A Case for Increased State Role in Transit Planning: Analyzing Land Use and Transit Ridership Connections Using Scenarios

Abstract

Land use and neighborhood characteristics have long been linked to transit ridership. Large-scale agencies, such as state departments of transportations, often make decisions that affect land use pattern and transit services. However, the interdependencies between them are seldom harnessed in decision-making. In this article, the authors develop and apply a transit ridership model based on land use and other neighborhood characteristics for an entire state, then discuss its implications for regional and state-level decision-making. The state of Maryland was chosen as the study area. Using a number of criteria, the authors subdivided the state into 1151 statewide modeling zones (SMZs) and, for each zone in the base year (2000), developed a set of variables, including developed land under different uses, population and employment densities, free-flow and congested speeds, current transport capacities, and accessibility to different transport modes. They estimated two sets of OLS-regression models for the base year data: one on the statewide SMZs dataset and other on subsets of urban, suburban and rural typologies. It was found that characteristics of land use, transit accessibility, income, and density are strongly significant and robust for the statewide and urban areas datasets. It was also found that determinants and their coefficients vary across urban, suburban and rural areas suggesting the need for finely tuned policy. Next the authors used a suite of econometric and land use models to generate two scenarios for the horizon year (2030) – business as usual and high-energy price – and estimated ridership changes between them. The resulting scenarios are used to show how demand could vary by parts of the state and demonstrate the framework’s value in large-scale decision-making.