Community and Regional Planning Program


Date of this Version

Spring 4-22-2014


Aftika, Sarah. 2014. GIS Spatial Analysis of Segregation Clustering Evolution in Lincoln, Nebraska. MCRP Thesis. University of Nebraska-Lincoln.


A THESIS, Presented to the Faculty of, The Graduate College at University of Nebraska, in partial fulfillment of requirements, for the Degree of Master of Community and Regional Planning, Major: Community and Regional Planning, under the supervision of Professor Yunwoo Nam, Lincoln, Nebraska, April, 2014.

Copyright 2014 Sarah Aftika.


Rising immigration growth in the Midwest creates Multi-racial communities and segregation such as social class segregation, economic segregation, education segregation, and also housing segregation. In urban America, there are three major sets of explanatory causal factors that have been hypothesized to explain ethnic residential segregation. They are: housing discrimination, socioeconomic status (SES) and ethnic group preferences (French 2008, 1).

Lincoln, as a metro city in Nebraska, shows signs of segregation phenomena as well as other metro cities in Midwest. The analysis tool used for this study is Geographic Information System (GIS) spatial analysis. This tool enables us to examine the segregation clustering in Lincoln by using Weighted Overlay Spatial Analysis. Multivariable that will use to overlay are including segregation variables (economic segregation, social segregation, education segregation) and housing quality variables (median housing value and year structure built).

We know that houses with structures older than 30 years may be the locations for problems such as injuries, and sometimes death caused by falls, fire and burns, also suffocation and strangulation, elevated lead levels, mental health, structural deficiencies and accessibility. Segregated neighborhoods, which are dominated by middle to low income communities, will have difficulties to solve those. Combining all segregation topics and housing quality special characteristics to analyze, the variables will be united for this study.

The analysis of residential housing segregation, will take time series data to see cluster pattern evolution. Census bureau data every ten years since 1990, 2000, and 2010 will be used for the segregation time series analysis. The change of pattern every ten years expected to give some hint of the change in residential housing segregation direction. Expected results are segregated neighborhoods clustering is still exist but reducing. In the future, conducting the segregation clustering research by examine the power of cluster is a bright idea.

Adviser: Yunwoo Nam