Lab 4

For my first map using the Black Population census data, I chose to depict the population rates using the Natural Breaks method in ArcGIS. From these classifications, I manually adjusted the break values to more easily digestable number values that were close to the Natural Breaks. I accounted for the actual Natural Break values in the information in the lower right, which is unfortunately unreadable after uploading these images to this blog. This data classification provides good distinction in the South, but also reveals how homogenous the rest of the country is. For the layout of my map, I chose to balance the map by placing the insets and legends in both of the bottom corners.

With the Asian-American population map, I made minor adjustments to the layout, and I think it provides a more visually appealing design. In retrospect, it may be better to have pushed the upper neatline to the edge and put the title inside the mapped area. In its current form, the legend stands out heirarchically because it overlaps the neatline, but if I had pushed the neatline to the top, this may have not been the case. For my data classification, I chose the geometric intervals method in ArcGIS. This method offered an opposite effect from the African-American population map: while there is distinction between classes across the nation, there is no distinction amongst counties with a substantial Asian-American population since the top class ranges from 8.56% to 46.04%.

In the 3rd map, I chose to classify by standard deviation in order to present the data in a different way. While this method makes a more visually interesting map than the other two, it would also be the hardest for a layperson to understand. I also chose to use a horizontal layout for the legend, which fit neatly above the Great Lakes.

All three maps presented a similar challenge: depicting data which is not well-dispersed throughout the mapped area. However, this presents an opportunity to use the maps to show the proper patterns of where the populations have tended to cluster. This series would not work well together due to the different classification methods I used and different layouts. If I was to create a series, I would have stuck to the Natural Breaks method I employed on the first map.

Following this exercise, I believe GIS is a very powerful tool for spatially depicting data. I think the classifications in choropleth maps presents a challenge, and understanding the purpose and intended audience is critical for presenting data. These maps presented similar data in different ways which would have not been appropriate for all purposes or audiences.