Europeans and Wine

This week we had to learn the basics of choropleh mapping and proportional symbology. This was building on our work with data classification (which sadly, I'm still wrapping my head around). The last two weeks saw me travelling about frustratingly building maps on my laptop while wedged into airplane seats in turbulent skies.,  Now that I'm settled again, I was really able to put some good work into this map.

To create the map, I starting in ArcGIS. I have it up and running on my pc, though that doesn't mean it's much faster compared to running it through the remote desktop. The first part I focused on was getting the choropleth right. This meant two things: 1) Determing the classification and 2) the color scheme. First, I tried to pick the best classification that best suited the population density. (For this part I picked random wildly different colors for each class so I could see it best). After re-reading the text and some google searches on the classification methods I boiled it down to equal interval and quantile. After classifying and reclassifying, I picked quantile. I felt it displayed population density the best. It's quite easy to determine which countries are most dense and least dense. (I did exclude a large set of outliers, mainly the small regions, statelets and countries. To ensure accuracy I excluded the same areas from the wine consumption data.) I'm assuming this map is meant for a more casual observer given the information so I wanted to be as easily understood as possible. I then selected the green color ramp and tweaked each color somewhat individually through their individual properties. I used colorbrewer but honestly, I'm at a lost at how to use it in arc. I found some information on scripting, but I was running out of time so I decided to use the colorbrewer as a guide as I tweaked the green colors.

Now the wine. For this part, I decided to go with the graduated symbology. I did this for two reasons. First, proportional wasn't displaying nicely on the map and second, the graduated symbols displayed nicely on the legend and was thus easier to understand. For this data, I selected equal interval classification because I felt it displayed better on the map and in the legend when compared to others. Again, I was concerned with how easy it is for the reader to determine the information. I changed the symbology from the default dot to a wine glass. I found this picture on google. In arc, I went to layer properties > symbology > graduated symbols > template > edit symbol. Here by going to type, I can go to "Picture Marker Symbol" it allows me to import the picture (png file) to use as a symbol. I then graduated it from 15 to 50. For the most part, it displayed nicely, though there was overlap in geographically close areas (i.e. the Balkans).  For the Balkans I created an insert map and added the same data from the main map. I then included the basics: legends, north arrow,and  scale.

After that I exported my arc map to AI. In adobe, I added the title and the description. I changed the background to be the pale blue which sat nicely behind the green color ramp. I then had to modify the legend. I was having this problem (which seems somewhat common) in which the symbols wasn't displaying correctly in the legend (or even in the layer bar on the left side in Arc). I had to build the legend from scrap by copy-pasting the wine glass symbol off the map into a rectangle then added the numerical data below each one. I liked the finished product, though I'm not happy where I placed it. I feel with the map, I left too much dead space in the upper left hand corner, but given the layers in AI, it was too cumbersome to re-position the map. I eliminated the glasses that were overlapping or covered too much of the country. For example, I used one symbol for Switzerland and France since they were the same size. I was happy for small countries that don't drink much wine, because it was easy fitting the symbol within the borders. For the insert I removed all the information from the Balkans area on the primary map and ensured that in the insert it was well displayed. I had to use leader lines to clean up the clutter. Over all, I was happy with the final product. I feel AI allowed me more freedom in creating a more polished map (albeit I find it more cumbersome than Arc).

Using choropeth for the population density and a graduated symbology for the wine consumption, we see where wine is consumed the most per capita. The most densely populated countries are the UK, Belgium and the Netherlands.