Assessing Inequality in Public Transport Accessibility: A Socio-Spatial Analysis

urban mobility public transport inequality mobility data

abstract

Public transport systems are vital for urban mobility, yet disparities in accessibility can contribute to social and economic inequalities. This study aims to evaluate the extent to which public transport accessibility influences inequality, with a particular focus on socioeconomically disadvantaged populations. By integrating geospatial analysis with socioeconomic data, this research seeks to identify disparities in transport accessibility and their broader implications.

introduction

Public transport is a crucial component of urban infrastructure, providing mobility to millions of people worldwide. However, accessibility to public transport varies significantly across different populations, leading to potential inequalities in access to employment, education, healthcare, and other essential services [1]. Understanding how these disparities manifest and their broader social implications is essential for informing policy and planning decisions aimed at promoting equitable urban mobility [2].

research questions

methodology

This study will employ a mixed-methods approach, combining quantitative geospatial analysis with qualitative socio-economic assessments. Key methodologies will include:

expected outcomes

The study aims to:

significance of the study

This research will contribute to urban mobility studies by offering a comprehensive assessment of accessibility-driven inequalities. By highlighting disparities and potential solutions, the findings can inform policymakers and urban planners in designing more inclusive transport systems.

This study will contribute to the discourse on transport equity and provide actionable insights to reduce accessibility-related inequalities in public transportation systems.

the project uses open data about Helsinki

This project requires intermediate Python (alternatively R, Julia, etc.) skills. It is good to have experience with plotting tools (matplotlib, seaborn or ggplot2/R, Gadfly/Julia, etc.), also regarding spatial data.

references

  1. Pereira, Rafael HM, Tim Schwanen, and David Banister. 2017. “Distributive Justice and Equity in Transportation.” Transport Reviews 37 (2): 170–91.
  2. Lucas, Karen. 2012. “Transport and Social Exclusion: Where Are We Now?” Transport Policy 20: 105–13.
  3. Bokhari, Ali, and Farahnaz Sharifi. 2024. “Public Transport Inequality and Utilization: Exploring the Perspective of the Inequality Impact on Travel Choices.” Sustainability 16 (13): 5404.
  4. Moreno-Monroy, Ana I, Robin Lovelace, and Frederico R Ramos. 2018. “Public Transport and School Location Impacts on Educational Inequalities: Insights from são Paulo.” Journal of Transport Geography 67: 110–18.
  5. Scheurer, Jan, Carey Curtis, and Sam McLeod. 2017. “Spatial Accessibility of Public Transport in Australian Cities: Does It Relieve or Entrench Social and Economic Inequality?” Journal of Transport and Land Use 10 (1): 911–30.