Illustration by Julia Harrison

A [big, beautiful] Tree Grows in Brooklyn [if you’re wealthy]

Measure a neighborhood not by its per-capita income or violent crime rate, but by the width and health of its trees.

I was fortunate enough to grow up in Park Slope, Brooklyn, a neighborhood so conducive to child-rearing that most of the local humor revolves around expensive strollers, organic produce or other trappings of an overachieving parent. In retrospect, excursions to other parts of the borough — along Flatbush Avenue for a Saturday doubleheader, into the downtown business district for yearly math competitions, or way out to old-school Bay Ridge to see my girlfriend — probably had outsized value as recesses from the wealth and whiteness of Park Slope.

Most middle schoolers aren’t familiar with per-capita incomes, violent crime incidence, infectious disease rates or other metrics used to evaluate a neighborhood. But you find other ways to figure out if you’re on the right side of town. Clean sidewalks, quiet nights, and cordial doormen are signs of a good neighborhood; barking dogs, barbed wire, and broken bottles are not. And trees: it always seemed like the blocks in nice neighborhoods were veritable arboretums during spring blossom.

We can turn that hunch into a hypothesis thanks to efforts by the New York City Department of Parks & Recreation, which conducts a census of all the trees in New York City every few years. The 2015 Tree Census contains records on the location, size, species, and health of over 680,000 of the city’s trees and is publicly available on NYC Open Data. Meanwhile, population and median household income figures for all 37 Brooklyn zip codes can be found on a site called Zip Atlas.

With the help of a few packages in R, we can retrieve both of these datasets from their respective sources:

One of the available tree variables is tree_dbh or the “diameter at breast height,” a common method for expressing a tree’s width. According to the census’ data dictionary, it’s measured (in inches) by taking the circumference of the tree about four feet from the ground and dividing by pi.

We can group the trees by zip code, take the average diameter, and then compare against our other chart’s economic data (and throw in trees per capita since we have population numbers too) to see if there’s a relationship between neighborhoods’ wealth and the thickness of their trees:

The results are far from perfectly correlated, but there’s a clear trend in the above scatterplot: neighborhoods with higher median incomes have wider trees. In zip codes with expected household incomes around $20,000, the mean tree diameter dips as low as only seven or eight inches, while almost any zip code with median household income over $40,000 has an average tree diameter of at least ten inches and as many as fifteen.

Trees widen as they age, so those in wealthier neighborhoods might simply be older than their peers, but they also could be members of larger, more magnificent species — brawny maples pushing up concrete next to Cobble Hill brownstones or towering oaks along the perimeter of Prospect Park.

And the trees are thicker in more ways than one in wealthier neighborhoods. As is demonstrated via the size of the green points above, there are about ten people to a tree in wealthy zip codes, while poorer zip codes have closer to twenty or twenty-five per tree.

As a final exercise, let’s focus on our data’s economic extremes. The wealthiest five zip codes are 11201, 11215, 11217, 11231, and 11234 which cover, roughly, Brooklyn Heights, Park Slope, Boerum Hill, Carroll Gardens, and Mill Basin. The poorest five zip codes are 11239, 11206, 11212, 11224, and 11221 which cover, roughly, East New York, Bedford-Stuyvesant, Brownsville, West Brighton, and Bushwick.

Here is a satellite map of Brooklyn with tree coordinates overlaid in blue for the wealthy neighborhoods and in red for the poor ones. Even in this simple visualization, the relative abundance of blue trees is apparent.

Now that we’ve reduced our dataset into two kinds of neighborhood and their accompanying trees, we can cross-examine some of the other variables. In particular, we’re given information on every tree’s species, whether it is alive or dead, and, strangely enough, if shoes have been tossed into the branches, an act that’s been associated with high school bullies and gang members alike.

What we find is that cherry trees, a species whose blossom is so beautiful that online instructions on where to find them materialize every spring, are found much more frequently in wealthy neighborhoods (1,136 versus 356), while poor neighborhoods, despite having fewer overall trees, still have more dead ones (452 to 406) and more with sneakers hanging from the branches (29 to 17).

So in summary, if you find yourself walking through an affluent Brooklyn neighborhood, you’re not only likely to enjoy more trees, but they will be bigger, healthier, and prettier.

Teasing cause from effect in this matter is unlikely, as most measurements of a neighborhood have somewhat of a cyclical or self-reinforcing quality. In our case, trees might attract a certain high-earning cohort to a neighborhood, but they might also benefit from having those people — and their time and resources — around once they’ve actually moved in.

This exercise was about more than creating additional ways to quantify the inequity among Brooklyn’s neighborhoods, though. It was about finding a middle ground between a statistical understanding of a city and an experiential one, which are generally taken as mutually exclusive. It’s a natural tendency to split knowledge into things you can learn versus things you can feel, information or impulse. Sometimes though, with the help of Parks and Rec volunteers and some statistical software, you can have it both ways.