Module 5: Choropleth Mapping

     In this weeks lab, I designed a map of Europe that communicated both wine consumption (liters per capita) and population density (population/sq km). To generate such a map, I used choropleth and symbol mapping in ArcGIS Pro. Making a map like this may not sound very difficult at first but there is a fair amount of detail that goes into it. 

    First, I had to decide how I wanted to present the data. Did I want to use graduated symbols or proportional symbols? Ultimately, I decided to use graduated symbols to display both the population density and the wine consumption. For the population density, I used natural break classification and green color ramp displayed as the countries shape. For the wine consumption, I also used a natural break classification method as well, but I used graduated point symbols to present the data. The larger the point symbol the larger the wine consumption in the country. I elected to make the point symbols partially transparent so you could still determine the population density of the country below the symbol. Then, I chose to exclude a few outliers in the data set, so that they would not skew the classes or clutter the map. 

    I found that the labels were a bit more challenging for this map since some countries are quite close together. Due to the close proximity of some countries, I converted the labels to annotations and moved some of the labels to open spaces on the map to help with clarity. I also used callouts to make sure the reader could identify what country the labels belonged to. After I had the labels placed appropriately, I was able to add a few more details to the map (i.e. labels for water bodies) to help the map reader orientate.

    While I am happy with the map, I do wonder if there are better ways to present the data. Perhaps I could have used a different symbol to show wine consumption that related more to wine than a dot. I could have used and image of a wine bottle and increased the number of bottles to communicate an increase in wine consumption. There is also a technique called bivariate analysis which is designed to communicate the relationship of two variables. This may have been a better approach if comparing the relationship of population density and wine consumption was the focal point of the map. With the techniques that I used, those variables are presented separately. 

Stay tuned for next week's lab that focuses on isarithmic mapping!