Block #6: Williamsburg
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With this week’s BONY turning to a hipster haven, we wanted to point out that we’ve been analyzing pedestrian traffic using computer vision since before it was cool. In all seriousness, this Brooklyn sensor revealed interesting features particular to its neighborhood.
The dataset we’re looking at comes from Bedford Avenue between N. 10th Street and N. 11th.
The block rivals our Block #3 in SoHo and Block #4 in Downtown Brooklyn, covered previously for the title of “quietest block profiled.” It also has the back and forth commuter patterns visible in our Block #1 in Midtown, and sleeps in on weekends like Block #2 on the Upper East Side. As before, we saw a winter storm take a bite out of pedestrian traffic, although not to the same extent as “Snowmageddon.”
Tree-lined and residential, this short block of Brooklyn’s longest street takes only a minute to walk end to end. In that short distance, you can find waffles on a stick,* an alehouse with a daily-updated beer menu, multiple brunch spots, and “a rustic schoolhouse-styled bar in a converted garage.” Amazing.
* Editor’s note: while not making an official endorsement, at least one BONY team member has vouched for the organic frozen yogurt and waffles at Von Dolhens.
Now that we have a feel for the area, let’s dive into the foot traffic data from a nine-day period starting in late February.
The first thing we noticed was very different behavior on weekdays vs. the weekend. Williamsburg has been resoundingly residential for more than a century, ever since the Williamsburg Bridge opened up access to Manhattan’s Lower East Side back in 1903. By 1917, Williamsburg held the most densely populated blocks in America’s most densely populated city, and the neighborhood served as a refuge for Hasidic Jews in the years leading up to World War 2.
Williamsburg no longer has the densely packed tenements of the nineteenth and twentieth centuries, and many of the factories, remnants of the area’s industrial past, have been converted into stylish residential lofts.
During the week, many commuters travel back and forth between their homes in Williamsburg and their jobs in Manhattan, visible in our data as the weekday morning and evening rush hours. A small spike around 6:00 AM indicates to us that some workers still have to go in on the weekends (or is it due to late night dancers coming back from Good Room, just North of McCarren Park in Greenpoint?).
Commuter tides
Our block lies just a few streets north of the Bedford subway station, one stop from Manhattan on the L train. When we subdivided the data by direction, the weekday commuter pattern became even more clear with a swell of southbound morning traffic and corresponding northbound evening traffic.
Weekend getaway
Williamsburg has been residential for a long time, but the neighborhood is also in the middle (at the end?) of a demographic shift. After deteriorating in the 1960s, it began to bounce back in the 1990s as artists and musicians were squeezed from SoHo and the East Village. In recent years, gentrification has started to push the hipster crowd further into Brooklyn as more and more yuppies balk at Manhattan rent, completely transforming the neighborhood.
One result of this shift is that Williamsburg has become over the years a popular spot for weekend escapades with numerous brunch options, flea markets, and attractive parks. This behavior leads to large spikes in traffic around 2:00 PM and 6:00 PM on Saturday, although traffic drops precipitously on Sunday evening.
Traffic patterns for Saturday were particularly interesting as the commuter tide of the week was reversed around midday and the early evening. The popularity of weekend brunch in the area and New York’s prohibition of drinking before noon on Sundays might explain the increased activity on Saturday relative to Sunday.
While Sunday evening might be expected to be quieter than Saturday, this particular Sunday had the biggest snow day in our dataset, quieting much of New York later in the day. The large downward spike around 4:00 PM turned out to be the sun hitting the dusty window in front of this particular sensor, problem solved by cleaning it.
There’s always more insight to be uncovered in this sort of dataset, and we hope that this post has gotten you thinking about questions that these data could help you answer. For example, one member of the BONY team has taken the (very) data-driven decision to come to work at 10:30 AM instead of 9:00 to avoid the crazy L train 8:00–9:00 AM morning rush — nothing to do with beauty sleep of course. On the contrary, Van Dolhens could decide to open earlier in the morning to capture more customers grabbing an organic frozen yogurt on their way to work!
As always, if you have any comments, please write a response below and feel free to reach out to us.
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The BONY Team
Download the dataset here (CSV)
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