Brooke's GIS Blog

 One spotlight of this week's lab was proportionate symbol mapping. The objective for this section of the lab was to map values related to job growth from 2007-2015 in order to see which areas had positive and negative growth. There was a challenge in mapping the negative job growth, because the values in the attribute table were negative, thus unable to be mapped using ArcGIS Pro's proportionate symbology. To overcome this, the negative values were exported to a new feature class using an attribute function, and a new field was added which calculated the absolute value of the negative job growth, eliminating the negative variable. These values were then plotted like normal, under the alias of "jobs lost."  Another section of the lab introducing Bivariate mapping. This particular symbology style is helpful for showing relationships between variables in one map. In order to prepare classes for mapping, the number of breaks, and the values which constitute a break, need...

 This week's lab focused around data visualization for maps in the form of scatterplots, bar charts and pie charts. To begin, the first task involved selecting two normalized variables from a spreadsheet provided by the Robert Wood's Foundation Health Rankings & Roadmaps. The normalized variables I selected were teen birth rate and child poverty rate. I created a quick scatterplot to determine if a relationship existed, which proved the relationship to be positively correlated. A summary of the design strategies I employed related to the chart aspect was choosing to learn the method of creating charts on Arc Pro vs. Microsoft Excel, which I was already more or less familiar with. After getting used to Arc Pro's layout for creating graphs, I was impressed with the ability to customize. The charts I chose were a scatterplot detailing the relationship of teen pregnancy to childhood poverty, and two bar graphs showing the top and bottom 3 States for rates of teen pregnancy....

 Looking at my color ramps, you can easily see I struggled pretty significantly with calculating an even color ramp, from linear progression to adjusted progression. Although performing the calculations was basic math (which can still be challenging!) I found myself having to readjust the values manually, regardless of my calculation. Clearly, the results from Colorbrewer are clean and without deviation, demonstrating that once again, computers can do things best! For the choropleth population change map, I calculated North Dakota's percent change from 2014 to 2010. I found this interesting because so much of North Dakota has decreased in population or is barely increasing. My design choices including using Jenks Natural Breaks to classify values in classes of 5. I chose this method because I felt it best represented the severity of many of North Dakota's Counties which have a declining or barely increasing population, in comparison with the Equal Interval Classification and Qu...