Analyzing Accessibility Inequalities and Workplace Reachability in Public Transport Systems: a Data-Driven Approach

In a smart city, it is essential to plan and design transport systems to reduce the environmental, social and economic impacts. Rethinking urban mobility, starting with the predominant use of Public Transport (PT) is essential, especially in the light of current policies aimed at discouraging the use of private cars, thus reducing vehicle congestion, pollution and land consumption. As most daily trips are related to commuting to workplaces (Isfort, 2024), providing efficient connections to PT systems is paramount in promoting a modal shift. Improving the access and connectivity between residential and industrial areas also helps to strengthen the local productive fabric. The aim of this work is to evaluate the accessibility to workplaces through a data-driven methodology that combines GIS tools and spatial analysis techniques using Python. Large-scale geographic data and temporal availability and territorial coverage of public transport are processed to generate detailed maps and calculate accessibility scores, guiding towards the exploration of territorial inequalities. The methodology has been applied to the case study of the metropolitan city of Catania (Italy), which has one of the highest motorisation rates in Europe. Accessibility scores are analysed in relation to the current PT supply and the assessment of inequalities is carried out across different parts of the study area. This study is proposed as a key tool for administration to help them identify intervention areas and assess the impact of new transport services to improve accessibility.