Date of Award
Master of Science (MS)
Local transit accessibility--Ala.bama--Huntsville, Local transit--Ala.bama--Huntsville--Planning
This study aims to investigate the accessibility of public transit within the City of Huntsville, Alabama, in Madison County. Accessibility, in this context, refers to the distance between the residents in a certain census tract to essential amenities such as hospitals, schools, parks, workplaces, and other necessary services using public transportation. Data were obtained from the US Census Bureau and the City of Huntsville's Data Depot, focusing on aspects such as population socio-demographic attributes, and the distribution of essential amenities within the Huntsville city. Utilizing a range of Geographic Information System (GIS) methodologies and tools, including proximity analysis, random forest regression analysis, and optimized hot spot analysis, this thesis evaluates distance-based transit accessibility in comprehensive ways. Proximity analysis evaluates the distance from transit stops to places. Random forest regression analysis selects various key socio-demographic variables and evaluates the correlation among transit accessibility and such variables. Optimized hot spot analysis identifies areas with high and low transit accessibility. The combination of these methodologies and tools reveals various sociodemographic factors correlating to transit accessibility. Further, this study suggests that public transit accessibility within Huntsville is heterogeneous spatially. South Huntsville, Harvest, Mountain Cove, and New Hope areas are among the regions lacking transit accessibility. This research provides insight from the perspective of distance-based transit accessibility for transit planning decisions and potentially helps the public transportation services in Huntsville become more comprehensive and equitable for the diverse needs of the residents.
Shivashankar, Sachin, "Assessment of public transit and access to essential services and facilities in Huntsville, Alabama" (2023). Theses. 500.