The demographics of public transport accessibility
Local governments are responsible for providing adequate service and infrastructure to their residents. Making sure there are enough playgrounds in areas with many young families and children and that footpaths and kerbs are suitable for residents in ageing suburbs are just some examples of population-appropriate service provision. One way of assessing if coverage and accessibility to services are adequate or appropriate is to study catchments and identify gaps where a particular service may be missing then delve deeper and ask – are the demographic characteristics of people in those service gaps different to the overall population?
To accurately assess coverage and usage (demand) of certain services, a catchment approach can be used which answers questions such as, “How many children live within 1km of this playground? Has that changed over time? Is it likely to change in the future and if so, would this justify a playground infrastructure upgrade?”. Demand analysis and assessment of demographic characteristics based on catchments is an effective way of understanding where your service provision may be spatially deficient (gaps) or where it may be population-inappropriate (e.g. prioritising playgrounds over footpath upgrades in an ageing suburb).
Recent catchment analysis example
We recently completed an interesting project for Albury City and the City of Wodonga. The project goal was to assess the demographic characteristics of residents who live outside of public transport walking catchments and who do not have reliable transport options within their households.
This analysis helped answer questions such as:
- how different are residents with unreliable public transport options to the overall population?
- are they older, younger, more or less diverse than the overall population?
- are they more socioeconomically disadvantaged?
With this information, the two cities would know whether they’d need to advocate for service improvement, better coverage and increased frequency of public transport in their communities.
Working collaboratively with councils
A project like this relies on our spatial analysis expertise as well as knowledge of demographic information which best characterises differences between residents outside of public transport catchments and those within them.
As with many collaborative projects, establishing strong communication channels between key contacts is important (especially in the “remote meetings” era). We met with several council staff who would be using the final output from the analysis as well as council spatial analysts, who would be providing us with mappable public transport information.
Spatial and demographic analysis
This project first required bus stop information in a spatial/GIS format, from the two councils. We could then geocode the information and map the locations of public transport stops before using network analysis in GIS software to create isochrones depicting walking distance catchments to those stops. Catchments were used in spatial selection of underlying statistical geography (SA1s) so we could capture statistical areas that included residents within or outside of public transport catchments. Where SA1s were not entirely within or outside of a catchment, we utilised splitting techniques with finer meshblock geography to ensure accurate coverage of statistical geographies. The video below is a visual illustration of all those spatial analysis steps.
Once areas outside of public transport catchments were accurately depicted, we queried ABS data to find out demographic information about residents living outside catchments, such as:
- Age structure
- Education characteristics
- Employment status
- Income levels
- Diversity (recent arrivals and proficiency in English) and
- Need for assistance due to disability
Although findings were amalgamated into two groups (“residents within” and “residents outside” of catchments) at only the LGA level, further analysis could have easily been presented at a suburb level to show perhaps where the largest differences in demographic characteristics were evident.
Findings and using results to improve service coverage
Once collated, statistical information showed that Albury City and City of Wodonga residents living outside of public transport catchments:
- are generally younger than the LGA population
- are more likely to be females than males
- are less highly educated than the LGAs overall
- are not employed full-time as much as the LGAs overall
- have lower-income levels
- are more ethnically diverse, with higher proportions of the population being recent arrivals who speak a language other than English
- have a higher need for assistance due to disability.
Another output from this analysis was a visual understanding of where public transport catchments were inadequate and where service coverage gaps were visible. In both Albury City and the City of Wodonga, areas with the largest “holes” in coverage (other than rural, lowly populated areas) were recently developed areas, where many residents lived, but where public transport services did not offer adequate coverage. This was almost a “by-product” of this analysis yet it provided the two councils with information that can be used to advocate for better coverage in these recently populated areas.
With this information and with other extensive analysis done outside the scope of this project, Albury City and City of Wodonga can make informed conclusions and correct strategic decisions about how to best advocate for public transport service improvements.
Demand analysis and catchment analysis are very powerful ways of understanding if the provision of services and infrastructure is appropriate for an area’s population and if service coverage is meeting expectations. .id can help you identify and describe the population around certain services to inform whether current or planned service provision is under servicing, over-servicing or correctly servicing residents. Catchment analysis such as this can also help you understand the population currently within or outside reasonable proximity to community assets such as playgrounds, sports fields, swimming pools, community halls or libraries and whether the demographic characteristics of those residents who “miss out” on some community assets allude to some sort of socioeconomic disadvantage.
If you have a similar project or question you’re trying to answer, we can help. Take a look at our list of case studies and if you’d like to discuss this piece of work or anything else you need assistance with, book a 30-minute remote meeting with me or simply email us at email@example.com.