Goals and Background:
Before beginning this lab, I had accomplished
previous tutorials that taught me important information that pertained to this
lab as well as crucial information I would need in my later career. Prior
to completing this lab, I studied new knowledge from the last few
tutorials. These tutorials included types of attribute tables, database
management systems, joining and relating tables, cardinality, static and
dynamic maps, and how to make a cartographically pleasing map. The
goal of this lab was to use my new found experience to evaluate GIS data and
explore my critical thinking skills as I transformed and manipulated
information from the United States Census Bureau for my own use. As a result
of completing this lab in full, my work should be portrayed by the creation of
two static maps and one dynamic map. Both of which involve processes I
have learned thus far in the semester as well as new tasks I
would need to overcome to achieve my goals.
Methods:
In order to complete this lab, I began by
downloading and unzipping the 2010 SF1 100% Data from the United
States Census Bureau into my personal Lab_3 folder. At first I had
trouble with the data set, but that was resolved when I was informed how to
format data in my Excel Workbook data so that it could be used properly in
ArcMap. Once I overcame this minor struggle, I was able to join my
shapefile attribute table and stand alone table together by using the GEO#id
field ensuring a one-to-one cardinality. Here I chose
the field that the join would be based on and the table to join as
well as the field in that table to base the join. I had to be cautious
during this step to assure I was joining my source to my destination and not
vice versa.
Once all my data was correctly joined, I
exported it as a new layer and chose the symbology of my choice to represent
population size per county in Wisconsin. I did this by suggesting a value
and choosing a monochromatic graduated color so that the information was
precise and could be clearly interpreted by my audience. I then
repeated this task for the data of my choice- Housing Units. Finally I
developed two cartographically pleasing maps.
My next step involved making a dynamic map
which was fairly simple. I signed into ArcGIS online, edited information
in the Service Editor, published my map online. Once this was done, I
made slight changes to the Pop-up window and shared it with UW-Eau
Claire-Geography and Anthropology.
Results:
Figure 1 displays the final map I constructed
portraying the population size in each county in Wisconsin. The darker
color represents counties with a larger population and lighter shades
are counties with less population. From this, we can infer that south
eastern Wisconsin contains the most populated counties.
Figure 1: Above is a map of population size
per counties in Wisconsin.
Figure 2 shows the number of housing units in
each county in Wisconsin. Similar to that of the population map, the
darker shades of orange are counties with more housing units and the lighter
shades are those with fewer housing units. Therefore, we can attain
evidence that counties also in the south eastern part of Wisconsin contain the
most housing units. This seems logical considering the population in
these counties.
Figure 2: Above is a map showing the number
of housing units per county in Wisconsin.
Figure 3 displays the dynamic map I created
from my housing map shown in Figure 2. This map shows similar statistics
but when using it online, it can be helpful for the viewer because of its
interactive capabilities.
Figure 3: Shown above is a map displaying the
number of housing units per county in Wisconsin using a dynamic map.
Sources:
United States Census Bureau (2010)
[Download]. SQLServer.URL:
factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml [March 7, 2017].
