Urban Economics
GIS Project (30 points)
Fall 2019
Due: Last class (Wednesday, December 11, 2019)
Please find the shapefile and economic data of a region that interests you. Use
the value of an economic variable to rank the geographic units in the region.
Let’s call this variable X. Pinpoint the geographic unit with the largest X value.
Suppose this geographic unit is town A. Produce a map that shows the region,
where the focus (i.e., center of the map) is on town A. Town A should be in a
different color from others. The map should have title, scale and a north arrow.
Integrate the X variable to your shapefile. At the end, write a short paragraph
that describes: (1) what is your variable X, (2) where is the region and which
town is town A, and (3) your data sources.
Example: The region of interest is Lowell and the 10 towns nearby. The
variable of interest is average household income. Among these 11 towns, the one
with the highest average household income is Carlisle. The map will be about
these 11 towns, where Carlisle is in red while other 10 towns are in green. In the
attribute table of the shapefile, there is a column (field) where the average
household income of all the 11 towns is given.
Please be advised that you have to finish the project on time. You may not
be able find the shapefile and economic data for your dream city in just a few
weeks. Choose X and A that have good data availability. The project is, after all,
for demonstrating your basic GIS skills.
On the due date, please bring the following three electronic files with a
memory stick:
1. An image file (pdf or jpg): your map;
2. A zip file that includes your shapefile and supporting files;
3. A text file (pdf, doc, or txt): the description mentioned above.
I will bring my laptop to collect your files. Please make sure that the shapefile
and supporting files can be opened on a different computer.
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Grading criterion:
1. Image file: a clear map of the region (10 points);
2. Image file: a “town A” correctly colored (4 points);
3. Image file: title, scale, and a north arrow (3 points);
4. Shapefile: the shapefile can be successfully loaded (3 points);
5. Shapefile: the attribute table of the shapefile has the “X” column (4
points);
6. Text file: the text file gives a clear description of (4 points)
• The region, • The “town A”, • The “variable X”, • Data sources;
7. Overall: well implemented and urban related (2 points).
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