Lab 6: Proportional Symbol and Bivariate Choropleth Mapping

 

When an attribute table has negative values they must be converted to positive before mapping. First you must separate the values to be mapped, in this case, jobs lost and gained. Make a selection of the values needed to create another feature, then use simple math of multiplying a negative by -1 to keep the same values. Then you have two different features to be mapped, positive and negative but it is easy to work. Proportioned dots stacked on each other with different sizes are effective. (The purple background in this map is the result of fatigue and is terrible.)

I used the ColorBrewer website to pick a 3-color classification. Once selected then the information was displayed for me. I chose three 3 color classifications with similarities in tones, which allowed to keep hues that complemented each other. In ArcGIS I opened each color of the symbology to ensure I had the matching numbers when applying the color scheme to each value.

H 321 S 86 V 77	H 277 S 48 V 65	H332 S 87 V 86
H 345 S 36 V 98	H 210 S 27 V 85	H 302 S 26 V 78
H 6 S 12 V 99	H 204 S 8 V 95	H 266 S 5 V 26

Bivariate choropleth mapping is great because of its efficiency in providing information. Having two variables that are related drives home the point better because of the link. In the lab, obesity and physical inactivity are two very good examples of complementary variables. Typically, one does not go without the other, although that is not always the case. In creating this type of map, it can also help bring an understanding that there may be an issue of concern is being addressed and shows a trend in specific areas. For obesity and physical inactivity, it may seem common knowledge they go together but creating a legible, balanced, and good visually contrasted map really can be a powerful tool of information. 

Lab 5: Analytical Data

 This week’s lab was especially tough, I found. It was tough because of the time it took to work through the lab. The to also work through the challenges that naturally come with GIS and data. The objective was to practice the use of different visualizations techniques to present data as well as designing communication material combining maps and graphics. My end result is not pretty but was completed.

I had a challenging time with the layout and working with the design for scatter plot and bar chart. The data was downloaded from the Census Bureau in an Excel csv format. It was the 2018 County Health Rankings National Data, which is quite interesting. We picked two variables to work with and had to create an infographic with maps displaying the relationship between the two. Finalizing the layout is where I ran into some issues when creating one with so much information in it. Putting so much into one layout to convey the message in the data results, such as adding a bar chart with multiple inputs, and pie charts are a couple of them. This was the toughest lab I have had yet and especially to work within the time constraints.

Lab 4: Color Concepts & Choropleth Mapping

The linear and adjusted progression color ramps are similar in their intervals and have a six-class sequential color scheme. In the linear progression, the intervals are evenly placed and calculated by subtracting the class low end from its high end and then dividing the result by 5 to get the intervals. In doing this the results make each separation between the classes 25. The linear progression is easy and simple using the formula. For the adjusted progression, the interval is random and has no specific formula to determine the intervals. I used the intervals from the lab example which followed the rough guideline of 1/3 higher than the largest interval and 1/3 lower than the smallest interval. The ColorBrewer site was easy, with a few clicks I got a blue-to-green multi-color scheme complete with RGB values. Afterward, the color ramp was created in Arc Pro using the RGB values found in the color ramp. The great thing about this site is its ease of use but it also is an “at a glance” way of understanding color ramps.

Linear Progression

Adjusted Progression

ColorBrewer composed

Once I had these the field calculated I went into primary symbology and chose Graduated Colors and Natural Breaks with 7 classes. The 7 classes were defaults, but I changed the percentages to make sense by removing the extra decimal places. For the ranges, the negative changes in population had a greater number at the end than the positive. I felt it was best to leave the numbers as they were because they were not large numbers and made sense of what was produced in the results. I chose 7 classes because there should be a middle label/color for 0 since the data has negative and positive percentages.

For the legend, I removed the word legend and the layer name. I left the label (layer name) in the legend and renamed it so the data can be interpreted more easily. I added the legend at the bottom of the map dragging it wide enough for it to be displayed across the bottom of the page. I had trouble removing the label (layer name), which is why it is on the map. If I could have removed it, then the legend would have looked more balanced with the symbology filling the bottom of the page.