Assessing Gentrification, Displacement, and Patterns of Environmental Inequity Surrounding Light Rail Stations, Bus Stops, and Transit Deserts

My dissertation examines the spatial and temporal aspects of transportation inequality in urbanized areas across the United States. I bring together literature in urban sociology and environmental justice to better understand the relationship between gentrification, residential displacement, and transit systems. Transportation inequality has been a feature of urban areas in the U.S. since the birth of the highway system. Middle class whites fled to the suburbs and enjoyed automobile-based transportation, while the poor and racial minorities were left behind in cities with inadequate and underfunded urban bus systems. However, the growth of the new urban middle class in late twentieth and twenty-first century is changing the nature of transit-based segregation. Rather than bringing reinvestment into the city as a whole and encouraging the ideal of a multicultural, multiclass city, the return of the white middle-class to the central city has tended to create a new chapter in the saga of geographical apartheid, transportation racism, and spatialized inequality. Some studies have recognized that gentrification and displacement of low income residents has been facilitated by new forms of transportation, such as light rail transit (LRT), that has made it easy for the new urban middle-class to move freely about the city without the constraints of urban traffic that has plagued bus systems. I expand on those previous studies in two ways. First, using insights from critical environmental justice theory, I argue that transit related gentrification from LRT should be studied through the lens of race as well as class and should include measures of racial displacement. Second, I examine whether LRT development leads to the displacement minority residents, and subsequently, the growth of minority populations surrounding dirtier forms of transit, such as bus systems as well as in transit deserts, using a series of spatial autoregressive models.