Mapping NYC Subway Ridership Through the Pandemic
Using aggregated turnstile usage data from Qri, the NYC Subway Ridership tool helps us visualize where transit usage has been impacted the most during the COVID-19 pandemic
A lot has happened in New York City since the start of the COVID-19 pandemic in March: Broadway went dark, schools closed, a statewide stay-at-home order was signed, the subway stopped operating overnight for the first time, an unrelated weeklong curfew was imposed, and now the city is beginning to open back up with Phase One. All these events have affected the ways New Yorkers live our lives, and how we move around.
The MTA has been publishing day-by-day systemwide ridership numbers for their subway and bus systems to show how their ridership has been impacted by the pandemic. But as Ben Wellington of I Quant NY pointed out when he published a visualization of subway ridership plummeting back in March, these changes in ridership were not evenly distributed. Subway stations further away from Manhattan experience smaller decreases in ridership numbers, due in part to many essential workers calling these less affluent neighborhoods home.
As the city slowly opens back up and social distancing is still in effect, it’s useful to know where ridership is growing back up again. In addition to day-by-day systemwide ridership numbers, the MTA also publishes a more granular form of ridership data in the form of turnstile counts. However, the format of this data is not for the faint of heart, as the raw data shows readings from each turnstile on a 4-hour interval. Fortunately, Chris Whong of Qri has been working on cleaning it up into a much more usable dataset by aggregating counts from individual turnstiles into total number of entries and exits per station per day. Chris explains in detail how he does this in his blog post.
NYC Subway Ridership tool
Using the dataset from Qri, I created the NYC Subway Ridership app. My goal was to create a tool that will be regularly updated, so we can observe how ridership will continue to grow as the city opens back up, as well as past trends on a per-station basis. There are two main metrics in this app: passenger counts and relative percentage change of passengers. The former gives us a sense of which stations are now the busiest in the COVID world, while the relative percentage changes tell us how less crowded each station is from the pre-COVID world as well as how much ridership has returned.
Some Observations
The ten busiest subway stations historically have all been in Manhattan, but that’s no longer the case now. Three stations in Queens (Jackson Heights, Flushing, Jamaica) are now amongst the ten busiest. The even bigger decrease in use of commuter rail is also apparent: the two subway stations connecting Long Island Rail Road at Penn Station are no longer in the top ten and the station serving Metro-North riders at Grand Central Terminal now has just above half the ridership as Times Square, when it used to be the second busiest station in the system.
Just like how the initial impact of transit usage has not been uniform systemwide, the recovery of ridership has not been evenly distributed either. Stations in Midtown and Lower Manhattan business districts have seen tremendous ridership growth, while stations that stayed busier during the initial stage of the pandemic has seen less growth. Stations in affluent neighborhoods have seen slower return of transit usage, despite having some of the biggest drops in ridership at the beginning of the pandemic.
The turnstile data also includes entry/exit counts for Staten Island Railway, Roosevelt Island Tramway, PATH and AirTrain JFK (I guess since they all use MetroCard as well). The line graph for the AirTrain was particularly interesting to me, because the AirTrain demand patterns don’t follow the typical weekday peaks of other train systems, and on top of that the system has suffered even more of ridership drop than the subway.
What are some findings that you found?
NYC Subway Ridership tool is an open-source project that to help us visualize how people are using the New York City subway system. Contributions are welcome on GitHub. Feedback can be directed to @_blahblahblah on Twitter.
