The main objective for lab three is to continue practicing
GIS and standalone data that can be used for analysis in a GIS project. The lab
focused on converting standalone tables containing data into an attribute table
that can be mapped and then exercised manipulating the U.S. Census Bureau’s
website to acquire information to be used in a GIS.
The U.S.
Census Bureau website is first introduced and the mission of the bureau is to
serve as the leading source of quality data about the nation’s people and
economy. The data collected is used to regulate the distribution of
Congressional seats to states, make decisions about what community services to
provide as well as distributing $400 billion dollars in federal funds. Downloading
the 2010 U.S. Census of Wisconsin by county is our first task followed by
downloading the Wisconsin shapefile, which is also obtained from the website.
Once the downloading and saving was complete modifications to the Excel
spreadsheet involving Wisconsin’s counties population were made. Deleting an
unneeded record, adjusting the population field’s decimal places, formatting the
population field to numbers instead of text and finally saving the spreadsheet
as an Excel workbook, which ultimately made it possible to add to ArcMap. Tying
the Wisconsin shapefile and the spreadsheet together is the next task. The
process used to combine the two is called the join technique. This technique
helps link the census data and the shapefile into one attribute table. After
applying the join method the data is now ready to be projected. Under
symbology’s quantities graduated colors the selected value is population, which
displays the most common used color ramp for population ranging from red
(highest in density) to light yellow (lowest).
The classification method used is defined interval with five classes. I
chose this classification method because I thought it best represented the distribution
of population by county in Wisconsin.
The next
objective is to project data of our choice onto the Wisconsin county shapefile.
Housing units was my selected variable. Following the same steps from the map
created before I only changed the joining process. The joining process involved
tying Wisconsin’s housing units and the population data table into the county’s
shapefile. Once the joining technique was finished projecting the data was next
on the list of steps. The map displays the population, which is divided by the
number of housing units. I found this projection unique because the number of
housing units in the northern counties exceeds the population. The data is
projected this way because of the number of cabins present in the north. The
classification method used is geometric interval. Once the maps were complete
the essential elements of map design were added to ensure the viewer has a well
understanding of the goal expressed.
Downloading
and mapping GIS data is an extremely important skill. I can now use data from a
source outside of ArcMap. I’ve learned to convert along with join data tables
as well as import shapefiles to project my data selected.
American FactFinder. (2015, January 6). Retrieved March 12, 2015, from http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml
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