How Accessible are NYC Parks?


Visualization

Intro

New York City has an extensive subway system that connects its residents to various areas of around the many boroughs and neighborhoods. Unique to each borough in New York City, the parks provide necessary outdoor and recreational spaces for all in the city to enjoy and use. Around 29% of NYC stations are ADA accessible, but accessible stations are near the city’s parks? For this lab, I was interested in how accessible and by which trains can parks be easily reached?

Inspiration

For my visualization I was inspired in general by the various geographic visualizations that have been produced since the wake of Coronavirus. Since my datasets includes transit information, an additional source of influence is the MTA route map since the subject of my visualization is New York City. I found this example, which shows the the MTA map with it’s accessible stations, so I thought I would create my take on this visualization.

Materials

Tableau Public Sheet Example

The main software I used to create my map was Tableau Public, which is a free and powerful information visualization software. Additionally to source my data I used data.ny.gov to find information about the accessible stations in the form of a CSV file. And for the spatial data in my visualization, the parks and train lines, I used the NYC Open Data site, which provided me with ShapeFiles.

My exact data sets can be found below:

Methodology

After downloading all of my data, the first part is uploading all of the files into Tableau Public. I uploaded the two ShapeFiles as Spatial files and the CSV file as a Text file. I started with Joining the two spatial files so that all the Geometric data can be compiled. I made sure to make the two files intersect with Full Outer join based on the Geometry field of both ShapeFiles. To add the CSV, I made sure to set the Route1 field equal (=) to the train field in the Train Lines field. This brought all three graphs into Tableau. Now was time to set up the map.

First I dragged the geometry field from one of my spatial datasets to generate the proper map, and then dragged the other geometry field and added it as a layer on the same sheet. Next, since my Train Stations CSV file had longitude and latitude, I was able to drag the latitude field as a third layer on the same sheet. Now that all the data is present. The last step is deciding on color and organization aspect. I wanted to keep the already existent color system set up by the MTA for the train lines, and for similar consistency reasons, the parks were made green. Lastly, ADA accessible stations were made pink and non accessible stations blue (also I made it so that the non accessible stations were filtered out on first arrival to my Tableau project). Additionally, on the map, I highlighted a few parks and added how many accessible stations were immediately surrounding each park.

Lastly, I created a bar graph to display the scale at which most stations are non accessible overall, and how much work needs to be done to provide access to all. My Dashboard just combined both the map and bar graph to show affects side by side.

Results

I didn’t really think about how inaccessible most parks are via the subway for differently abled individuals before creating the visualization. Since, I mostly commute around manhattan on the red line I somewhat knew there were a decent amount of ADA accessible stations up and along Central Park which skewed my perception of this problem. I also had no idea, New York City had over 1800 parks! I’ve barely been to a handful, so that was pretty surprising to me as well. One other thing to note is that this only features the subway lines, but I do know that buses provide access to a lot more specific areas and routes which should also be assessed to make sure that more parks can be reached by all.

Reflection

I had a tough time with the set up for this lab at first. It was a bit confusing knowing all the steps you have to take to get two or more spatial files in the same data source, and adding the third file as a CSV also provided some challenges for me initially. For next steps, it would be cool to add a time aspect and see how this has changed over time / what is planned for the future and add that information to this viz.