Communicating GIS Lab 6

This week we experimented with Choropleth maps. We learned different classification techniques and what each are useful for. I was able to create a few maps to practice my skills with the symbology and color ramps. One of the big learning points for me was the use of normalized data rather than raw data. The normalized data allows the creator to successfully display the information accurately while raw data would have no real meaning being classified.

The culmination of Lab 6 was our choropleth map of Colorado population change between 2010 and 2014. For my classification I used 6 classes in order to get 0% between two classes. I chose a color ramp of diverging red and green to show an increase in population with green hues and a decrease in population with red hues. The 6 classes were separated using the natural breaks classification. This gave me an accurate representation for all of the data without skewing the classes. I then adjusted the middle class to begin at 0%.

For the legend I ordered the classes to show the increasing percentages at the top and decreasing percentages at the bottom with their respective symbols. I rounded the percentages to two decimal places since the percentages were generally small. For the title and description I used the Population change and the years it occurred.

Communicating GIS Lab 5

Proportional symbol mapping can be a useful tool when trying to display numerical data based on certain features. This week we experimented with the symbology and how to effectively communicate data to the user. Proportional symbology allowed us to use different sized symbols to represent specific numerical values for different areas. With the areas being proportional to each other based on the data it made it easy for users to draw conclusions based on the data. 

One particularly interesting feature we worked with was how to display positive and negative numerical data using the proportional symbol mapping. In the map below you can see that the same proportional symbols can be used creatively to display a positive value of the data (Green) and a negative value (Red). 

With the symbols staying the same size proportionally based on the absolute value of the numerical data we had to represent them as neutral in the legend and then explain the coloring system. This was a neat solution to an interesting problem. At first it seemed difficult to display the wide range of data in this map with something other than color ramps, but the proportional symbology made it quite simple in the end.

I think this type of symbology also grabs the users attention better than using a color ramp. With different sized objects representing data on a map it draws the users attention immediately to the fact that one is bigger than the other. Rather than seeing a specific color and wondering what that color represents the user can identify that one area has more of something or is larger in a number of something than another area without referencing the legend. This could be extremely useful in quick reference products where the title explains the data.

Communicating GIS Lab 4

This week we are working with color progressions and experimenting with linear vs. adjusted color ramps. The linear progression makes the most sense mathematically when it comes to choosing colors in a ranking scale. The darker shades are definitely harder to distinguish from one another. I did not think they would be as close as the lab described, but it definitely shows in the color ramps. For this reason I think the adjusted progression is the most effective. The color ramp clearly separates the darker shades more than the lighter ones. With my adjustment I went with the “1/3” rule the lab described and it seemed to work. I was pleased with the color ramp and would choose the adjusted ramp over the linear one. Then using colorbrew I selected a slightly greener base. The intervals seemed to follow the adjusted progression, but were almost random in a sense. They were generally larger for the darker shades, but had no real pattern.