Greening Taipei: Fifty Years of Urban Transformation

Greening Taipei: Fifty Years of Urban Transformation

I lived in Taipei for a year from 2023-2024 and one of the first things I noticed was the urban greening across the city. Outside of the flat my partner and I lived in was a pocket park (photo attached), which can be found all across the city. I decided to design an exploratory visualisation to look at urban green spaces in Taipei City. I wanted to begin with a timeline as the starting point of the visual, shaped to mirror the Tamsui river, which runs through the city. I originally wanted to plot a choropleth map to visualise how the shape of urban green spaces have changed over the years but I could not find any open datasets which had both location and time variables. I have attached a photo of some of the notes I made while doing this visualisation.

I used Python for exploratory analysis and preliminary visuals, and then I refined the visuals in Adobe Illustrator. I downloaded open data from the Taipei Government website, which consisted of a time series dataframe with the area of green spaces in Taipei City between 1968 to 2025. To visualise a map of green space locations, I found data for this from 2023 in the Taipei Water and Green Space Atlas. I first had to translate all the data from Mandarin and I manually classified the green spaces so I could add a layer of information here and colour code the green spaces based on the type of green space. I spent a lot of time thinking about how to layer multiple pieces of information into this visual as Federica does in her final visualisation for this course. I unfortuantely could not find more complex open data or clear statisitics to add anything else to this visualisation and therefore had to keep it simple and exploratory. I have attached a screenshot of the GeoDataframe, which I used to plot the location of the recorded green spaces.

I played around with the design of this visualisation a lot, using Pinterest and Behance for visual inspiration. I settled on using a raster-like plot to illustrate the time series data, as I liked this aesthetic for the exploration of spatial-temporal dynamics. I overlaid the plots for each type of green space to convey the sense of an interconnected urban ecosystem. Other details include using a cube-helix colour palette for the map (colour-blind friendly) and using the red timeline as a continual aesthetic element to link the three visuals together. I kept the focus of visualisation on the generation of green spaces (to keep the visuals clear as the area of green space was the only time series dataframe I could source) and I decided not to illustrate other policies, such as tree planting or beautifying urban spaces, on the timeline.