GIS 6005 Module 4 - Color Concepts and Choropleth Mapping

The three color ramps displayed below show a linear progression through six different shades of brown. A sequential color ramp allows the cartographer to illustrate quantitative data, specifically on a choropleth map [generally, the darker the shade, the higher the value]. While this type of thematic mapping can be quite informative, caution must be used so the viewer can differentiate between the colors on the map. For this exercise, the RGB [Red Green Blue] value was given for the darkest shade of brown on the linear progression, the lightest shade of brown was manually chosen, and the RGB values were recorded for each. To obtain the intermediate shades, the RGB values of the lightest shade were subtracted from the RGB values of the darkest shade and divided by five. This integer was progressively added to each RGB value to obtain the next shade of brown; this is how the linear progression color ramp was calculated. The adjusted linear progression color scheme was derived from the linear progression color ramp, but the incremental values were manually adjusted so that they were bigger in the darker shades of brown and progressively reduced as the shade got lighter. This manual adjustment makes it easier for the viewer to distinguish between the darker shades of brown. The third color ramp was obtained from a free internet resource, https://colorbrewer2.org, by selecting three simple options: color scheme, RGB value, and sequential color ramp.

In my opinion, the results of the linear and adjusted progression color ramps are substantially more elegant and visually aesthetic than the ColorBrewer color ramp. The ColorBrewer color ramp utilizes very bright, bold, saturated colors while the customized linear progressions are softer and milder; they are not as visually overpowering. Additionally, the colors generated by ColorBrewer are somewhat scattered within the spectral range, employing hues such from maroon-brown to orange to yellow, while the shades of the linear and adjusted linear progression color ramps are confined within the same hue [brown in this case], only differ in saturation, and possibly lightness, values. Lastly, small modifications were easy to make throughout the construction of the adjusted linear progression ramp, so complete control is in the hands of the cartographer; ColorBrewer has approximately 20 sequential color ramp choices, so there is little room for customization. The ease and convenience of ColorBrewer is a benefit on its own accord, but time permitting, I would prefer to have complete control over the colors within the map.

After experimenting with colors and sequential color ramps, the next portion of the lab assignment was applying these fundamentals by creating a choropleth map. A choropleth map is a thematic map where 'each data collection area is given a particular color lightness, color saturation, or pattern texture depending on its magnitude' [Kimberling, 2012, p. 191]. In the map below, the percentage of Hispanic people is mapped for each county in Texas [the data collection areas] and the shade of the county is determined by the magnitude of the percentage.

To accurately portray the information, the data must be normalized, and an appropriate data classification system must be adopted. Data normalization is standardizing the data so accurate comparisons can be made between each data collection area. To illustrate, a raw count of 1,000 Hispanics residing within a rural county of 5,000 is quite different than 1,000 Hispanics living in Dallas County. Lastly, a data classification system must be employed. While data classification systems are well beyond the scope of this blog post, ESRI [the Environmental Science Research Institute] has a great introductory resource [it can be found by clicking here]. For this specific map, the natural breaks classification system was the best option. 

For the final portion of this assignment, all subjects explored throughout this module were applied in the creation of the map below.

This map is a choropleth map that shows population change between 2010 and 2014 for each county in the state of Colorado. For the diverging color ramp, I chose to employ the natural breaks classification system, slightly modified so they were divided by 0% change. Hence, a red shaded county represents negative growth while a green shaded county represents positive growth. Furthermore, the darker the shade, in either direction, the higher the magnitude of population change. Lastly, for this map, I chose to employ a custom projected coordinate system. This was an intentional decision due to the fact that there were two NAD 1983 State Plane systems [one for the north and one for the south] for the State of Colorado, but not one that encompassed the entire state. Additionally, the state of Colorado intersects UTM Zones 12N and 13N, so the use of a custom projection system minimizes the distortion that would have occurred otherwise. 

I am pleased with the subject matter of this module, and I believe that a fundamental understanding of these concepts are displayed throughout the design of these deliverables.

Sources:

Environmental Science Research Institute. [2024]. Data Classification Methods. https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/data-classification-methods.htm

Kimberling, A.J. (2012). Map Use: Reading, Analysis, Interpretation (7th edition). ESRI Press Academic.