Bivariate Mapping

 This week, we worked on bivariate choropleth mapping and proportional symbology.  Below is a bivariate map I created to show the relationship between the percentage of inactivity and the percentage of obesity in the United States.

I think bivariate mapping creates the best visual example of mapping the relationship between two variables that I have ever seen and worked with.  Provided the correlation is strong, this form of mapping condenses so much information into an image that is both easy to understand and pleasant to look at.  I am very thankful for the opportunity to learn this mapping technique because I think it will be very useful in my future endeavors, whatever they may be.  Instead of having to read a lot of text and look at multiple keys to understand a two-variable relationship, a map like this allows you to gain a solid understanding from a relatively quick glance.  And the greatest effect comes from a solid understanding of color and the ability to turn map items into graphics for free arrangement.  I had never done this before this lab and I find it much easier to work with, although probably more limited in scope, than Adobe Illustrator.

Infographic

 This week, we created an infographic using information from the 2018 County Health Rankins National Data.  I selected unemployment and children in poverty as my two variables for comparison.  Please view the infographic I created below.

Color and Choropleth

 This week, we experimented with color ramps and worked to develop a deeper understanding of how color is used to develop more meaningful and beautiful maps.  Below is a map of population change in the state of Colorado from 2010 to 2014.  I used a 4 part color ramp with two classes showing population increase and two classes showing population decrease.  I used a divergent color ramp from Color Brewer and manually created the colors on my ramp using the RGB values listed on Color Brewer.

Terrain Visualization

 This week, we explored terrain visualization tools in ArcGIS Pro.  We explored DEM's and TIN's, contour intervals, and hillshade effects.  Below is a map I created of the landcover in Yellowstone National Park.  This landcover map is overlaying a DEM with a multidirectional hillshade effect.