Best Location For Amusement Park

Fall ‘03
Click
here to
see a PowerPoint Presentation for this project.
Outline
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Project Outline
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General Location
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Populated Areas
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Available Transportation
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Best Region in Nebraska
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Finding
the Data
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National Map Viewers
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Nebraska Natural Resources Data Clearinghouse
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Working the Data
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Export .e00 extensions
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Modifying Projections
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Roads
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Landuse
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Spatial Analyst
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Hillshade
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Slope
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Viewshed
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Cost Weighted
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Reclassifying Data
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Raster Calculator
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Best
Locations
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Narrowing the Options
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Location #1
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Advantages
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Disadvantages
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Location #2
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Advantages
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Disadvantage
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Location #3
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Advantages
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Final Layout
Click
here to
see a PowerPoint Presentation for this project.

Project Outline
For my final project in Geographic Information Systems I was curious about where
in Nebraska is the best location to put an amusement
park. Nebraska currently does not have any permanent fair-type parks in
the state, nor does it have many tourist attractions to draw outsiders. The attraction does not
have to be a large theme park (i.e. Disney World); however, it should be large
enough to draw people for many years. With that being said, Nebraska is
due for a medium size park and I will show you how I obtained my data for the research
and used ArcMap to come up with the
best location.
General Location
The first research I did was to find a general area in which to put a 200 acre
park. Since Nebraska covers over 77,000 square miles of land, I needed to
narrow down the area. This was fairly easy to do. Past family
vacations and initial research (sixflags.com)
showed me that all theme parks revolve around populated areas. With Omaha
and Lincoln in the east and the Sandhills in the west, Eastern Nebraska is
obviously the most
populated part of the state. However, the park should not be located in
anyone of these cities. Omaha and Lincoln are the largest cities in the
state, which makes them a great candidates, but the cities are still rapidly
growing. You would not want to build a park on what is now the edge of the
city, only to have the city grow and totally encompass the park. So a
fairly large buffer needs to be put between the park and a large city.
The next issue on a location is the available transportation near the park.
All parks need an adequate roads to get visitors around smoothly; in fact, many
amusement parks are location right off an interstate. A developer could
pick a site that has only county dirt roads around it; however, it would soon
need to be paved and wided to support the traffic need. This comes as an
added cost to the park, so finding an existing major road is important. In
Nebraska, Interstate 80 is the only major road big enough to support a the
traffic needs. So the park would have to be somewhere close to I-80 and an
exit. That narrows the location of the park to a relatively small area, half
way between Omaha and Lincoln and off of I-80. There is already
development around that area, including: Mahoney State Park, the Wildlife
Safari, and the SAC Museum. However, the as mentioned earlier a theme park
revolves around a populated area. Omaha has a
greater population than Lincoln. So the location of the park should not be
directly between the two cities, but a little closer to Omaha. That brings
the general location to around southwest Sarpy County.
Assuming all land that has not been urbanized is available,
which is a large assumption, I started my search around that area.
Finding the Data
Once I was able to locate a general area, it made it much easier to find data
for my project. Part of the assignment was to be able to located much of
your data on your own. I was able to find much of my data through two
websites. The internet is an ongoing maze of information, so
knowing the
general area of where I needed my data was very helpful in finding it. The
first website was the National
Map Viewer site provided by the USGS. There is a total of four map
viewers on the site: the Original National Map
Viewer, the new National Map Viewer,
Seamless Data Distribution System Viewer, and the GISDATA Viewer. Each
viewer is an interactive map that lets users pick what type of data they want
and about any location in the country. The viewers have easy navigating
tools and have many different layers All of them contain slightly
different types of data, so finding which viewer is best depends on the data
needed.
For this project I only used two of the viewers from USGS to obtain data.
Each viewer has the capability for multiple dataset downloads which makes
obtaining the data much faster. With the new National Map Viewer I was
able to download political boundaries, roads, cities, and hydrology. With
the Seamless Data Viewer I was able to download a 1/3" National Elevation
Dataset (NED) or and DEM and a land cover map from 1992. A benefit to
using these viewers is that all downloads come as shapefiles, which makes using
them in ArcMap much simpler.
Another website that I used to download data is from the
Nebraska Natural Resources Data Clearinghouse.
At this site you can search for data by category
or by area. If the user desires,
they can use a simple interactive map to narrow down where they want data.
All the information at the site is Nebraska data, so the user does not have to
worry about searching through other states data. At this site I was able
to download a detailed road map file provided by the U.S. Census TIGER and a
Sarpy County land use vector file. A downside to the site is all that
downloads comes as ArcExport format, which adds an extra step in the working of
the data.
Working the Data
With using two different websites, the data need to be slightly
modified for it to be worked with in ArcMap. First, all the data from the
Data Clearinghouse had to be exported. Using ArcImport I had to
take all the .e00 extension files and convert them to shapefile. A fairly
easy process, but a extra step not needed from the USGS data. However, the
USGS data and the Clearinghouse data had different map projection that would not
match if brought into ArcMap. So, using ESRI's ArcToolbox I was able to
modify the shapefile's projections. I choose Albert's Equal Area Conic
projection for all shapefiles in my project.
After working with the data so it would match, I had to modify the roads
shapefile. The file had all the roads from the 2000 Census, but the roads
were not ordinal classified; meaning, all the roads looked the same and wider
roads were not thicker in the file. This created a small problem since
Interstate 80 went through the map, but it looked the same as a county dirt
road. So I had to export the I-80 polygon and create a new shapefile that
would stick out more than the smaller roads. Another area that needed to
be worked on with the roads shapefile is the Interstate exits. You could
not easily decipher where an exit was located, so I had to find where in the
area was an exit and create a shapefile
for it also. That way it was easier to locate both I-80 and Exit 432 on
the map.
Landuse
was another modification that needed to be made to a shapefile in ArcMap.
The landuse dataset came as a vector file and was not color classified. I
had to convert the vector file into a raster file, so that future maps would
overlay easier on it. Converting it also insured that when I was ready to
work with the data ArcMap would be able to use the file for analysis.
Unfortunately the file came as with no color classification. So using the
ArcMap program I was able to find out which polygon was each type of landuse,
and then assign a color to each six categories. Luckily I did not have to
do much modifying of my data. I think that getting data from only two
sources helped in limiting how much manipulation needed to be done.
Spatial Analyst
After I got all my
data modified, I was ready to start the analysis part of my project. All
of the analysis for my project
was done using the Spatial Analyst function in ArcMap. Spatial Analyst
provides the user
with a large range of powerful spatial modeling and analysis features which has
been shown to us throughout the semester. It has a variety of different
functions that has helped me discover a location for an amusement park.
The following is a list of functions I have used and the results of each.
- Hillshade
The hillshade function calculates
how each cell of a raster file would appear if it were
illuminated by a light
source. It uses the digital elevation model
(DEM) for its
calculation. Once it was created you can immediately notice
the large floodplain
northwest of I-80. You can also easily see how much
hills
are in the southern part of
Sarpy County. Hillshade does not serve too
much an analysis function; however, it does
give the map more of a three-dimensional appearance which can be seen throughout the
rest of the project.
- Slope
The slope function
computes the
maximum rate of change between each cell on the
DEM.
I used this to determine where the steepest
slopes are in the
area. Green colors
indicate flat surface, while red shows a
steep area. Notice the affects of the Platte
River, and how it
was cut
into the land. Again this
function illustrates the floodplain
well. Using this
spatial function automatically eliminates a large
section for park
development.
The flatter the land the better, so any area in red is not a wise place to
build a park due to the cost of flattening the area.
- Viewshed
The
viewshed is a utility that calculates the cells in a triangulation irregular
network (TIN) that can be
seen from one or more observation
points or lines. The first image is any area that can be seen (Green)
from I-80.
This is important
because most of the park should be
seen from the interstate. If it is
visible
then I
believe it will be a greater attendance draw, plus it is free
advertisement
since thousands of
drivers would pass by on I-80 daily. With that said, I
can eliminated
certain large areas on the map that
are in red. The other viewshed map
that was created was using where the Platte River can be seen from.
This is also
another important factor because the park should have a scenic view. About
the only
uniquely scenic out in southwest Sarpy is the braided
Platte River.
Viewshed has become one of the
most important functions in this project.
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Cost Weighted
Cost weighted
finds the
least accumulative cost from each cell to the nearest or cheapest
source.
In this case, I-80 is the source and the elevation is the
cost factor.
A developer
does not want to spend too much money on building far from the
interstate and elevation
would
be the made hurtle. Notice the
affect that
the Platte has over the cost. Where the
floodplain is
the cost stays low, while is quickly goes up in the hilly areas.
After using those Spatial Analyst functions I had five new datasets.
However, all five of them need to be reclassified. The process of
reclassifying data is to ensure the program knows what values in the datasets
have more meaning. This is done by looking at each dataset and ordering
most important (10) to least (1). Landuse was order from forest being the
best place to put a park to urban which is the last place to build. The
I-80 and Platte River viewshed were ordered so that any area that can be seen
from the respected spot was a 10, and not seen was a 1. Slope was
reclassified so that the green shades had higher priorities than the red.
And the cost from I-80 dataset was reclassified so that the lighter colors (less
cost) were better than the dark.
Landuse I-80
View Platte View
Slope I-80 Cost
Once the reclassifications were complete, I used the Raster Calculator function
to calculate what the program thinks is the best spots for the amusement park.
The Raster Calculator function takes any raster datasets and performs Map
Algebra on each set to come up with a solution. I had to choose what
factors were most important to perform this task. Keep in mind these
numbers are arbitrary, there many be other factors involved in deciding. I decided that the view
from the Platte River was the greatest factor, while the landuse was not as big
of a factor considering must land in the region is crop land. The
following was the breakdown:
Platte View 40%
I-80 View
20%
Slope 20%
I-80 Cost
15%
Landuse
5%
Best
Locations
After performing the
calculations, the program came up with best locations for the park. Light
values are best areas for the parks, while dark areas are not good places.
I have highlighted three area that could possibly work.
Narrowing the Options
Location #1
At first
glance this location looks to be the best area out of the three. It has a
large flat
area, and it is
close to I-80 and the Platte River. However, that
whole area is
a FEMA floodplain. So building here
might be a mistake if the area was to
be hit with a flood.
Location #2
This spot
seems alright.
It is close to
an exit off the interstate, and has a good I-80 view. But, the area is
too
small to develop a 200 acre
park and the
slope is a little too intense for a amusement park.
Location #3
The last spot has got it all. It has a great I-80 and Platte view and it
is close to Exit 432 so there is quick
access to the park. It is also
close to the
small
town of Melia, which could benefit with
restaurants and
hotels. The location looks like it might be on the
floodplain;
however, there
is a 20 foot difference in
elevation from the FEMA floodplain and the parks
purposed location.
Final Layout