Gentrification in Charlotte: A Tale of Urban Redevelopment

Gentrification research almost exclusively focuses on traditional postindustrial cities. Despite a growing number of scholars emphasizing the importance of understanding gentrification outside of traditional urban areas, its presence and modalities in mid-sized cities remains underexplored. This holds particularly true in the U.S. South where unique historical processes of industrialization, segregation, and immigration form low-density spatial patterns of urbanization that set Southern cities apart from other U.S. regions. A group of rapidly emerging mid-size U.S. Sunbelt cities – known as the New South – share concerns over a number of converging and interrelated trends: urban core revitalization, rising housing costs, lagging economic mobility, investing in public infrastructure, and shifting demographics. In this context, the New South is an ideal region for investigating longitudinal neighborhood development trends within a gentrification framework. Using a case study approach in Charlotte, my dissertation explores the spatial, temporal, and spatial-temporal aspects of contemporary gentrification. A survival analysis also tests the relationships between gentrification and changes in housing renovation, urban amenities, proximity to light rail development, and other factors. Results reveal that administrative data at the parcel level is more precise at pinpointing where gentrification occurs and how it diffuses overtime. Findings also identify substantial differences between area estimates of gentrification hot spots calculated from parcel data, demonstrating that spatial aggregation error may lead to significant errors in measuring gentrification. Findings suggest that aggregating data to census blocks or tax parcel spatial unit provide more precise measurements of gentrification. Key findings from the survival analysis identify that neighborhood parks and greenways increase the likelihood of gentrification. Results also highlight a strong spatial effect, demonstrating that neighborhood effects do influence spatial patterns of gentrification. Unexpectedly, light rail variables do not increase the likelihood of gentrification. Additional variables that increase the likelihood of gentrification include parcels with older homes, parcels in and around historical areas, lower home values per square foot, proximity to quality education, proximity to highways, and proximity to commercial areas increase the likelihood of gentrification. Thus, at a time when urban areas are rapidly changing and considering how to accommodate future growth, a local level understanding of gentrification aids policy makers and community organizers to tailor more effective public policy.