Lab 3: Downloading GIS Data

     The American Fact Finder, a source for population, housing, and economic geographic information, is very useful as base data for making cartographic maps. The site has base tables and appropriate shape files that allow users to easily integrate data into the ArcGIS program.This site is run by the U.S. Census Bureau, which is dedicated to sourcing quality data for the U.S government and public.

      Our task in this lab was to take data from The American Fact Finder site and illustrate it in a cartographically pleasing way in ArcMap. In the process of making these maps we were able to learn more about this site as a source for data, the ArcGIS program, and the integration from one to the other.

Objective I
     This Lab Started by downloading data from our online source. We used The American Fact Finder site at factfinder2.census.gov and locating the data to be used later in the exercise. We were able to simply select data and download them as zip files. The zip files were then extracted and converted to a file type useable in ArcMap ( from .csv, Comma Separated Values, to .xlsx Excel workbook format). 

     We then took a look at the data that was downloaded as well as the metadata that came with it. Metadata acts as a means of understanding the data table that it coordinates with, allowing for a more streamlined table that can still be interpreted. Using these we located our data of interest.

Objective II
     Next, we downloaded the shape files for the Wisconsin census data. Without them we would have been able to move our data into the ArcMap program, but it would still simply be tabular data. We needed a visual representation to attach this data to, and fortunately the A.F.F. site provides us with the appropriate shape files for our data at the county level. This data was downloaded and extracted in the same manner as before.

Objective III
     Next came joining of the data. Now that both the data and the counties shape file were in ArcMap, we needed a way of connecting the data to the map in order to change visual representations according to the data. To do this we used a table join, which takes a category that both sets of data share and uses it to combine them into one table. both the both the shape file and the table we loaded shared a category called Geo ID, which identifies each county in Wisconsin the same way between different tables and files. 

Objective IV 
     The task in this objective was to map the data onto the shape file. This was complicated by the fact that the files we downloaded needed to display data in a certain format. When we downloaded the files, all values were in text format. This means that the computer takes every symbol for its symbol value, essentially treating them all, including numbers, as text. In order for the program to display the data numerically the format had to be changed. The method I used to achieve this was to go to the joined table, make a new field (column) that was formatted for "short integers", and use the field calculator tool to set those numerical values to the same as the symbol values of the field of interest (the one we want to represent visually). Now the numbers are actually numbers! (Fig.2)

     After all this we were able to simply go to layer properties and display the data in a graduated color scheme.

Objective V
     We were now tasked with using all the same steps to find our own data from A.F.F. I chose to simply represent housing data in a manner that was similar to the population data. I was also careful to make sure that the data was from 2010, just like the population data, in order to keep the data itself and any comparison between the two relevant and up to date. It turns out that the distribution the quantity of houses per county matches the population distribution per county fairly well. This makes sense as a place with more people should have more houses. 

     The metadata was important in finding my data of interest. The A.F.F. website fortunately gives previews of what data are enclosed in the files available, but metadata also needs to be examined to see if the variable if interest should be normalized or to see what field title matches your actual variable. 

Objective VI
     The final task was to take our maps and give them a pleasing layout and representation. I chose to change the projection of the layers to something that would more accurately represent the smaller area of the state of Wisconsin. In layout view the maps were framed with the appropriate titles and legends added. Credit was given to the cartographer and data source for this project. (Fig. 1)

Results

Figure 1. Final maps indicating Total Household Distribution and Total Population Distribution per county

Figure 2. The process of adding a column in a numerical format and copying the data from our field of interest involved the use of the field calculator in ArcMap. This was not a part of the program we had used before so I included an image showing what it looked like when I was able to get it to work (after much trial and error). I also tried using excel itself to format the values as numerical but they would simply revert when being loaded into ArcMap.

Source Materials
U.S. Census Bureau, 2010 Census; American FactFinder; <http://factfinder2.census.gov>; (26 October, 2014).

Lab 2: Comparison of ESRI Virtual Campus and Mag Lab Assignments

     ESRI Virtual Campus is an online resource for learning about a variety of tasks that can be done on the ArcGIS suite of programs. Anyone can register online for free and for a small fee per learning tutorial, (or free for a university class in my case), you can learn how to use information systems and the ArcGIS software. At the end of each tutorial you gain a certificate indicating that you have successfully learned a specific skill in this program that is held as a standard in its field of use.

     The Mag Lab Assignments and Tutorials are taken from our course textbook "Mastering ArcGIS". This book is a thorough guide of almost everything in the program as well as background history and information to fully understand all things involved. A chapter generally starts with some reading on background and important information for a subject, then moves on to a tutorial and ends with Tutorial questions about what was learned.

     The two methods of learning the program both have their benefits and draw backs, of course, and I think they both have their place. In general I prefer the ESRI online Virtual Campus, but maybe not for the right reasons.

     The Virtual Campus is something that I think is great for professionals and students alike. Its a resource where you can learn a variety of necessary skills in the field of GIS and for the ArcGIS software, and you don't have to go to a university or pay tuition fees just to use it. It's just a relatively small fee ($30 per tutorial if I remember correctly), and I'm willing to bet that many workplaces in the field would consider covering the cost. The tutorials are straightforward, easy to follow, and I don't have to look down at a book constantly when I do them. There are no pages to flip and there's no searching for something I read earlier in the chapter. The downside to virtual Campus however, is that it doesn't provide a lot of background or context to what we are doing or entirely why were doing it or what we may also need to know.

     The book is a wealth of information. The only problem is that you have to trudge through a lot of reading to get to a point where you can do a tutorial. Surprise, it's a college textbook! But the struggle is real. As a full time student taking 18 credits and a part time worker at 26 hours per week I have to prioritize the amount and quality of the reading I do for classes. After the time for work, homework, and lectures are taken out of the day, I literally do not have enough time left in each day to read everything assigned; at least not thoroughly. Using online tutorials and videos speeds up the intake of information.

     So the dilemma is a complicated one of balancing quality and cost tradeoffs. For me the best solution would probably be to use the darn disk in the back of the book for once. For people who aren't at a university but are already in the field, ESRI virtual campus is a fantastic and affordable tool for continuing and progressing the skills necessary in the field of GIS.

Source Materials

Esri Training. http://www.esri.com/training/main

Price, Maribeth Hughett. Mastering ArcGIS. 6th ed. Dubuque, Iowa: McGraw-Hill, 2014.

Lab 1: Base Data

      In 2012 Clear Vision Eau Claire announced a new development in the city of Eau Claire just south of the confluence of the Chippewa and Eau Claire rivers. Now known as the Confluence Project, this venture is funded by a partnership of Eau Claire’s private developers and public establishments like the UW – Eau Claire, and the Eau Claire Regional Arts Center. 

     Plans for the site include a large, modern community arts center and mixed commercial space for restaurants, coffee shops, retail space, and student apartments. The site would see various public uses along with University students and members of the regional arts center. This development could be seen as a downtown revitalization project; an initiative that would bring people back to the downtown area of the city.

     The task in this first lab was to prepare a report including a base map with relevant information of the confluence site. In the process, we learned about different data sets used to create these maps from areas of administration, land use, and public land management.

Objective I

     We started by exploring the data sets provided in lab for the City and County of Eau Claire using the ArcCatalog program from the ArcGIS suite of programs. This included parcel, road, and zoning features amongst many others. We also viewed properties of topology features in order to understand how and why rules are used in the creation of features.

Objective II

     The confluence site was digitized using ArcMap. We started by taking a simple base map from an aerial image and added in the city’s parcel feature. This allowed us to create a new feature for the Confluence site itself by following the outlines of the parcel feature. The process involved loading features into our map and using editing and snap program elements. After we created polygon features of the buildings located in the proposed site, we are able to fill them with visible colors, distinguishing them from the rest of our base map.

Objective III

     Next we studied readings on the use of townships, ranges, and sections in the Public Land Survey System. This gave us a basic understanding on how townships are sectioned and the difference between a town or city and a township. We then started with another base map and loaded sections and “quarter quarter” sections (one sixteenth of a section) features into our map. We digitized the confluence site again so that it could be seen in its section and quarter quarter section.

Using this system we would identify the confluence site down to the quarter quarter section. The site is located in the NE ¼ of the NW ¼ of section 20, T27N, R9W.

Objective IV

     In this objective we built up a legal description of the confluence site. This includes information about the current owner of the site as well as the location and detailed description of the property included in the site. This information was gathered from the City of Eau Claire Property and Assessment Search website, as well as the parcel number included in the parcel feature that we were provided with. (Fig. 1)

Objective V

     Finally, six maps were made to visualize the data at hand involving the confluence site. The maps were those of civil divisions, census boundaries, Public Land Survey System data, parcels in Eau Claire, zoning data, and voting districts. (Fig. 2)

     Each map was designed on the same base maps and appropriate features were added to each individual map. Features were digitized using proper coloration in order to distinguish between features as well as visualize datum. The site of the Confluence Project was also given a distinguishing feature from all other features and in some cases given a label. This was to understand the sites orientation within the data.

     The Civil Divisions map has the Eau Claire county boundary added and then the divisions placed over this and categorized by type. These represent the types of civil division designated for government, administrative, or legal purposes and in Wisconsin they sometimes represent a town or township. The data here is nominal, so it can be different non related colors

     The Census Boundaries map shows tracts and groups of blocks within those tracts as they are recognized in census data. The color gradient between block groups indicates numerical data. In this case we added population data normalized against square miles.

     The Public Land Survey map is the same one developed in objective III, but we moved in on the area of the Confluence Project within its quarter quarter plot.

     The Parcel map shows individual land parcels and features such as roads that are relevant on this larger scale.  

     The Zoning Data Map shows what areas have been designated as land in a specific use. It is broken down into different nominal groups of what that specific use is and therefore the colors do not indicate a relationship between data.

     The Map of Voting Wards simply has the Voting wards of the city shaded in and numbered as they are publicly recognized. The numbers were given a “halo” to increase their visibility.

     In Layout view, all six maps were oriented on an 11X17 document using guide lines. More guidelines were used once Legends and scale bars were added allowing for consistency in the orientation and location of these map items. 

Results

Figure 1: Legal description of building and land parcels located on the Confluence site.

Figure 2: Final digitized maps used to report on the Eau Claire Confluence Project.
 Names are indicative of the data used to develop each map.

Sources

University of Wisconsin Eau Claire. Frequently asked questions: The Confluence Project.   
    Retrieved from http://www.uwec.edu/News/more/confluenceprojectFAQs.htm 

Irene D. Lippelt (2002). Understanding Wisconsin Township, Range, and Section Land   
   Descriptions. Wisconsin Geological and Natural History Survey. 

Eau Claire Regional Arts Center. The Confluence: Coming Together for the Arts. Retrieved 
   from http://www.eauclairearts.com/confluence/