Goal and Background: For this lab I am working as an intern at Clear Vision Eau Claire, which is a county wide action to create a combined vision for Eau Claire.  Clear Vision Eau Claire announced a public-private partnership between local developers during the spring of 2012.  The local developers, UW-Eau Claire and Eau Claire Regional Arts Center, intend on creating a new development on the confluence of the Chippewa and Eau Claire Rivers.  The Confluence is located in downtown Eau Claire and the development is going to include a new community arts center, university student housing, and a commercial retail complex beginning in 2014.  The goal of the Eau Claire Confluence Project is to become familiar with many spatial data sets used in public land management, administration, and land use while creating several base maps for the Confluence Project.   

Methods: The results consist of six base maps each created in ArcMap 10.2.  The six base maps represent various data sets in the city of Eau Claire and Eau Claire County, while showing the digitized parcels involved in the Confluence Project.

The first step was to digitize the parcels that are involved with the Confluence Project.  To do this, I added the parcel_area feature class with a hollow yellow outline over the world imagery basemap.  I then zoomed in to the Confluence Project area where the Eau Claire River meets the Chippewa River and used the identify tool to locate the two parcels purchased by University of Wisconsin-Eau Claire.  I then used the editor menu to digitize the two parcels with the polygon construction tool.  I finally saved my edits for further use in the six basemaps. 

I then inserted a new data frame for the Public Land Survey System (PLSS) map.  To complete this map, I first added the imagery basemap and then the PLSS_Townships feature dataset from the City of Eau Claire geodatabase and the 2009-17-13 Eau Claire geodatabase.  I made the townships hollow with a yellow outline.  These depicted the 18 townships in Eau Claire County.  I then added the PLSS_qq feature dataset, which consists of quarter quarter sections of the townships, and made that hollow with a yellow outline as well.  I inserted my proposed site digitized and changed the color to bright red.

I inserted another data frame for the Civil Divisions map.  I added the world imagery basemap followed by the county boundary of Eau Claire and civil divisions.  I changed the colors of each of these and turn transparency on 50% so boundaries could be seen as well as the world imagery basemap underneath.  I then added my digitized proposed site in bright red.

The next map was Census boundaries.  I added a new data frame and the world imagery basemap.  I then added the BlockGroups feature class and Tracts group.  I then symbolized the BlockGroups using graduated colors in the symbology properties and normalized my values so that there were no decimal places.  I used a noticeable color for the Tract boundaries and made the BlockGroups slightly transparent so the world imagery basemap could be seen underneath.  I then added my digitized proposed site and zoomed in to the confluence site. 

I added a new date frame for the Parcel Area map and inserted the Parcel_area, Centerlines, and Water feature classes from the City of Eau Claire geodatabase.  All of these were over the world image basemap.  I symbolized the Parcel_area with a hollow symbol and a brightly colored outline.  I chose a color for the centerlines, kept the water blue, and inserted my digitized proposed site in bright red.

I inserted another data frame for the Zoning map. I then added the zoning_area feature class.  I had to symbolize unique values based on the zoning_cla.  Creating this map was slightly more complicated because of all of the specific zoning codes in the zoning_cla values.  I had to group all of the specific codes together into more general categories such as commercial, residential, industrial, and transportation.  I then labeled these zones on the map with colors, inserted centerlines, and inserted my digitized proposed site in bright red. 

I added my final data frame for the Voting Districts map.  I added the voting districts class for the city Of Eau Claire and made the color blue and 50% transparent.  I then labeled the voting districts with a halo around them to make the numbers more readable.  I also added my digitized proposed site in bright red.  

I then switched to layout view and positioned and adjusted all the maps so that they were the same size, three maps on top of the other three.  I renamed all data and features so the legends would be easy to read and presentable.  I inserted legends and scale bars with gray backgrounds so the colors presented in the legends did not come into conflict with the background.  I used a callout label to label the proposed sites that were too small to be seen.  I added titles to each map, the source on the bottom left, and my name on the bottom right.


Results:


 Figure 1 shows six maps: Eau Claire City Parcel data, Civil Divisions, PLSS featuers, Voting Districts, Zoning, and Census Boundaries. Eau Claire Parcel data shows the various properties around Eau Claire, including the two parcels involved in the Confluence Project.  Civil Divisions shows the City of Eau Claire versus the Town of Eau Claire.  PLSS featuers shows the quarter quarter sections of townships zoomed in to the confluence between the Eau Claire River and the Chippewa River where the two Parcels are located.  Voting Districts simply shows the boundaries of the voting districts.  Zoning shows the various types of zones in Eau Claire around the confluence such as commercial districts, industrial districts, and business districts.  The Census Boundaries map shows population density per square mile.     

Figure 1 

Sources:  

"Frequently asked questions: The Confluence Project". (2014). Retrieved Febuary 17, 2014, from http://www.uwec.edu/News/more/confluenceprojectFAQs.htm