Rick James Evans

A GIS‐based land use and public transport accessibility indexing model

Accessibility indexing is important in evaluating existing land use patterns and transportation services, predicting travel demands and allocating transportation investments. A GIS-based land use and public transport accessibility indexing model has been developed for measuring and mapping levels of accessibility to basic community services by walking and/or public transport, within local government areas. The model aims to assist the planning and decision making process to deliver integrated land use and transportation outcomes. It is an origin-based accessibility model that determines levels of accessibility by utilising GIS analysis techniques to measures accessibility based on both actual walking distances and public transport travel time. The model has been applied to two pilot studies in the Gold Coast City to assess its practicality and effectiveness. This paper outlines the methodology of the model and the findings related to these pilot studies. The paper also demonstrates benefits and application of the model to other urbanised local government areas.

Investigating the Social Dimensions of Transport Disadvantage II: From Concepts to Methods through an Empirical Case Study

This article is the second of two papers that review the field of spatially sensitive social scientific research into the links between social status and transport disadvantage. The first paper undertook a comprehensive review of the social scientific and transport planning literature to mark the level of development in the field and identify conceptual and methodological issues and constraints in this field of inquiry. The present article supports the advancement of socially and geographically sensitive transport research by opportunities for the development of more sophisticated spatial analytical methodologies. The approach we present is able to account for factors not previously addressed in either social or transport planning research, in particular the temporal dimensions of transport service accessibility. The article articulates the methodology through an empirical case study of socio-spatial transport disadvantage within the Gold Coast City. The article demonstrates that there are important theoretical and practical lessons to be gained for researchers and policy makers in addressing the social dimensions of transport and infrastructure provision. Further, the article argues that an attentiveness to new ways of combining and representing social and transport data-sets can promote policy relevant empirical social inquiry. The article also contributes in a productive way to the empirical knowledge of Australias sixth-largest metropolitan area, which is often overlooked by urban scholars.

Travel behavior patterns of different socially disadvantaged groups: analysis of household travel survey data for a dispersed metropolitan area

This paper contributes to the understanding of transport disadvantage and the transport dimensions of environmental justice by investigating the travel behavior patterns of socially disadvantaged groups by using household travel survey data. The study described in this paper goes beyond determining the basic descriptive statistics that are commonly reported in this area of research and instead uses cluster analysis to identify socially disadvantaged households. The study then uses the six clusters generated by the analysis to identify the differences in the travel behaviors between these groups. The paper shows considerable differences in travel behavior between socially disadvantaged households that must be recognized if scholars and policy makers are to describe and respond adequately to the experience of transport disadvantage for these groups. The paper concludes with some comparative observations about the travel behavior of the disadvantaged population in dispersed rapidly growing regions and the wider implications for ensuring environmental justice in transport.

How Will We Get There? Analyzing Access of Low-Socioeconomic-Status Households to Destinations in Australian Cities

Access to essential goods and services is increasingly recognized as a key factor influencing household socioeconomic disadvantage within cities. Socioeconomic status (SES) and spatial location partly determine differential accessibility. Spatial variation of low-SES groups across cities and the travel patterns of these groups have been mostly ignored by strategic transport models, which have been concerned more with traffic volumes on the road network and peak hour travel. This study expanded on a method that used cluster analysis techniques to identify low-SES groups on the Gold Coast of Australia from a large regional household travel survey. This method allowed for the identification of the actual travel behavior of low-SES groups. With this information, the study advanced a new origin–destination-based land use and transport accessibility model. The model used the output from the cluster analysis, in conjunction with 2006 Australian census data, to highlight accessibility to goods and service needs for a set of low-SES groups on the Gold Coast. The method developed provided unique opportunities for research into spatial disadvantage and accessibility in Australian cities. The conceptualization of the transport network with outputs provided at the census collection district level (approximately 200 households) ensured that the model could be run concurrently with conventional transport models.

How Will We Get There

Access to essential goods and services is increasingly recognized as a key factor influencing household socioeconomic disadvantage within cities. Socioeconomic status (SES) and spatial location partly determine differential accessibility. Spatial variation of low-SES groups across cities and the travel patterns of these groups have been mostly ignored by strategic transport models, which have been concerned more with traffic volumes on the road network and peak hour travel. This study expanded on a method that used cluster analysis techniques to identify low-SES groups on the Gold Coast of Australia from a large regional household travel survey. This method allowed for the identification of the actual travel behavior of low-SES groups. With this information, the study advanced a new origin–destination-based land use and transport accessibility model. The model used the output from the cluster analysis, in conjunction with 2006 Australian census data, to highlight accessibility to goods and service needs for a set of low-SES groups on the Gold Coast. The method developed provided unique opportunities for research into spatial disadvantage and accessibility in Australian cities. The conceptualization of the transport network with outputs provided at the census collection district level (approximately 200 households) ensured that the model could be run concurrently with conventional transport models.

How will we get there? New approaches to analyzing low-socio-economic status household access to destinations in Australian cities

Access to essential goods and services is increasingly recognized as a key factor influencing household socioeconomic disadvantage within cities. Socioeconomic status (SES) and spatial location partly determine differential accessibility. Spatial variation of low-SES groups across cities and the travel patterns of these groups have been mostly ignored by strategic transport models, which have been concerned more with traffic volumes on the road network and peak hour travel. This study expanded on a method that used cluster analysis techniques to identify low-SES groups on the Gold Coast of Australia from a large regional household travel survey. This method allowed for the identification of the actual travel behavior of low-SES groups. With this information, the study advanced a new origin–destination-based land use and transport accessibility model. The model used the output from the cluster analysis, in conjunction with 2006 Australian census data, to highlight accessibility to goods and service needs for a set of low-SES groups on the Gold Coast. The method developed provided unique opportunities for research into spatial disadvantage and accessibility in Australian cities. The conceptualization of the transport network with outputs provided at the census collection district level (approximately 200 households) ensured that the model could be run concurrently with conventional transport models.