Introduction
The question I am trying to answer with my data is a very basic one. I am trying to find where a 2013 nursing graduate from UW-EC would live if he/she wanted to live within a half of a mile from her job at the 5th avenue Mayo hospital. This recent graduate also does not want to live within a half of a mile from the UW-EC campus, or the noisy bars on water street because he/she does not want beer cans and broken bottles littered in her yard every time somebody throws a party. By using simple data analysis, the parcels of land that best fit this criteria can be located and arranged on a cartographically pleasing map that will allow the fictional nurse to know where to start looking for houses.Data Sources
In order to answer this question, I needed to compile data regarding the land parcels around the Eau Claire area. This data ended up being located in the geodatabases for lab 1 and lab 3. A data concern that I had was whether the Eau Claire data was up to date. If land parcels were completely wrong due to the data being too old, it would render the map completely useless. This was less important with the campus data, which may have been off due to the recent construction. Because I was trying to avoid the UW-EC campus and water street by a half of a mile, it did not matter if one building was not in the correct location. It would not affect my final map either way.
Sources:
All data collected by the City of Eau Claire and Eau Claire County 2013
Methods
In order to solve my problem, I had to identify all of the buildings that I would be using to make my map. To do this, I digitized parcels for water street bars and the hospital. I then used the union tool on campus buildings and water street bars to find the areas that my fictional character did not want to live by. Next, I used select by location to select all parcels that fell within a half-mile radius of the Mayo Luther Middleford Hospital, and created a new feature class based on this selection.
Now that I had all of my specific parcels of land located and labled, I was ready to do data analysis on the rest of the information and finish the map. The next step I took involved using the buffer tool to create a half-mile radius around each of the parcels that were deemed undesirable to live near by the fictional nursing graduate. The feature class created by the buffer was then dissolved to create one large shapefile that covered all of the areas that were too close to the bars or student housing. To bring everything together, I ran the erase tool to produce a feature class that only showed the parcels of land that were within a half of a mile from the hospital, but were at least a half a mile from the campus or bars. The steps that I took to create the map can be seen in my data flow model (figure 1). This map (pictured below) could be used to locate which areas would be the best ones to seek housing in. Lastly, a locator map was created to show the area of interest within the state of Wisconsin.
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| Figure 1- A data flow model that shows all of the steps taken to produce my Eau Claire map. A larger map can be seen by right clicking the map and opening the picture in a new tab. |
Results
The result is a map of the land parcels around the Mayo Luther Middlefort Hospital, located on 5th Avenue in Eau Claire, Wisconsin (figure 2). This map could be used to find a suitable location for housing in the Eau Claire area that is within .5 miles of the hospital, but far enough away from the noisy college students. A locator map is present on the right side of the map. This locator map shows the location of the city of Eau Claire inside of Eau Claire county, and the location of Eau Claire county inside of the state of Wisconsin. As per any cartographically pleasing map, sources, a scale, a north arrow, and legends were applies to create a clean, easy to read map.
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| Figure 2- A map of the land parcels around the Mayo Luther Middlefort hospital in Eau Claire, WI, as well as a locator map showing Eau Claire's location. A larger map can be seen by right clicking the map and opening the picture in a new tab or window. |
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Evaluation
I personally thought this was an interesting project. Thinking of my own problem forced me to think about the role that each tool in ArcMap plays in data analysis. It also gave me the freedom to use any and all of the skills that I have learned while taking Geog 335 at the University of Eau Claire. As a geology major, I may not be using all of these data analasys tools, but I will definitely be using the skills I have learned at some point down the road.
