Massachusetts Institute of Technology
Department of Urban Studies and Planning
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11.188: Urban Planning and Social Science
Laboratory
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11.205: Introduction to Spatial Analysis
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In-Lab TEST - April 6, 2020
Test
Instructions
- This test starts at the 2:35 PM. You 24 hours
to finish, even though it is the same test for which we had planned
2.5 hours in lab. Any Stellar submissions tagged after 2:30 pm on
April 7 will be marked as late. Please do not stay up all
night working on the test. The 24 hours is needed to
accommodate your classmates spread across the globe in many time
zones. Given all that is happening (and P/NE grading this semester),
do not lose sleep because of this test.
- This is an open-book, open-note test. However,
do not contact any "live" non-staff person via electronic or other
means while you take this test. We will be in our zoom classroom
during classtime. If you have questions, we can address
them privately in a zoom breakout room. Otherwise, you can
post them on piazza or email the two of us.
- Please create your answers in electronic
format - just as you have for lab assignments - and save your work
on your personal computer (or on a USB drive, one-drive, etc.). You
can edit your answers directly into your copy of this test if you
have an HTML editor. For your convenience we have also provided
MS-Word and PDF versions of the test in case you find these formats
easier to use.
- Even where we don't require an explanation,
you may want to say a few words about what you did so that you
can get partial credit if some of your numerical answers
and names are incorrect but your method has merit.
- Turn in your test (both the text and the PDF
exports of your maps) by uploading your answer documents to Stellar
(just as you have done for homework). If you wish, you may open the
answer sheet in MS-Word and include your PDF images within your
answer sheet as a single document.
- Remember
to turn in your test before logging out and check to be sure that
Stellar has uploaded it successfully. We strongly recommend that
you retain the file containing your answers until we return the
graded exams to you.
- Make sure to include your name and Athena user
ID near the beginning of each document that you turn in.
- Finally,
don't spend all your time on one or two questions. Start by looking over all the questions to get
a general sense of what, and how much, is being asked, and the grade
points associated with each question--then start work on your
answers. Move on to the next question if you've spent more than 10
minutes on any short answer question; mapping questions will likely
take longer.
Good
luck!
Datasets
for
the Test
For this test, we will use US county-level
data from the November 2016, US presidential election (between
Donald Trump and Hillary Clinton).. The relevant data for the test
is bundled together in a folder called test20data
in the AFS class locker. The
folder is also compressed into a 'zip' file called, test20data.zip,
in our '11.188 2020 DATA' Dropbox
folder. Copy test20data.zip
to a writeable space on your local drive (e.g., C:\TEMP) and extract all its files into a local folder:
C\temp\test20data.
Look into your local copy of test20data for
an ArcMap document called 11.188_test20_start.mxd
that has already included some of the shapefiles and tables that you
will need. This ArcMap Document utilizes one new Metropolitan
Statistical Area shapefile from the US Census plus several
shapefiles that were obtained from the MIT Library Geodata
Repository and then projected to a North_America_Albers_Equal_Area_Conic
projection (NAD 1983) projection (in meters). (The standard EPSG
code for this coordinate system is 102008 so I have included it in
the shapefile names, but you will not need to use this fact.) For
each of these shapefile, only the contiguous 48 United States were
saved (the "lower 48").
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Filename
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Description
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us_a1city_2000_lower48
_epsg102008.shp
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Point
feature shapefile showing the location of major US cities
(within the lower 48 states) having 2000 US Census
population of at least 50,000.
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us_f7states_2006_lower48
_epsg102008.shp
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Polygon feature shapefile showing state boundaries for the
lower 48 states.
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us_e25msa_2010_lower48
_epsg102008.shp
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Polygon
feature shapefile from US Census Bureau of the US 2010
Census boundaries of metropolitan statistical areas
(MSAs). The original shapefile has been limited to the
lower 48 states and projected to the EPSG=102008
coordinate system.
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us_f7counties_1996_lower48
_epsg102008.shp
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Polygon feature shapefile
from US Census Bureau of the 1996 County boundaries within
the lower 48 states together with the state, county name,
Federal Information Processing Standard code (FIPS), and
estimated 1990 and 1996 population.
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2016_US_County_Level
_Presidential_Results.csv
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(Optional) A
comma-separate-value (CSV) text file containing the 2016 US
Presidential Election results by County showing the votes for
Donald Trump and Hillary Clinton, the total votes, the
percentage of votes for these two candidates, the difference
in votes, and the percentage point difference in their
votes. The same data are duplicated within the personal
geodatabase (below) in the election16_county table so you do
not need to use this CSV file. |
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election16.mdb
(for use with ArcGIS)
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An MS-Access database (that is accessible from ArcMap as a
personal geodatabase) containing two key tables: (1) election16_county with county-level
presidential election results and a few 5-year 2015 ACS
census variables, and (2) election16_county_data_dictionary
explaining the meaning of each field in election16_county.
The rest of the tables (GDB...) are extra geodatabase tables
that ArcMap utilizes.
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election16_county.xlsx
(for use with QGIS)
election16_county_meta.xlsx
(for use with QGIS) |
Spreadsheet with County level 2016 presidential election
results plus a few 5-year 2015 ACS census variables
data dictionary for columns in election16_county.csv |
Within the
ArcMap document, 11.188_test20_start.mxd, the several state, county, MSA, and city
shapefiles have already been added. The counties are shown
thematically using the default (Jenks Natural Breaks) classification
broken into 10 categories based on the 1996 population of each
county. The county boundaries are omitted in order to avoid map
clutter and make the map more readable. Data are shown for the 3111
counties in the lower 48 states.
In addition to the shapefiles, spreadsheet,
CSV file,, and ArcMap document, the test20data folder also
contains an MS-Access database, election16.mdb, with the
ELECTION16_COUNTY table of
county-level presidential election results along with selected
census data extracted from the 5-year 2015 ACS census. For your information, the MS-Access database
also contains a data-dictionary, election16_county_meta,
explaining the columns in the election16_county table. Even if
you do not have MS-Access installed on your local machine, you may
connect to these tables from ArcMap.
The 2016 election dataset was obtained from
https://github.com/tonmcg/County_Level_Election_Results_12-16.
Portions of the CSV file with election data were then imported into
MS-Access and joined with ACS census data to produce ELECTION16_COUNTY.
The 5-year 2015 ACS census data included with the election data come
from the S1701 table on Poverty Status and the S2301 table on
Employment and have been downloaded from the ACS website: https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=bkmk.
In
addition, we have added population counts for years 2000 and 2010
to the MSA shapefile, us_e25msa_2010_lower48_epsg102008.shp. These
population data were obtained from an Excel spreadsheet downloaded
from: https://www.census.gov/population/www/cen2010/cph-t/cph-t-7.html.
[In order to join the population
data for Los Angeles with the most similar shapefile polygon, we
had to change the CBSA_code for Los Angeles-Long_Beach-Santa_Ana
from 31100 to 31080 (Los_Angeles-Long_Beach-Anaheim). This editing
issue is not relevant for the test.]
Part
I: Short Queries (32 Points)
Question
I-1
(28 points total, 4 points each part) - Queries
of election16_county
- Which county had the largest number of votes
for Donald Trump? fips = _________, County name = _______________.
- How many votes did Trump get in that county:
______________? How many votes did Clinton get in that county:
____________?
- How many counties are there in Michigan?
________________
- How many of the Michigan counties favored
Clinton over Trump? ______________
- Among all Michigan counties, which county had
the largest vote difference (positive or negative) between Trump and
Clinton? What was the vote difference in this county? diff =
__________, fips = ___________.
- What is the smallest total number of votes
received by Hillary Clinton in any one of the 48 US states
(plus the District of Columbia) ?
_________ State = ____________ ?
- How many votes did Trump receive in that state?
________________ State = ____________ ?
Question
I-2
(4 points total, 2 points each) - Queries of
us_a1city_2000_lower48_epsg102008.shp
- How many cities in the shapefile have a reported population (POP)
greater than 250000: __________?
- What is the 8th largest city: Name = ____________, POP =
______________?
Part
II: Mapping Concepts (6 Points)
Question
II-1 (6 points total, 3 points each)
When you open the
map document, the county map is displayed using a North_America_Albers_Equal_Area_Conic
projection (NAD 1983) rather than in geographic lattitude-longitude
coordinates. As we know, local planning agencies typically use
projected coordinate systems. For example, the MassGIS
mapfiles that we have used are generally
saved in the Massachusetts (mainland) State Plane coordinate system.
Part II-1a
(3 points): Suppose we
were to view the same US County map in lattitude-longitude
coordinates. Would the size of Washington state (in the northwest
corner) appear to be larger, smaller, or the same relative to the size
of Florida? Explain Briefly. [Note: Feel free to change the coordinate
system to see the results. However, there is no need to change the
coordinate system and submit a map. You need only provide a brief
answer and explanation.]
Part II-1b
(3 points): Now
suppose we were to view the same US County map in the Massachusetts
(mainland) State Plane projection. Would the map be rotated clockwise
or counter-clockwise relative to the original orientation when you
opened the ArcMap document? Explain Briefly. [Notes: there is no need
to change the coordinate system and submit a map. You need only
provide a brief answer and explanation.]
Part
III: Election Map (30 Points)
Let's develop a chloropleth map showing the percentage of votes for
Donald Trump in each county. Add the election16_county
table to ArcMap, join it to the shapefile of 'lower-48' counties and
design your map. Note that election16_county
lists the county FIPS code as text (field= fips_txt) as well as an
integer (field=combined_fips). We added the fips_txt field for your
convenience. It is not in the original CSV file. Be careful to select
the appropriate data type when you join the table to your shapefile.
There are 3139 records in election16_county
table and 3111 records in us_f7counties_1996_lower48_epsg102008.shp.
Note, that election16_county data is
missing from a few counties (such as Dade County, FL, fips12025) and
includes counties in states like Alaska and Hawaii that are not part
of the 'lower 48). So every row in election16_county
will *not* match a row in us_f7counties_1996_lower48_epsg102008.shp
and vice versa. After you join election16_county
to the shapefile, you should see 3105 non null values for the election
results among the lower-48 counties.
In addition, please notice that election16_county has many columns,
most of which are not needed for the test. We have made these
available just in case you want to explore this data beyond the test.
This may be interesting for some of you, depending on your research
interests.
Question
III-1 (14 points total)
MAP #1: Prepare and submit an ArcMap layout
of the counties within the lower 48 states and shade the counties
based on the percentage of votes that were for Donald Trump. Be sure
to:
- Include the outline of the States, and the usual scale bar,
source, legend, north arrow, and an appropriate title,
- Indicate your choice of classification method,
- Overlay a proportional point map of major cities (in the
us_a1city_2000_lower48_epsg102008 shapefile) with the size of the
city 'point' proportional to the population of the city. Only
include cities that have POP >- 250000,
- Adjust color ramps, choice of background and foregound colors and
outline, etc. to improve the readability of the map
NOTE: This question is worth 15 points and provides an opportunity to
demonstrate the cartographic skill that you have developed.
Question
III-2 (6 points total)
Part III-2a (3 points): :Briefly
discuss your choice of classification scheme and number of categories
for your election results map.
Part III-2b (3 points): Briefly
discuss any spatial pattern that you observe in your map regarding
Trump's percentage of votes among the US counties.
Question
III-3 (10 points total)
Part III-3a (2 points):
What is average (mean) value of the percentage of votes for Trump
(per_gop) among all those 'lower 48' counties for which you have the
voting results joined to your map:: _____________?
Part III-3b (4 points):
Select those counties that contain the cities that have
POP>=250000. How many counties are selected: ___________? What is
the average (mean) value of the percentage of votes for Trump
(per_gop) among these counties with the big cities: _____________?
Part III-3c (4 points):
Using the county-level ACS census data joined to your county
shapefile, determine the average (mean) percentage of persons below
the poverty level (pct_below_pov) for those counties containing the
larger cities ___________ and for those counties outside the larger
cities ______________.
Part
IV: Proximity to Big Cities and Metro Areas (32 Points)
Next, let's examine the presidential voting pattern for counties in
and around the larger cities.
Question IV-1 (6 points total)
Create a buffer of 50 km radius around the cities with
POP>=250000. Select all the counties that intersect your buffer. In
particular, select the counties that have their centroid within your
buffered large cities.
Part IV-1a (4 points): How many counties fall within your
buffered large cities: _____________? If, instead, your overlap
criteria were having any or all of the county area within your buffer,
how many counties would satisfy that criterion:
__________________?
Part IV-1b (2 points):
Among those counties with centroids within the large city buffer, what
is the total number of votes for each candidate (i.e., the sum of
votes_gop, and the sum of votes_dem): Trump votes: ____________, and
Clinton votes: ______________?
Question IV-2 (14 points total)
Part IV-2a (4 points): Based on the 2010 MSA
population (pop2010) field in the
us_e25msa_2010_lower48_epsg102008
shapefile, select those Metropolitan Statistical
Areas that had a population of more than one million persons. How many
MSAs met this criterion: _____________? Which MSA in this million-plus
group had the smallest population: fips_txt = ___________? and Name =
_______________________________?
Part IV-2b (2 points): Next, select those
'lower-48' counties that have their centroid
within those MSAs that have a population of one
million or more. How many counties meet this criterion:
_______________?
Part IV-2c (2 points): Among these counties that have
their centroid within the larger MSAs,
what is the average (mean) value of the percentage of votes for Trump
(per_gop): _______________? and for Clinton (per_dem): ______________?
Part IV-2d (2 points): Among those counties that have
their centroid within the larger MSAs,
what is the total number of votes for each candidate (i.e., the sum of
votes_gop, and the sum of votes_dem): Trump votes: ____________, and
Clinton votes: ______________?
Part IV-2e (4 points): Upon examining the last two
questions, we notice that the average vote percentage (in the counties
within the larger MSAs) is higher for Trump, but Part IV-2d shows that
Clinton earned more votes in total among those counties within the
larger MSAs. Explain briefly what is going on that allows this to
occur:
Question IV-3 (12 points)
MAP #2: Prepare and submit a second ArcMap layout of
the counties within the lower 48 states and once again shade the
counties based on the percentage of votes that were for Donald Trump.
This time, be sure to:
- Include the outline of the States, and the usual scale bar,
source, legend, north arrow, and an appropriate title,
- Indicate your choice of classification method,
- Overlay your 50 km buffer of the larger cities with enough
transparency to allow the chloropleth map to be visible underneath.
- Include only those counties that you associated with the larger
(million-plus population) MSAs and shade them using a hash pattern
so the chloropleth map is visible underneath.
- Adjust color ramps, choice of background and foregound colors and
outline, etc. to improve the readability of the map
- Instead of showing all 48 states, zoom in to an area in the
mid-west in order to see the details more clearly in that region.
For this purpose, consider the mid-west to (at least) include all of
Illinois, Ohio, Kentucky, and West Virginia.
That's all for the test, but feel free to
keep the election data and explore some of the election patterns
further when you have time. We do not have time on the test to
examine further the relationship between voting, demographics, and
health exchange participation and subsidies.
Please note:
- Before creating the PDFs, be sure to include
your name and Athena ID somewhere on the text file and the map
layouts
- You should test your PDF files with Adobe
Acrobat Reader before submitting them to Stellar in order to be sure
they are readable.
- You should keep a copy of your text output and
PDFs file in your Athena locker until your test is graded
- You should confirm with an instructor that
your test files were received.
Last modified 22 March 20021 for alternative use with QGIS.
(jf)
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