GIS I Lab 4: Final Project

The Ideal Location for a Campground

Introduction:

For my final project in Geography 335, my research question was, “Where would the best place be for a new campground in Oneida County, Wisconsin?” One objective of my project was to identify an area or possible areas that would be suitable to create a new campground in northern Wisconsin that took advantage of the natural resources and scenery. The other objective was to craft a data flow model that I could create and complete on my own; demonstrating that I have mastered the concepts I have learned throughout the course.

My intended audience is for investors who see a potential in environmental tourism. Wisconsin is blessed with a large amount of green space that is still relatively remote in this world of constant urbanization. The remoteness of Oneida County offers something would be enticing to campers who wish to get away from the hustle and bustle of everyday city life. Being located somewhat close to Green Bay give the county a desirable location as a weekend summer getaway.

Data Sources:

For the ideal area for campground to be located, a moderate amount of data sets would be needed. Data taken from the Wisconsin DNR included the county forests in the state of Wisconsin as well as all lakes in the state. The major roads data set was also taken for reference. This data set would not be taken into account for the actual analysis. ESRI provided data for the cities and county borders.

To access the actual data, I had to connect to the UW-Eau Claire data servers. There I was able to pick and choose all that data from a huge database that contained a wealth of information. Taking data straight from the Wisconsin DNR and ESRI insured the most accurate information compared to finding data online from a website whose credentials may not be able to be verified.

When running analysis on GIS, there should always be data concerns. I had multiple concerns over some of the data I had collected. One was the county forest borders. I was unaware if there were any logging operations that have occurred in boundaries or near the boundaries that could have disturbed the natural tranquility I was searching for. Another concern I had was settlements on lakes. As I desired remoteness for a possible campgrounds, I could not tell if lakes had significant human development on them. This is a problem as a lot of lakes in northern Wisconsin have become pseudo-resort areas with large human footprints. A final concern I had was with the population and size of the cities ESRI provided. Knowing Rhinelander was the only significant town in Oneida County with a human population of 7,557, I was unable to estimate the size and scope of the other unincorporated communities that were spread throughout the rest of the county.

Methods:

Once all the necessary data had been acquired, certain tasks had to be performed so analysis could be run. The first step required me to locate and isolate Oneida County from the rest of United States’ counties that ESRI provided. Once selected, a new layer was exported from the selection of Oneida County. To prevent analysis from being run on data that included the rest of United States and Wisconsin, a series of clip tools had to be run on the cities, county forest, major roads, and lakes data files. These new clips contained only the necessary data that fell within the boundaries of Oneida County.

The next step would finally allow the data files to be appropriate for analysis. The data downloaded was projected in a Web Mercator projection among other projections. To make sure all the data would be presented in the least amount of distortion, as well as sharing the same projection, the project tool was used. Therefore, all data presented in the final map is presented in the NAD 1983 HARN Wisconsin Transverse Mercator (US Feet).

To select the best possible campground, I came up with three factors that would decide the ideal location. The first was that the campground had to be within a quarter mile of a lake. The second was that it needed to be at least five miles away from an urban settlement. The final stipulation was that the campground had to be at least one mile away from protected county forest. Four tools were used in this process: buffer, dissolve, erase, and intersect.

Lakes, county forest, and cities were all given their own buffers of .25 miles, 1 mile, and 5 miles, respectively. Lakes then had their buffers dissolved so lakes close to one another appeared as one. Cities, along with their five mile buffers, were erased from the map. This final layer was then intersected with the dissolved lake buffers and forest buffer. This process is depicted in the model below.

The following image shows the date flow model used for the assignment. Tools are shown in red. Inputs and outputs are displayed in blue.

Results:

According to my criteria, there only appears to be one area that is suitable for a campground that wishes to be both remote as well as near water and woods. This area falls on the western end of the Willow Flowage. Being situated nicely between a huge tract of county forest as well as a large water body offers a perfect place for that weekend getaway. Not being near any urbanization provides the tranquility that campers clamor for.

Although there were three other large bodies of water in Oneida County, none were near county forest that my criteria specified. Also, some of the lakes fell within the five mile buffer of a local community so they were eliminated by my criteria as well. 

This map shows the final results for this lab assignment once all tools and analysis had been completed.

Evaluation:

I enjoyed this project due to the lack of hand-holding that was typical of MAG assignments we have done prior in the class. Everything from the topic to the data used was up to me. I was in control of the assignment and I had to create my own road map that would answer the question I selected. This fostered a sense of independence that I will now be able to carry with me into projects I may be tasked with in GIS in future course work or the professional world.

Not knowing much about the geographical layout of Oneida County, I expected there to be more lakes and larger tracts of county forest within its borders. However this was far from the case. If I were to redo the assignment, I would do more research into the features of a county to find one that had more waterways or protected forest. These counties would possibly contain more sites than just the one area I identified in Oneida County.

A few challenges I encountered started from the beginning of the assignment. I had a difficult time in coming up with my own specific spatial question. I wrestled with many ideas, but some could not be answered with data that was provided or recommended to use. As the land cover date file was described as not being reliable, I had to find my own substitute for a data file that would show the most amount of untouched forest.