Bivariate choropleth mapping

Continuing the work in Applied Cartography, this time about bivariate choropleth maps. Bivariate choropleth mapping is a cartographic technique that simultaneously represents two variables within a single map using a combination of colors. This can be important for visualizing the spatial relationship between the two variables, allowing for the identification of patterns, trends, or potential correlations. 

My task was to try this technique out by designing my own bivariate choropleth map of Sweden's 290 municipalities. I had to download two statistical variables that were both quantitative and continuous, but also related. For that, I chose to investigate the spatial relationship between gainfully employed individuals and car ownership (total cars in use) in each Swedish municipality. In addition to this, I needed population data for normalizing the datasets to avoid biases between the different-sized municipalities.

By mapping those variables, questions may arise, such as: 

These questions could be important in finding solutions to root problems regarding sustainable transportation developments in relation to socioeconomic status, which in this case I represented through gainful employment.

The resulting map shows the extent of Sweden as a whole and its municipalities as well as its neighboring countries. In the legends square, there’s an x-axis and a y-axis. The x-axis indicates the ratio of car ownership and the y-axis indicates the ratio of employment. Starting at the lower left, each corner of the square indicates the ratios of both variables. This can be low-low, low-high, high-low, or high-high.

There may be a multitude of reasons that could explain why, for example, certain municipalities with high car ownership have low employment. This could potentially be because of different industries residing in different municipalities, differences in age groups, as well as transportation options.