Welcome to a collection of my work pertaining to the Master of Science in GIS Administration program at the University of West Florida. I have utilized a variety of software platforms to produce these maps and cartographic material, including ArcGIS Pro, ERDAS Imagine, Microsoft Excel, and Google Earth.
All work is solely for educational purposes and is not available for reproduction.
M5 - Choropleth and Dot Density Maps
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Depicting Choropleth and Dot Density Data across European Nations
Among the various laboratory assignments this semester, this was one of my favorites to work on. I enjoyed having the ability to showcase data in a new way that is both aesthetically pleasing and can show important trends. This assignment involved showcasing both population density data and wine consumption rates for the countries that encompass the continent of Europe through the best-fit methods. We were tasked with using a choropleth method to display the population densities of European countries. To do so, I utilized the population density field in the dataset and chose a graduated color ramp ranging from light to dark purple to display the densities. I analyzed the histogram of the dataset and found that since it varied so widely and many countries in Eastern/Northern Europe were very sparsely populated, it would be best to employ the quantile classification method. Thus, I chose this method so that each class would contain the same amount of features (i.e. 0-45 persons per km would have the same amount of countries in it as 203-768). Then I selected five classes, because I found this number to show the differences among densities best. Then we were tasked with displaying wine consumption rates among the countries. To do so, I used the graduated dot symbols method. This method broke up the consumption levels into classes so that one could clearly see differences in the levels as opposed to using proportional symbols. I chose a red dot, as it created a stark contrast from the purple symbology of the countries. I also set the range of dot sizes to be larger (1-24 points), so that ArcGIS Pro would break up each class dot values into dots that are easy to differentiate and compare their values in the legend. Speaking of legend, I chose to remove the gap in the symbol values for the density data so one may clearly see the graduated color ramp, and to adhere to choropleth legend guidelines. To create the inset map, I added a new map to my map layout showing the smaller countries and used the extend indicator tool to showcase where on the map this inset would be displaying. For Europe's micro-nations (such as San Marino, Monaco, Jersey, Gibraltar), I used the data exclusion tool to create an SQL Query to effectively remove them from my map, as these countries were not relevant to the assignment. Overall, I greatly enjoyed utilizing the various tools, methodologies, and classification schemes to showcase the data. Due to excessively slow server times and being unable to get in contact with UWF's IT Department, I was unable to add the country labels as would not load into ArcGIS Pro, even after waiting hours and reseting my program. I was also unable to remove the symbology from the area of the map where the inset map covered for the same reasons. Next week I will be contacting the IT department to discuss a hard reset of my account so that these issues do not occur in future laboratory assignments and so that I may showcase all of the data with ease. All in, I encountered a few hiccups in the lab, but otherwise enjoyed using my learned skills and personal style to create a map that employs visual hierarchy and effective classification schemes.
