Equity Driven Data Analysis for Public Transportation Planning

Gerardo Ivan Valenzuela Mendoza, University of Texas at El Paso


Existing public transportation planning methods use a trip-based approach rather than a user-based approach; a user-based approach is sensitive to a broader range of planning strategies and policies, especially those that affect or take into consideration how users spend their time and resources. Even though transportation planning agencies such as Metropolitan Planning Organizations (MPOs) are required to strive for environmental and social justice, there is still a gap that needs to be filled. Urban population growth and urbanization with its impact on public planning require continuous research to address the constantly evolving challenges when it comes to transportation. As cities grow, questions related to equity, accessibility, and systems performance arise. Modern tools and techniques are available, allowing planners and decision-makers to visualize and compute the effects of the current systems as well as create scenarios for future decisions. The application of Geographic Information Systems (GIS) spatial analysis tools allows for the development of a system that can incorporate equity as well as demographic and environmental indicators into the planning process. Datasets for the analysis portion were retrieved from freely available governmental sources such as the United States Census Bureau and the Environmental Protection Agency (EPA). In addition, transportation data from General Transit Feed Specifications (GTFS) was also incorporated into the analysis for the transportation portion. The main objective of this study was to systematically consider the accessibility and coverage to public transportation during the planning phase. Due to the existing tools within ArcGIS Pro, the demographic and environmental indicators were combined with the transportation data to calculate coverage and accessibility for the public transportation system in the City of El Paso, Texas. The Location Quotient (LQ) was calculated as the main factor to measure accessibility and relationship between demographics and their geographic location to identify vulnerable areas, it was identified that a large number of low-income population does not have access to a bus stop within a 1-mile walking distance cutoff. The results have shown how unequal spatial accessibility and coverage in terms of public transportation can impact the underserved population.

Subject Area

Civil engineering|Urban planning|Transportation

Recommended Citation

Valenzuela Mendoza, Gerardo Ivan, "Equity Driven Data Analysis for Public Transportation Planning" (2022). ETD Collection for University of Texas, El Paso. AAI29211566.