Introduction
Where is the safest place to live on the west coast? People
moving to the west coast may be asking themselves this, because it is a region
that is located within the ring of fire on the edge of the Pacific plate. This
region is known for its intense tectonic plate movement causing many
earthquakes and volcanoes to form. To guarantee safety, I have created a map
showing areas of the west coast that are at least 50 kilometers away from any
volcano and/or earthquake site. I have also included smaller areas within these
safe areas that show places within 20 kilometers of a hospital. I would like
this map to help people that are moving to Washington, Oregon or California to
find the safest place to live according to the sites of volcanoes and earthquakes.
This map may also be used for insurance purposes, and a reference for
building/company safety codes and regulations.
Data Sources
To answer my geographic research question I obtained the
volcano and earthquake feature class data from the “Mastering ArcGIS”
geodatabase (mgis.gdb). I then also obtained the hospital data from the ESRI census
geodatabase (Esri2013.DBO.USACensus). I do have some data concerns with my project such as the scale; it
may be too small to really showcase the regions I wanted to emphasize. Also is
the data frame in an appropriate projected coordinate system? There are always
many coordinate systems that may be appropriate but I hope the North American Equidistant Conic
portrays the data in a sufficient manner.
Methods
To get started with this project I first added a States map
and a counties map from the mgis geodatabase, selected the states Washington,
Oregon and California via select by attributes and created a layer of these
selected features and named it States_of_interest I did the same step for the
counties layer and named it Counties_of_interest. I then deleted the layer
containing the entire United States. I proceeded to add the volcano layer and
earthquake layer and clipped those by the states of interest to only focus on
the volcanoes and earthquakes within Washington, Oregon and California; these
layers were named volcanoes_clipped and earthquakes_clipped. Next I added the
hospital layer from the census geodatabase and also clipped this layer by the
states of interest.
Now all data points lie within Washington, Oregon and
California. The next step was to buffer the earthquakes_clipped layer and the
volcanoes_clipped layer. I made the buffer 50 kilometers around the points and
created the layers Distance_from_Volcanoes and Distance_from_Earthquakes. I
then used the union tool to bring these two buffered layers together and called
it Distance_from_Volcanoes_and_Earthquakes. Next I used the erase tool to
“punch out” the buffered layers from the Counties_of_interest to clearly see
the areas that were considered safe, and named this layer Safe_Distance2.
Once I had my safe distance from both the volcanoes and
earthquakes I started applying tools to the hospitals_clipped layer. I first
buffered it for 10 kilometers and realized this was not a sufficient buffer. I
then buffered it again for 20 kilometers and was much happier with the results.
I then took the buffered hospital layer and intersected it with the
Safe_Distance2 layer. I wanted to show areas that were within 20 kilometers of
a hospital that were also in the area declared safe. This is how I obtained my
answer of areas Near_hospitals_and_Safe.
Figure 1: Data flow Model of how I obtained my answer of areas near hospitals and also in the safe area.
Results
As you can see from the map, the safety buffer covers much of the area. The green area shows regions considered safe on the west coast, and the smaller yellow areas depict places that are within 20 kilometers of a hospital and in the safe area. These places are the most ideal places to live on the west coast but green areas will do as well.
Figure 2: Map of West coast depicting safe areas to live.
Evaluation
I like that our final project was mostly independent. It allowed us to use the skills we have been learning the entire semester and really tested our knowledge. I am grateful that Professor C. Hupy checked and graded our data flow model before we started so we could get started on the right track. If asked to repeat this project there may have been a couple things I would have changed. I would have liked to include crime data, but that was not a part of the preapproved data making it more difficult to include. I also would maybe focus on one of the states Washington, Oregon or California; I think right now the map may look too overwhelming. Also next time I may ask a geographical research question that is biology related, since that is the field I am majoring in and hope to work for the Minnesota DNR one day. There were a few challenges I faced during this project such as saving my data to the Q drive, a very simple but easy to forget task. I had to go back a few times and redo some of my tasks to make sure they were in the correct folder. I also created some buffers that were not to my liking, so I had to play around with that a little. Overall this was a great project to do, I really feel like I have a handle on the GIS tools.
