Emilie Falguieres
Final assignment- project report
An overview of the project.
The objective of this project was to demonstrate how non-white population was
disproportionally affected by the construction of highways and highways interchanges in
the 1950s and 1960s. With the use of GIS I was able to quantify the proportion of
minorities versus the proportion of whites living in areas where construction of highways
network were pursued. Barbara Parmenter proposed me to work on this project. She
already had mapped the location of current highways on population of the 1950s.
Data:

Highways: Bureau of Transportation�on Statistics of the U.S government, ESRI,
vector, 2005,

US 1950 Census: Minnesota Population�on Center. National Historical
Geographic Information System: Version 2.0. Minneapolis, MN: University of
Minnesota 2011, http://www.nhgis.org, vector

Core Based Statistical Areas (CBSAs) for Metropolitan areas: United States
Census Bureau, February 2013, vector
Steps
I mapped the proportion of non-white population who were living in areas where
highways and interchanges were subsequently constructed in the 1950s and 1960s.
1. I started by doing an overlay of the 1950s census data on the CBSA metropolitan
area data in order to have the name of metropolitan areas on the attribute table.
2. I created an interchange data layer, using Network analyst
3. I calculated the total of non-white population as well as the total population in all
of the tracts in each metropolitan area.
4. I selected, using the select by location tool, the tracts that are intersecting an
highways all over the US. I selected the tracts that intersect 300 meters from the
interchange.
5. I then did the same calculation for the selected tracts as for all the tracts
6. I calculated the fractions of non-whites per metropolitan area using excel and the
fraction of non-whites in selected tracts in the metropolitan areas.

I calculated the difference between the fraction of non-white in selected
tracts and the fraction of non-white in the total tracts in order to see the
difference in percentage points

Barbara proposed to create an index dividing the two fractions. An index
inferior to one would show that the proportion of non-whites in the
selected tracts is inferior to the proportion of whites. An index superior to
1 would show that non-whites were disproportionally living in areas
targeted for the construction of highways and interchanges.
7. I decided to use the index instead of the difference between the fractions because
it presents a more clear demonstration of the proportion of racial groups.
8. I then joined the index tables to the attribute table of the metropolitan areas data
layer in order to create the two big maps.
The two smaller maps are a closer view of Dallas downtown and Detroit where we can
clearly see how highways were crossing black communities. I used the 1950s census data
for those maps as well as the junction layer and highway layer.
Limits
My first issue with this project is that we cannot locate clearly inside the tracts
where minorities communities where located. Tracts have very different shape and I was
sometimes obliged to select large tracts were populations were living probably far away
from the highways. Seconds, I could not figure out by myself a good way to present the
disproportion of racial groups living in affected areas. The fact that I am using
metropolitan areas from 2013 for the big map can be misleading because the tracts from
the 1950s cover much smaller areas. However they provide good visuals for mapping.
Conclusion and ideas
I believe this project was interesting and exciting, as it had never been done before. It
demonstrates a clear tendency for policy-makers to target certain areas for the
construction of highways. The project could have been more completed if I had given an
overall number for the United States of the probability of highways to be constructed
close to minorities’ communities. An analysis of the impact of highways on
communities’ livelihood would have also been interesting. I was surprised not to see
cities known for having that type of issue appearing in the maps such as Atlanta. The
subject is very interesting and should develop more research ideas. Indeed the
construction of highways has always created major changes in the population1.
1. Analyzing segregation
Some authors have found that highways were used for segregation2. We could use
GIS in order to demonstrate a potential pattern. We could first use the index of
dissimilarity to calculate the degree of segregation for a city and then calculate it 5 or 10
years after the construction of the highways.
1
Voss, Paul, R., Guangqing Chi, Highways and Population change, Rural Sociology,
2006, pp.33-58
2
Mohl, R.A., Race and space in the modern city: Interstate 95 and the Black community
in Miami, in A.R.Hirsch & R.A. Mohl(Eds.), Urban policy in twentieth-century America
(pp100-158). New Brunswick, NJ: Rutgers University Press
2. Change in the population:
The construction of highways forced thousands of people to live their house and move to
another part of the city. We could measure the change in racial configuration before and
after the construction of highways.
3. Low social class population:
Black communities were not the only one affected by the construction of highways. As it
is often a question of a community’s influence and power, blacks and poor whites were
often powerless to resist highways construction. We can use census data from the 1950s
or 1960s on income in order to create different categories of population from lowincome, middle-income to high-income. As I have done with the black population we can
then look at the proportion of low-income whites living in areas affected by the
construction of highways.
4. Regression analysis
Finally we could use regression analysis in order to assess the effect of black
communities on the construction of highways in the 1950s and 1960s.
Journal articles

Connerly, Charles E., From Racial Zoning to Community Empowerment
The Interstate Highway System and the African American Community in Birmingham,
Alabama, Journal of Planning Education and Research December 2002 22: 99-114,
http://jpe.sagepub.com/content/22/2/99.abstract
This article is interesting for the subject of highway building because it looks at how
highway constructions and racial zoning were used for segregation and expulsion of
communities. The author is using a map of Birmingham with racial zoning data, which
shows more efficiently than tract census the location of black communities, and highways
data to demonstrate his argument.

Chi Guangqing, Parisi, Domenico, Highway expansion effects on Urban racial
redistribution in the post-civil rights period, Public Works Management& Policy,
2011
http://www.academia.edu/1404899/Highway_Expansion_Effects_on_Urban_Racial_Redi
stribution_in_the_Post_Civil_Rights_Period
This research uses census data for 1970, 1980, 1990 and 2000 to examine the role
that highway expansion plays for the redistribution of black and latinos communities. The
paper looked at the communities in the metropolitan area of Milwaukee in the Wisconsin.
The interest here is not the result of the research, which demonstrates that the
concentration of Latinos and black communities have expanded after the construction of
highways. The paper used data for highway expansion segments and census tract.
They quantified the spatial relationship of census tracts to highway expansion segments.
They used a series of distance buffer zones to select the distance to highways and
therefore in order to express the potential exposure of highways. In this study the
researchers divided the census tracts into seven groups based on their distance to the
corresponding nearest expansion segments. They finally used regression analysis to
estimate the effect of highway expansion of urban racial redistribution.

Ritters Kurt H., Wickham, James D., How far to the nearest road?, Frontiers in
Ecology and the Environment, Vol.1, No.3, April 2003
http://www.jstor.org/stable/3867984
The project looks at the impact of road proximity on land areas. The authors
calculated the proportion of land area that is located within nine distances from the
nearest road and mapped the results. They use overlay tool with 4 different map showing
each different data. They created a gridded road map in which each cell recorded the
smallest window size that contained a road. Data summaries were prepared by overlaying
road-distance grid with land-cover, watershed and ecoregion maps. Finally they tabulated
the road distance. Note: I did not understand very clearly how they created the gridded
road map.

Mark Crowell, Kevin Coulton, Cheryl Johnson1, Jonathan Westcott, Doug
Bellomo, Scott Edelman, and Emily Hirsch, An Estimate of the U.S. Population
Living in 100-Year Coastal Flood Hazard Areas, Journal of Coastal Research,
Vol.26, No.2, 2010
In this project, the authors estimated the US population living in coastal area and that
is subjected to the 1% annual chance coastal flood.
They combined census data with the national digital flood hazard database and the
boundaries for two different zones.
The authors were able to determine U.S population subject to the 1 % annual chance
coastal flood. GIS unions were performed to spatially combine the coastal flood hazard
areas with census block groups. In order to determine the population within a coastal
flood zone, the authors multiplied the block-group population density by the square –mile
area of the coastal flood zone.

X. Ben Wu and Daniel Z. Sui, GIS based lacunarity analysis for assessing Urban
residential segregation, Texas A&M University, retrieved from:
http://proceedings.esri.com/library/userconf/proc02/pap0667/p0667.htm
The authors created a GIS procedure, using Arc view spatial analyst called multi-scale
lacunarity analysis for measuring segregation. This method allowed them to measure
different pattern of segregation. The lacunarity index is another method for measuring
segregation, different from the dissimilarity index. The authors used this index and
calculation as well as census data with census tracts converted to raster data, to measure
segregation in Houston between 1980 and 1990.