Equity issues and the PeCUS index: an indirect analysis of community severance

Abstract

Urban barriers are often a consequence of the unplanned expansion of transport infrastructures, housing growth nearby existing transport infrastructures, and the vehicular traffic itself. This process, also known as "community severance", is a problem that affects the travel patterns of the population and causes negative impacts to adjacent communities, but it is not easy to assess. As an alternative to the costly technologies and restricted-access data sometimes used to analyze urban barriers, we propose an analytical approach that assesses community severance levels by classifying the quality of Pedestrian Crossings on Urban Streets (the PeCUS index). Additionally, the approach is used to identify possible inequities nearby the different classification groups regarding demographic data. We used the chi-square (χ2) test of independence and the standardized Pearson residuals to indicate deficits and excesses of residents regarding the demographic characteristics studied surrounding the urban streets. We found the following evidences of associations: residents with low-income or those aged up to 19 tend to live close to the worst crossings, whereas residents with permanent mobility constraints or the elderly tend to live near the crossings with the best classifications. Therefore, the study shows that the assessment of community severance by the analysis of the PeCUS index is feasible. Moreover, it reveals that the distribution of residents surrounding the distinct classes of quality of crossings is equitable for vulnerable social groups, except for low-income or young residents.

Assessing the fragmentation-barrier effect in urban areas: The case study of Thessaloniki, Greece

“…Concerning the transport infrastructure that could be considered as potential physical and dynamic barriers, the current methodological approach, building upon the findings of the literature on vulnerable users' mobility, e.g. [12,20,22,35], identifies the following:…”

“…The authors pilot-tested their toolkit on a major road in North London, UK [12]. A few years later, Lara and Rodrigues da Silva (2019; 2020) introduced a methodological approach to appraise the barrier effect caused by railway lines and roads in the city of São Carlos, Brazil [4,22]. Utilising georeferenced population census data, the authors highlighted significant differences in the socio-economic characteristics of the affected population [4,22].…”

“…A few years later, Lara and Rodrigues da Silva (2019; 2020) introduced a methodological approach to appraise the barrier effect caused by railway lines and roads in the city of São Carlos, Brazil [4,22]. Utilising georeferenced population census data, the authors highlighted significant differences in the socio-economic characteristics of the affected population [4,22]. Moreover, building upon their experience from previous studies, Jesus and Rodrigues da Silva (2022) investigated through a questionnaire survey the local population's perception regarding the potential role of high traffic volume and speed as a dynamic traffic barrier [23].…”