Urban Inequality: Combining Sociodemographic, Zoning, and Engineering Development Data to Plan More Equitable Designs
Open Access
Author:
Lenze, Victoria
Area of Honors:
Mechanical Engineering
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
Caitlin A Grady, Thesis Supervisor Daniel Humberto Cortes Correales, Thesis Honors Advisor Jessica Dolores Menold, Faculty Reader
Keywords:
Redlining Pittsburgh Spatial Data Mapping Principal Component Analysis Zoning Variance Social Vulnerability
Abstract:
Historic injustices due to racial discrimination, redlining, and unequitable zoning practices have led to urban inequalities in the United States. These inequalities have been compounded by a lack of consideration for how infrastructure, industrial projects, and planned zoning impact nearby low-income and minority populations. Industrial processes near residential areas have several health impacts and have historically been in closer proximity to minority and low-income neighborhoods. To investigate whether zoning plays a role in this process or if there are spatial patterns we can uncover to promote a more equitable future, we study zoning variance data in the city of Pittsburgh, Pennsylvania. Using principal component analyses and regression analyses, we showcase statistical correlations between sociodemographic characteristics and zoning variance data. A number of relationships reflect statistical significance while the overall results highlight potential future areas of research. Using ArcGIS, we display these relationships spatially, showcasing potential designs and directions for future equitable maps for urban designers and engineers. Our work combining data sets with spatially explicit statistical analysis has the potential to equip decision makers with future tools necessary to account for inequalities and create more equitable solutions in the future.
