Our final project aimed to explore service access in Vancouver for individuals with mobility challenges relying on public transportation. In order to produce this map of physical accessibility, we used distance from public transit (bus and rapid transit) stops in combination with slope information. In identifying physically accessible locations and combining this with service data, our hope was to produce a map that identified suitable areas for future service sites.
In order to achieve this aim, we divided our team based on task. We considered individuals’ strengths, preferences and other commitments in order to assign tasks and establish a feasible time frame. This allowed us to meet in person only a few times over the course of the project, vital as we had differing schedules.
In producing the map, we quickly discovered that the most physically accessible areas with the highest density of services overlapped with areas typically associated with higher housing costs. This correlation between physical accessibility and economic inaccessibility forced us to broaden our understanding of accessibility, problematizing our previously defined ‘accessible’ zones. Instead, by considering housing prices as a very coarse indicator of economic accessibility, the most accessible locations shifted out of the downtown core, highlighting the implications of the assumptions and definitions made in GIS. As a result, rather than Yaletown being the most accessible location, the optimal are outside of the downtown core.
Using housing prices required normalization of the data by number of rooms, without normalization the cheapest area was the center of downtown. After normalization downtown became the least economically accessible location. Adding to this, we also classified layers based on a scale of 1-3, enabling us to create a new field and a weighted overlay to produce a single image of Vancouver’s accessibility, producing a sort of very loose and limited ‘accessibility index.’
However, data and time constraints continue to limit the scope of our accessibility analysis, such as information on many service locations data being limited to the City of Vancouver. Furthermore, it was not possible to validate our findings and compare these to reality as we lacked residential information specifically for those with mobility challenges.
Producing this single, weighted map required constant communication with the team, communicating information on findings, process and questions of classification to team members working on separate aspects of the project. This communication was eased by the clear definition of roles and timeframes and by keeping a running document of the steps and methodology used with a section detailing necessary future actions below.