Introduction: The
question I posed for this lab was which town in Lane County would be the best
environment to create a home near recreation? My objectives are to maximize the
accessibility to nature as well as well as minimize large amounts of traffic
from cars and people. Specifically, I focused on the parameters for proximity
to be at least thirty miles away from interstates, a mile or less from water
bodies and state parks, with a town population less than or equal to 7,000
citizens. My intended audience is simply people who desire a connection to the
natural world; perhaps to people who wish for a place to escape or would simply
enjoy a quieter lifestyle.
Data Sources: For
this particular question, I was able to use the data within the ArcGIS program
under the Oregon file. My main concern for this project’s data is the age of
the population data. It has been over four years since the last population
survey was taken, and much could have happened within this time, therefore
possibly changing my results drastically. Another concern of mine is the
quality of water located near the town. My goal of this project was to
determine a recreation friendly place to live; the data simply shows that water
bodies exist there, but not necessarily if the water is swimmable and fishable.
Methods:
Objective One: Create
the Geospatial Basis for Lane County
This required me to connect the data from the ‘mgisdata’
folder to my computer. This folder contained all of the feature classes I used
in this project. From here I created a file geodatabase to hold all of my data
in order to easily locate it. Next I allocated Lane County as the county I
would focus on for the entirety of my project. This meant creating a new layer
by exporting the data solely for Lane County. I kept the original projection
for this county because it was already set to an Oregon projected coordinate
system.
Objective Two: Add
the Data and Create Parameters
For this step I added the feature classes for interstates,
cities, waterbodies, and parks. I then used to ‘cut’ tool to reduce those
feature classes to the size of Lane County, thereby speeding up the processing
time for the future.
My first parameter was selecting a town smaller than or
equal to 7,000 people. To execute this I queried the data under the ‘Select By
Attributes’ tab. I then created a new layer from these selected points and
deleted the regular ‘cities’ feature class.
My next desired limitation for the data of my project was to
ensure that whatever town was desirable had a water body within one mile. To do
this I created a one-mile buffer on the feature class. In addition, I utilized
the dissolve tool to unify the lines amongst the buffer.
Next I wanted to also create a one-mile buffer around State
Parks to ensure close proximity to the Great Outdoors. To do this I needed to
query NAME LIKE ‘%State Park%’ from the parks feature class to reduce
the type of park considered in my project. After creating the State Parks layer
I created a one-mile buffer around that as well.
Finally, I wanted to make for a less trafficked town by
eliminating close proximity to the interstate. To do this I created a thirty-mile
buffer and then proceeded to use the erase tool to create a zone at least
thirty miles away from the interstate.
To connect the entire project together I used the intersect
tool to create an input of the buffered layers: water bodies and state parks;
the queried less than or equal to 7,000 people layer, and the erased thirty
mile zone around the interstate. This resulted in the determination that Dunes
City was the optimum place to build.
Objective Three:
Create a Cartographically Pleasing Map
To clean up my map I made sure that all of the layers were
appropriately placed so they could all be viewed at the same time. This meant
that I made the county layer ‘hollow’ to make sure that it was clear to the
viewers. I only included the buffered zones of each parameter that I set up to
make the map easier to view. In addition, I created a legend labeling all of
the final results in a user-friendly manner. I also thought that it would be
helpful to label the cities with less than 7,000 people so I did that, while specifically
highlighting Dunes City with a star. In addition to creating the initial map of
the county, I also added another frame with the exact same data to be able to
additionally zoom in on Dunes City to see the lay of the land enlarged. I
created a third frame as a locator map to show were Lane County was located in
proximity to the rest of Oregon. I added a North Arrow as well as two scale
bars (one for Lane County and the other for Dunes City) to get a better idea of
the size of the areas mapped.
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| Data Flow Model for Lab 5 Parameters |
Results: The
final outcome of this project was determining that Dunes City, Oregon is a very
good place to build a home in close proximity to water, state parks, and away
from the interstate. Additionally, the small size of this town would allow for
a quiet place to live, which is often appreciated by those who love the
outdoors. This area was determined by using the intersect tool to connect all
of the parameters.
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| Final Lab 5 Map |
Evaluation: I
truly enjoyed working on this project. It allowed me to utilize the tools I had
learned throughout the course and apply it to something relevant and
interesting to me. I faced few challenges, but the most bothersome was the
difficultly in querying the parks data to just represent state parks. Through
much trial and error, this was finally managed. If I redid this project I think
I would have looked into more data from the county itself. This would have
given me more specific feature classes to look at. Additionally, I would have
selected an area of the county rather than a city to create a cabin, which
would provide more privacy than the city limits.
Source: ESRI
Software
