Identifying clusters of public transit unreliability through an equity lens using GIS: A study of Winnipeg, Manitoba, Canada
Abstract
This thesis investigates the clusters of public transit service unreliability using GIS techniques through an equity lens. In the first study, I analyzed transit on-time performance and pass-up records in the city of Winnipeg, Manitoba, Canada, using spatial scan statistics and identified clusters of high- and low-risk areas for unreliable transit services such as delays and early arrivals. I also discovered that high-risk clusters are associated with socio-economically disadvantaged neighbourhoods, suggesting evidence of transport inequality in service reliability. In the second study, I analyzed the spatio-temporal patterns of pass-ups during the COVID-19 pandemic in Winnipeg using emerging hot spot analysis. I found hot spots in the central and southern parts of the city, which coincide with low-income neighbourhoods. This finding suggests that socially disadvantaged neighbourhoods might experience inequality in terms of unreliable transit services, and this issue further worsened and persisted during the pandemic. Transit providers and city leaders could benefit from utilizing these methods to evaluate and improve transit services, making them more equitable for the populations that need them the most.