Improving public transport accessibility can be considered an effective way of reducing the external costs and negative side effects of motorized commuting. Although there have been many studies ...conducted that have measured access levels to public transport stops/stations, there has been limited research on measuring accessibility that integrates population density within geographical areas. This study develops a new measure that considers public transport service frequency and population density as an important distributional indicator. A public transport accessibility index (PTAI) is formulated for quantifying accessibility within local areas in metropolitan Melbourne, Australia. A public transport network model is applied to identify the service coverage of public transport modes using a Geographical Information System (GIS). A consistent method is introduced for evaluating public transport accessibility for different levels of analysis, from single elements, including public mode stops to network analysis. The Victorian Integrated Survey of Travel and Activity (VISTA) is used to evaluate the index and examine the association between commuting trips undertaken by public transport and the level of accessibility within the Melbourne metropolitan region. Furthermore, the new index is compared with two existing approaches using the VISTA dataset. Key findings indicate that the PTAI had a stronger association whilst showing more use of public transport in areas with higher values of the PTAI.
•The paper presents a new index measuring public transport Accessibility (PTAI).•The index assessed and compared with two existing indexes using travel data of Victorian Integrated Survey of Travel and Activity (VISTA).•More use of public transport was found in areas with higher values of the PTAI.
The development of a public transport accessibility index for older travellers using total travel time is not a subject of frequent discussion. This study proposes a public transport accessibility ...index (EPTAI) which considers older peoples’ travel time and the populations of the second-smallest statistical areas according to census data. EPTAI identifies the level of access of the elderly to public transport (train, tram, and bus) in an urban area. The time-based EPTAI includes different trip purposes, including shopping trips (trips to shopping centres), medical trips (travel to healthcare centres), education trips (travel to education centres), and recreation trips (e.g., restaurants, parks, and cafes). The developed index is validated using statistical validation methods, including Pearson’s chi-square, likelihood ratio, linear-by-linear association, Cramer’s V, contingency coefficient, and phi. In addition, the performance of the developed index is compared with household survey data and the public transport accessibility level (PTAL). The results indicate that older adults’ public transport access varies depending on travel time, population density, and travel destination. The proposed index can be used for future planning/expansion and modification of public transport networks in urban and regional areas to meet the travel demands of older travellers.
While much research has explored the influence of the built environment on public transport use, little focus has been given to how this influence varies by public transport mode. Using a case study ...of Melbourne, this study assesses the influence of the built environment and other characteristics (transit service quality, demand management and socio-demographics) on commuting by train, tram and bus. Key findings indicate that the built environment has a significant influence, but with notable differences between individual public transport modes. Commuting by tram was found to have the strongest association with the explanatory variables, while bus had the weakest explanatory power. Differences in the geographical coverage of public transport services in Melbourne play a key role in explaining the influence of the built environment. Population density is positively associated with tram use, which operates in older, higher density environments, but is negatively associated with train and bus use. Furthermore, the association with land-use mix is only significant for train and tram use, as buses tend to operate in areas with greater land-use homogeneity. When focused on inner Melbourne only, the influence of the built environment is diluted, while distance to public transport becomes more significant. The findings have important implications for practice, not only in terms of improving transit demand forecasting but also in targeting changes to the built environment to leverage higher transit ridership by mode.
Household decisions to move from or stay at a current location may be based on a great number of variables. There has been substantial discussion among planners about the effect of the built ...environment in the choice of residential location. However, there is limited research on the role of non-motorised accessibility on residential location. Households may base their decision to move from or stay at a current location on the neighbourhood's accessibility. The public transport accessibility, walkability and bikeability of a neighbourhood may affect residents' decisions to stay or move from their current location. The focus of this paper is on modelling and comparing the influence of non-motorised accessibility measures on the number of years that households stay at their current location. The paper addresses this issue by employing three non-motorised accessibility measures in separate ordered logistic regression (OLR) models. Focusing on metropolitan Melbourne, Australia, the Victorian Integrated Survey of Travel and Activity (VISTA, 2012) was adopted to model years of residency incorporating socio-economic characteristics, built environment features and accessibility measures. Key findings indicate that non-motorised accessibility has statistically-significant impacts on the number of years that residents live at their current address. Furthermore, of the accessibility measures, access to public transport has the greatest impact.
•This paper aims at investigating the influence of non-motorised accessibility on residential location.•Focusing on Melbourne, Australia, three accessibility measures were employed in Ordered Logistic Regression (OLR) models.•Findings indicate that accessibility had significant impacts on residents’ tendency to stay in the same neighbourhood.
We investigate the prospective association between neighbourhood-level disadvantage and cardiovascular disease (CVD) among mid-to-older aged adults and whether physical activity (PA) mediates this ...association. The data come from the HABITAT project, a multilevel longitudinal investigation of health and wellbeing in Brisbane. The participants were 11,035 residents of 200 neighbourhoods in 2007, with follow-up data collected in 2009, 2011, 2013 and 2016. Multilevel binomial regression was used for the cross-sectional analysis and mixed-effect parametric survival models were used for the longitudinal analysis. Models were adjusted for age, sex, education, occupation, and household income. Those with pre-existing CVD at baseline were excluded from the longitudinal analyses. The mediated effect of PA on CVD was examined using multilevel generalized structural equation modelling. There was a total of 20,064 person-year observations across the five time-points clustered at three levels. Results indicated that the incidence of CVD was significantly higher in the most disadvantaged neighbourhoods (OR 1.50; HR 1.29) compared with the least disadvantaged. Mediation analysis results revealed that 11.5% of the effect of neighbourhood disadvantage on CVD occurs indirectly through PA in the most disadvantaged neighbourhoods while the corresponding figure is 5.2% in the more advantaged areas. Key findings showed that neighbourhood disadvantage is associated with the incidence of CVD, and PA is a significant mediator of this relationship. Future research should investigate which specific social and built environment features promote or inhibit PA in disadvantaged areas as the basis for policy initiatives to address inequities in CVD.
•Characteristics of disadvantaged neighbourhoods increase the risk of CVD.•Indirect effect of PA on CVD is higher in most disadvantaged neighbourhoods.•About 10% of the increased risk of CVD is mediated through lower levels of PA.
A growing number of recent studies have focused on improving the sustainability of transportation systems by routinely converting motorised travel to walking and conventional bicycling. The ...importance of physical activity has recently attracted the attention of practitioners as well as planners and policy-makers. In order to identify effective strategies for increasing active transportation, planners need to identify how current levels of accessibility in neighbourhoods affect walking and cycling trips. Despite a substantial amount of research on modelling active transportation, there have been limited studies on the importance of accessibility considering availability of activities and travel distances for pedestrians and cyclists. Hence, this study employs new approaches for measuring cycling and walking accessibility against land-use features in separate models to examine how accessibility can affect participation in active transportation. Key findings indicate that more accessible neighbourhoods have more active trips, while models using accessibility measurements show better fit on data.
Although pandemics are rare, planning and preparation for responding to them plays a crucial role in preventing their spread. The management and control of pandemics such as COVID-19 relies heavily ...on a country's health capacity. Measuring vulnerability to pandemics in geographical areas could potentially delay a pandemic's exponential growth and reduce the number of cases, which would alleviate the disease impact on communities and the health care sector. The aim of this study is to generate an area-level COVID-19 Pandemic Vulnerability Index (CPVI) and to assess its correlation with COVID-19 cases. Data were collected for Local Government Areas (LGAs) across Australia from different sources including Australia Bureau of Statistics, Australian Institute of Health and Welfare, and General Transit Feed Specification. Based on recent official reports about the COVID-19 outbreak, 18 factors were identified as influencing vulnerability to the disease within LGAs. Using factor analysis, four latent factors were identified and named as sociodemographic, medical conditions, transportation, and land use. Predicted factor scores were summed to generate a CPVI for each LGA. The CPVI was evaluated by correlating with confirmed cases of COVID-19 standardised by adult population in New South Wales and Victoria, the two Australian states with the highest numbers of confirmed cases. There was a statistically significant correlation between the CPVI and COVID-19 in New South Wales (r = 0.49) and Victoria (r = 0.48). LGAs scoring higher on the CPVI also had a higher absolute number of cases. The CPVI could be used by policymakers to identify at-risk areas and to develop preparedness and response plans to help mitigate the spread of COVID-19 and future pandemics.
•Developing a flexible pandemic vulnerability index at local contexts, which could be generalised elsewhere to identify at risk populations.•Proposing a tool for mapping vulnerable areas and allocating an appropriate amount of medical and associated equipment and staff well in advance.•Offering a useful guide for local government and communities to anticipate potential threats to their communities to respond promptly to threats.
The elderly population is increasing rapidly. Understanding travel behaviour for this group of commuters (in terms of the trip purpose and travel time) is necessary for future transport planning. ...Many researchers are working on travel’s spatial and temporal analysis to provide operational decision making and transport network planning. This research study’s primary purpose is to identify the influence of trip duration (using public transport), time of the day (usage of public transport), and public transport (PT) accessibility over public transport mode preference by elderly (over 65 years of age) commuters. The methodology of this study is divided into two parts as spatial analysis and temporal analysis. The research identified the dependency of trip duration, time of the day, geographical areas, and PT access over transport mode preference of elderly. The temporal study shows that transport mode preference can vary depending on trip purposes. However, for specific trip durations and times of the day, the elderly sometimes choose PT as a mobility mode. For instance, on shopping trips between 10:00 and 11:00 a.m., the elderly have a greater possibility of choosing public transport over private vehicles. Moreover, the results show the public transport mode preference based on different times of the day and trip purposes. Urban and transport planner can use the results to modify/plan public transport schedule, which can be easily accessible by the elderly population.
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