Barry

I am a graphic designer who focuses on information design. My day job? I am the data visualisation manager for the Federal Reserve Bank of Philadelphia. (This blog is my something I do on my own time and does not represent the views of the Fed, blah blah blah legal stuff.) And with my main interest in information design—be it in the shape of clear charts, maps, diagrams, or wayfinding systems—I am fortunate that my day job focuses on data visualisation. Outside of work, I try to stay busy with personal design work. Away from the world of design, I enjoy cooking and reading and am interested in various subjects from history and geography to politics to science to the arts. And I allow all of them to influence my work.

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