In this article we attempt to establish the connections between transit ridership and land use and socio-economic variables, and project future ridership under different scenarios. We subdivided the state of Maryland, USA into 1151 Statewide Modeling Zones and developed a set of variables for the base year (2000). We estimated multiple models of transit ridership - using ordinary least squares and spatial error modeling approaches - for the entire state. We also test for the determinants of ridership within urban, suburban and rural typologies. We find that land use type, transit accessibility, income, and density are strongly significant and robust predictors of transit ridership for the statewide and urban areas datasets. We also find that the determinants and their coefficients vary across urban, suburban and rural areas. Next we used a suite of econometric, land use and other models to generate two sets of future transit ridership scenarios under conditions of - (a) business as usual and (b) high energy price - for a 30-year horizon. We analyze these scenarios to demonstrate the value of our approach for state-level decision-making.
- Land use
- Transit ridership
ASJC Scopus subject areas
- Geography, Planning and Development
- Nature and Landscape Conservation
- Management, Monitoring, Policy and Law