A couple weeks ago, blogger Tim De Chant posted an article pointing out the correlation between amount of tree cover in urban neighborhoods and income. It may seem like a no-brainer that wealthier neighborhoods boast larger trees and more overall, but it’s a tighter correlation than you may think. De Chant referenced a study that “found that for every 1 percent increase in per capita income, demand for forest cover increased by 1.76 percent. But when income dropped by the same amount, demand decreased by 1.26 percent.”
Apart from neighborhoods that are being blitzed with gentrification, tree cover ought to reveal a neighborhood’s per capita income with a fair amount of precision, given the right algorithm. (Don’t look at me; I’m not figuring it out.)
Anyway, De Chant reasoned that income inequality might be seen “from space.” He grabbed screenshots from Google Earth to compare tree cover in different neighborhoods within a city. The pictures are pretty interesting. He didn’t include Baltimore, so I went and grabbed a couple of my own images. I found the most stunning difference between planned neighborhood Guilford and nearby Waverly in North Baltimore.
Guilford – Median household income, 2009: $84,501
Waverly – median household income, 2009: $43,981
On the other hand, I didn’t find a noticeable difference between Mount Vernon and Greenmount West, despite the large income disparity.
Mt. Vernon – median household income, 2009: $28,480
Greenmount West – median household income, 2009: $18,090
What do you think? Is the “tree test” valid for Baltimore?
It seems like neighborhoods with larger tree canopies are also much lower density. In Baltimore and elsewhere, the average lot size should be compared along with the density of trees. Obviously, a half-acre lot in Guilford will have much larger area where trees can be planted than a 2,000 square-foot rowhouse lot. To really make this study meaningful, Guilford should be compared to Ashburton, Waverly to Berea, Mt. Vernon to Bolton Hill etc.
Absolutely. There are plenty of confounding factors. And on one level, saying “richer neighborhoods have more (and larger) trees” is liking saying “richer neighborhoods have larger houses.” Like, of course they do.
For me, what’s most intriguing about the whole idea is the implication that you could estimate the average income of a neighborhood at a glance from a satellite image. But you’re right, Guilford versus Waverly is fish in a barrel; they are different in every way. I’ll see if I can find a comparison that controls every physical characteristic except for tree cover, scanning around this morning, I couldn’t.
I think there is some truth to tree density correlating to income but it also has to do with population density. A place like Harbor East has few trees but lots of dollars. I can imagine a place like Manhattan would also not really correspond well to the tree density model of wealth. That being said we should still plant a lot more trees.