Week 5: Choropleth and Proportional Symbol Mapping

 

This week, I explored the relationship between wine consumption per capita and population density across European countries in 2012. The goal was to visually represent how these two variables are distributed and to choose effective mapping techniques to communicate the data. Using both choropleth and proportional symbol techniques, I created a combined map (Figure 1) that highlights these patterns across the continent.

Figure 1

Using ArcGIS Pro, I began by importing the provided EuroPopulation feature class. I used the quantile classification method to divide population density into five equal groups and applied a graduated blue color scheme, adjusting shades manually for better balance. To avoid skewing the data, I excluded outliers like Monaco and Gibraltar using SQL queries. Once the labels were added, I converted them into annotations, which allowed for precise control over their placement. This process took a few tries but greatly improved the layout’s clarity.

With the population density map in place, I added proportional symbols to represent wine consumption per capita. After testing several classification schemes, I found that the Natural Breaks method worked best for this dataset, effectively grouping countries based on consumption levels. I was less successful in the placement of the symbols as I couldn’t quite figure out how to move or omit them in the layout.

For a creative element, and some extra credit, I imported a wine bottle icon from a free .svg vector file and used it as the symbol for wine consumption. I carefully adjusted the symbol sizes to make sure they weren’t too large or too small, aiming for a proportional and readable display. Interestingly, I found working with the symbols more challenging than managing the country labels! I attempted to strike an aesthetic balance with all the information contained on this map.

This project gave me valuable experience with classification methods, symbology, SQL filtering, and overall map design. Tools like Data Exclusion were especially helpful in creating a more balanced, readable map, especially when dealing with small countries that had extreme population densities.

Overall, this project was a great opportunity to practice key GIS and cartographic skills. By choosing appropriate mapping techniques for both population density and wine consumption, I was able to create a final product that’s both visually engaging and informative. While there’s still a lot to learn, this assignment helped me better understand how thoughtful design choices and data handling can enhance map readability and impact.