Rättvisa på räls och väg - En GIS-baserad analys av samvariationen mellan socioekonomisk status och kollektivtrafikens tillgänglighet i Skåne - Krook,Filip; Werner,Gustav (2026)
Public transport is essential for closing the gap between different geographical locations. The equal distribution of opportunities to travel is fundamental in both Edward Soja’s theory of spatial justice and Karel Martens’ theory of transport justice. Access to modes of transport may vary according to the socioeconomic status of the area, creating differences in transport opportunities based on location. This essay aims to explore the relationship between socioeconomic status and accessible public transport in Scania, southern Sweden. The relationship is explored by creating a socioeconomic index and a public transport accessibility index, which are analyzed through regression analysis with the use of geographical information systems. The results show both positive and negative local relationships in different parts of Scania. The local positive relationships are primarily situated in and around the largest cities. These positive relationships show areas where public transport gets more accessible the stronger the socioeconomical status is, which indicates an uneven distribution of travel. However, the relationships are highly local, and the opposite relationship is also identified in the same cities. This suggests that the result isn’t necessarily structural, but may rather be the result of complex, long-term urban development in areas with different preconditions. The result is however problematic from a perspective of transport justice, as individuals in the identified socioeconomically disadvantaged areas with poorer access to public transport risk falling into transport poverty due to a lack of financial means for car-based mobility. This, in the long term, can further trigger the processes behind social exclusion.
Keywords: public transport; socioeconomic status; spatial justice; transport justice; accessibility; time geography; geographically weighted regression; GIS; Scania