Mexico

This week we did 3 maps of Mexico to practice our Cartographic skills and deepen our skills with layouts in ArcMap.  Manipulating the legend continues to take up most of my time; I ended up working with the TOC and changing the legend to graphics.

Sorting It Out

Week 3 was about how to best classify and symbolize data.  Our lab assignment focused on data classification by using four different methods to show the same data.

To create the four panel map, I first set up one data frame completely.  Next, I added data frames and worked to match the layout to the original panel. I felt that keeping all four panels uniform would highlight the classification differences. The four panel map was very useful in showing how a data classification choice can shape the interpretation of the data and possibly lead a map reader to various conclusions.

 I analyzed the attribute table and used the Statistics function to choose a best-fit method.  I thought Quantiles (5 classes) best showed the important clusters in the data. 

That's My Map!

Week 2 started us off on taking ownership of our maps by creating our own style.  As I grow into my personal style, I will try to utilize the Template features to help me create a cohesive body of work as well as save a bit of time.

Statistics Graph

This graph is of a scatter plot I created using the state statistics given to us in the lab. It is a plot of only the California data. The graph shows the relationship between time (Year) and the population.  The graph with its trendline equations is useful in that populations can be estimated further into the future.  It appears a better estimate would be gotten using the polynomial trendline.
One of the reasons I used this California data alone was to check that I received the same equation that I did when I first did the scatter plot using all 4 states as directed by the lab. The polynomial equation gave me a negative number for the California population in the year 2050 - this doesn't seem right!  I still have not figured out where the problem lies.
What it did for me, however, was give me a good chance to brush up on my exponential nomenclature as well as an experience seeing a statistic and thinking "Hmmm, this doesn't seem right. I should investigate the data further."

Good Map, Bad Map

I chose both of my examples from the Example Maps given to us in the R drive.

GOOD Map

 The map title clearly explains what the map is going to convey.  The zones stand out due to the coloration and bolded lines.  The legend is nearly for backup as the large numbers clearly indicate which group is which zone.  The counties within zones are included as this is probably information a map user will need, but they are visually secondary and complement rather than detract from the map.  The map sheet is visually balanced and elements are not crowded or left looking like random elements in space. Additional text gives a useful websites to visit for more information, which is helpful yet concise and does not detract from the main stated purpose of the map.

BAD Map

The map title doesn’t let me know what to expect from the map; “IRAQ” is too vague.  The color choices for the Sunni and Shia categories are very poor and it is difficult to tell the two apart.  Given that I am guessing that the map means to display 3 different religious groups by geographical grouping, there is a lot of extraneous information. The nearby countries do not need to be displayed or labeled.  The rivers really stand out yet they don’t seem to be important to the map message.   The outline around the title looks silly.

 

Overview Map - Population by Country

I enjoyed making this week's map - I enjoy using ArcMap and look forward to learning more of this great program. I find one of the big challenges in this course, which will be the same as I observe at the County, will be data management. Specifically, knowing where stuff is being saved!