Marshall Kirchner's UWF GIS Blog

The final module of Communicating GIS course involved using proportional symbols and bivariate choropleth on maps to represent different types of data. I find that these map types are excellent at showing common trends and symbolizing data in a unique way. This lab began with using proportional symbols to represent different Indian cities' populations. As recommended in the lab instructions, I opted to use a darker background for the country of India, and a light, bright colored symbol for the cities. This symbol was pink and had a high level of saturation. I opted to use a yellow outline for the city symbols, as this helped them contrast even further with the dark blue background. For the size, I chose a minimum of 5 points and maximum of 40, as I found this combination reduced many points of overlap while still representing the data appropriately. For my legend, I used the nested circle legend design. This allowed for me to show the proportional symbols, while saving space and al

 The focus of this week's laboratory assignment was on numeric, tabular data. Luckily, ArcGIS Pro and Microsoft Excel are excellent in data visualization which allows for informed analysis of important topics. This week, I was tasked with determining two a relationship between two variables from the County Health Data posted by the University of Wisconsin. I selected a more obscure relationship with a profound correlation. The selected variables were the Food Environment Index and impoverished children. The Food Environment Index was determined for each county in the United States, and consists of a ranking 0-10, with 0 being the wort in terms of access to health foods and 10 being the best. The impoverished children statistic was normalized for each county and represented as a percentage of the total number of children in the county. These statistics were then used to create meaningful graphs and maps that outline their unique correlation.  I chose to utilize Microsoft Excel to cr

While easily overlooked, color choices and data classification schemes are instrumental in constructing accurate and appropriate maps. This laboratory assignment highlighted how color selections impact a map's overall legibility and message to the viewer. Adjusting colors to meet the needs of an array of audiences, such as those who are visually impaired or even color blind is also very important to take into account when creating a map. Throughout this post I will highlight the different color ramps and maps that I created during this fourth lab in Communications in GIS. I began the assignment by manually creating two color ramps - linear and adjusted. These ramps were constructed using various RGB values within the ArcGIS Pro 'Color Properties' option. I used different formulas and patterns to determine what RGB values to use, such as using a 33% increase in the interval between the darkest and next darkest and 33% less interval between the lightest and next lightest for