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.
