Question

Please, I need tips on how to model land use and accessibility of rail station.

Answer 1

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.

ntroduction Accessibility is one of the key issues of transport and land use planning. It reflects the ease of reaching needed/desired activities and thus reflects characteristics of both the land use system and the transportation system (Handy and Clifton, 2001; Wu and Hine, 2003). It is crucial to allocate necessary land use destinations (LUDs) and to provide public transport (PT) networks within close proximity that would take people to these LUDs (e.g. goods, services, employment, social contacts) within a reasonable travel time (Hine and Mitchell, 2003). Transport and land use planning has a significant role in promoting accessibility, and at the same time accessibility is becoming increasingly important in making sound and sustainable land use and transport decisions (ODPM, 2003; Bertolini et al., 2005). Therefore it is important to develop models that are able to measure accessibility to PT networks and LUDs (Handy and Niemeier, 1997). Additionally, within these models accessibility standards are required in order to establish better land use and transport planning strategies and policies (Tyler, 1997). Although there have been several accessibility models previously developed, only a few considered access to PT and basic community services by using walking and PT modes, with a limited number implemented successfully in complex urban environments

Accessibility models Accessibility essentially describes an individual’s ability to reach desired goods, services, activities and destinations – collectively, ‘opportunities’ (Litman, 2003). Although a seemingly simple concept, accessibility has proven elusive to define and measure. Geurs and van Wee (2004) argue that despite the important role that accessibility plays in policy making, it is often misunderstood, poorly defined and a poorly measured construct. This is a reflection of the underlying complexity of accessibility as a multi-faceted concept. An assessment of transport from an accessibility approach could help in addressing issues of equity and transport disadvantage. This is a desirable outcome, as a socially just transport system provides a fair distribution of transport services and equal access to LUDs (Department of Transport, 2001). Accessibility is strongly affected by the design of infrastructure such as PT routes and stops, road network, and the availability of various LUDs in a close proximity. It is also influenced by problems such as the legibility of a timetable and the perception of safety (Tyler, 1999). According to Bertolini and le Clercq (2003) accessibility can be directly related to both the qualities of the transport system (e.g. travel speed), and the qualities of the land use system (e.g. densities and mixes). At the same time it can also be directly related to economic goals (access to workers, customers, suppliers), social goals (access to employment, goods, services, social contacts), and environmental goals (resource-efficiency of activity/mobility patterns). Cervero (1997) considers the paradigm shift from ‘automobility planning’ to ‘accessibility planning’ as an appropriate means of increasing accessibility and decreasing the negative impacts of transportation on the environment. Wixey et al. (2005) identifies several aspects in which accessibility has been used for planning purposes, which include:

(a) access to opportunities;

(b) distribution of transport impacts;

(c) travel options; (d) consistency of transport;

(e) linkages with public policies;

(f) impacts of new developments; and

(g) community and business travel planning.

In recent years, Australian state governments have started to realise the importance of accessibility. For example, one of the key policy strategies of the Melbourne 2030 is to plan urban development around high levels of accessibility to jobs and community services more accessible (Victorian Government, 2002). The primary goal of the Perth Metropolitan Transportation Strategy 1995-2029 is to improve and enhance accessibility throughout the whole metropolitan area (Ministry for Planning, 1995). Sydney’s Metropolitan Strategy views accessibility as an important policy for self-sustaining (Department of Infrastructure Planning,
2004). The Planning Strategy for Metropolitan Adelaide underlines the importance of enhancing accessibility and ensuring a fair distribution of resources throughout the urban area (South Australian Government, 2005). Similar to all above in SEQ Regional Plan 2005-2026 accessibility is also identified as one of the desirable regional outcomes (Queensland Government, 2005). Given that a reasonable level of fair and equitable access for all is a desired outcome for transport systems, an accessibility indexing model which monitors of a transport system’s performance is greatly beneficiary for land use and transport planning (DHC&UW, 2004). The importance of developing a composite transport and pedestrian oriented accessibility index is evident in land use and transportation literature (e.g. Hardcastle and Cleeve, 1995; Hillman and Pool, 1997; Ewing and Cervero, 2001; Handy and Clifton, 2001). However because of the complexity of developing accessibility indices, both within Australia and overseas, there has been limited research conducted on measuring accessibility and developing indices for planning purposes. One of the successful accessibility model developed, is the ‘Accession’ software by MVA and Citilabs. Accession is a GIS-based model and combines data on the local transport network and location of services with information on disadvantaged areas and demographic groups to identify particular accessibility problems. Accession used the following layers in measuring accessibility: PT data, road networks, LUDs, and demographic data. It also covers a range of modes, including PT, car, flexibly routed services, walking and cycling (AccessionGIS, 2006). The only downfall of this accessibility model is that it is not an open source model, therefore it can only be run via specific software (Accession and Geomedia). The second example is the accessibility model modified and developed by the Transport Studies Group. In their recent research they explored how a geographic accessibility index can be designed to quantify service accessibility within urban areas with a special focus on socially disadvantaged groups. They proposed enhancements on the two existing strategic accessibility measuring tools, ‘Calculator for Public Transport Accessibility in London’ (CAPITAL) and ‘Public Transport Accessibility Mapper for West Yorkshire’ (PTAM). This research also developed an accessibility planning tool to be used by local councils, which is called ‘Weighted Access for Local Catchments’ (WALC). These models used the combination of the following layers: local walking network, PT network, labour markets, financial services, education and training, healthcare, food shops and social, cultural and religious activity centres as the main LUDs (Wixey et al., 2005). The third example is the GIS-based accessibility model developed by Liu and Zhu (2004). This model provides a general framework for integrated use of GIS, travel impedance measurement tools and accessibility measures to support the accessibility analysis process. It includes formulating the concept of accessibility, selecting or developing accessibility measures, specifying the accessibility measures, deriving the accessibility values using the selected or developed accessibility measures, and presenting and interpreting the accessibility values. This model measures accessibility by PT to shopping centres, healthcare services, public schools, banks, post-offices, parks and community centres. This model also develops a composite index combining these different measures (Zhu et al., 2005). However this model does not consider walking modes in measuring accessibility to PT and LUDs. The last one is the ‘Metropolitan Accessibility and Remoteness Index of Australia’ (Metro ARIA). This project was developed for Adelaide and Melbourne metropolitan areas to produce an index measuring accessibility and remoteness by the University of Adelaide (ABS, 2001). Metro ARIA is a composite index that aims to measure the ability of people to access basic services within the metropolitan area. It quantifies levels of accessibility by measuring the on-road distance people travel from their homes to reach different types of services. It incorporates five themes (health, shopping, PT, financial and postal, education) and component services that combine to produce the final index (GISCA, 2005). One weakness of the model is that it measures accessibility by road distances only, which favours road-based mobility with the motor vehicle as the preferred mode of travel.

Conceptual approach of LUPTAI LUPTAI seeks to measure how easy it is to access common LUDs (e.g. health, education, retail, banking, employment) by walking and/or PT. This is in contrast to the traditional method of measuring accessibility by road or Euclidean distances, and is the first of its kind to consider PT as a means of access, rather than a facility to be accessed. LUPTAI is an origin-based accessibility model. It has been produced via the use of GIS analysis techniques, applied to datasets obtained from a number of sources, and using information relating to LUDs, the road/pedestrian network, and the PT network. The model produces a GIS based map giving a visual representation of the opportunity to reach places by PT and/or walking. A five colour scale shows the levels of access for any given area, highlighting areas of ‘No, Poor, Low, Medium or High’ accessibility. LUPTAI differs from the other accessibility models, as most of them conceive PT solely as a service to be accessed, and not as a means of potential access. It represents travel by modes other than the private motor vehicle and may be more useful in determining sustainable transport/land use outcomes. LUPTAI seeks to quantify accessibility to destinations via walking and the PT network. It considers walking in one of two ways: it may be either the single mode used to directly access a destination, or it may be the mode by which a person accesses PT services. Walking travel is measured in terms of actual distance, measured using the road and path network. In general, five minutes walking time is widely accepted as the equivalent to a 400 metre walk, assuming a walking speed of 80 m/min (O’Sullivan and Morrall, 1996; Department of Transport, 1999). It is also possible to convert walking distances to walking time, however the general tendency in transportation research is reporting walking travel as distance (Loutzenheiser, 1997; Shriver, 1997). LUPTAI is an open source model which does not rely on a single GIS software package, unlike other models. The model performs its analyses using ESRI ArcGIS, however it can be run on other GIS packages (e.g. MapInfo) that have the capability to measure on-road distances (network analysis). Figure 1 below illustrates the details of the GIS-based LUPTAI flowchart. During the developmental stage of LUPTAI, PT comprising of scheduled bus and rail services only were considered appropriate. Taxis, community transport and ferries were excluded, as were school bus services due to data availability issues. PT travel was measured in terms of travel time, derived directly from current timetable information. Walking distances to PT stops and LUDs are determined by examining current and previous household travel surveys (1992 and 2003/04) The LUDs used in LUPTAI were:

Employment: commercial zones (represent employment opportunities);

Health: chemists, dentists, doctors and hospitals;

Shopping: major shopping centres, newsagents (a measure of local shopping centres);

Financial and postal:ATMs, banks, post offices;

Education: primary, secondary and tertiary schools.

LUPTAI’s approach to trips is more realistic than other accessibility models.

It considers a trip which starts from an origin and includes all trips taken to reach a destination; walking to a PT stop, PT travel, walking to a destination from a PT stop. LUPTAI also accommodates PT frequencies, which are incorporated in the PT layers (AM peak, off peak, PM peak, and evening). Moreover different PT service periods are associated with relevant LUDs. For example employment is measured with AM and PM peaks, representing the times that accessibility to employment is most needed.