For my first assignment for CY255 I created a map of my hometown using data from the city’s open data platform. Burlington is a small city, but it has been making a sustained effort to become more data-centric, and the availability of this dataset is one result. The data itself was relatively easy to work with, although adjustments had to be made to fit the requirements of Carto. The first two maps used a dataset of property parcels. I found this dataset interesting because it contained both the structure of the city, and by including the year the parcels were developed, it also contained some history. The last map shows the number of rental units across the city, which was located in a separate dataset from the city.
My first map plots the development of Burlington over the past two hundred years. The properties on the map light up as they are built and then fade away, showing the patterns of growth across the city. Construction is contained in the center city at first, and then works its way outward. By the suburban era of the late 40’s and 50’s a building boom occurs in what is still referred to as the New North End.
The second map zooms in on a neighborhood I used to live in, the Old North End. The animation reveals the story of the neighborhood. If you are familiar with the area, you can see how the city was formed around a few landmark buildings. Like any work of history, this map invites you to speculate on what life was like in a past era when the city consisted of only a few buildings. For this map I made two layers – one with static center points in each parcel, the other with a torque that cumulatively filled in the city.
The two different visualizations show two different ideas of city development. The first is active, showing a city churning and creating. The second illustrates a city that slowly creeps outward to cover everything. The design choices in the color and speed of animation reinforce the perception these maps could make on an audience.
The final map uses a separate dataset to map where rental housing is located. This map shows that most of the housing that is available to renters is concentrated in the downtown area, especially the areas known for housing University students. As we know from the other maps, this area is also one of the oldest parts of the city. If you mouse over the properties on this map you can see that there are very few parcels with many more than 5 units. For this map I made altered the appearance of the larger properties both by adjusting the color and making them more opaque that the smaller properties, so they could be seen more clearly. I did struggle with the scaling of this map, and it works best if it is zoomed in to focus on a neighborhood at a time.
There are a number of caveats with these maps. First, the data is not perfect. Likely too many parcels have been coded as being built in 1900, as both of the historical maps show a significant jump over that year. My best guess is that 1900 was a default date chosen for old buildings, though it is possible there was a building boom during that time in the city. There were also a number of parcels that did not have a build date. Finally, the data is not a complete history of the city, since it only has current buildings on current parcels. A more thorough historical database might also have buildings that were constructed and then demolished. The other issue I had was with Carto. I was hoping to incorporate these maps together, using both a cumulative and non cumulative torque to show how the city was building and filling in on one map, but this was not supported by the site.
I chose to work with Burlington for this project because I knew exactly where to get the data and who to talk to about it. However, as I look forward to my final project I’d like to find a similar dataset for Berkeley or a wider part of the Bay Area. Housing is an extremely pertinent issue for everyone who lives here. Even those who are well off by any comparable standard to the rest of the country find they pay too much of their income on housing and are unable to buy a home. Although the housing crisis has deep and complicated roots, the slow growth of building is one cause. By mapping where housing is being built, we can see where it isn’t. Towards this end, I’d also like to find a way to understand the vacant housing in Berkeley, where it is and why it’s there.