Edinburgh Napier University

  Sustainable transport requires a perspective that extends beyond the present and beyond the transport system itself. To view sustainability properly requires more sophisticated models than we currently employ, and more data than we currently collect. As we extend the capabilities of models, and require better monitoring of transport impacts, the scope and scale of data needs increases significantly. Scope increases as environmental data items, covering issues such as air pollution or greenhouse gas emissions, are needed. Scale increases as both temporal and spatial detail expands. For example, morning weekday peak commuter travel data to key destinations was once sufficient for planning transport capacity. However to monitor the environmental impacts of transport, or assess measures to reduce them, data covering travel throughout the day and the week is needed. Moreover the impacts of travel for all purposes to all destinations need to be assessed, requiring fine spatial detail. There are two basic characteristics required for sustainability assessments and monitoring which are particularly data hungry:
1. Taking account of interactions: Interactions between different transport, activity and physical systems are necessary components of any serious sustainability information system. One dimensional assessments of, for example, a single mode, can ignore the effects on all the others.
2.Extending over time to ensure that sustainability is maintained: Impacts of measures which seem successful in the short term need to be tracked in case benefits unwind over time. Sustainability demands a longer term perspective, and the data and analysis framework must follow the same path.

Requirements for extra data, for data update for tracking over time, plus data management systems to manage large and diverse data sets, place strains on transport data budgets. In this situation the data manager asks “when is it worth – or when is it necessary – to invest in updating this information?” This is particularly an issue for updates of transport surveys which are often costly to conduct. Yet the type of information collected in transport surveys, providing insights into revealed and stated behaviour and preferences, is particularly important when moving to a more sustainable transport system depends upon behavioural change. Regular updates are likely to be needed and a continuing horizon for data review and refreshment cannot be avoided. This paper, which builds on work done for the Queensland Department of Transport (Meyrick and Oxford Systematics, 2006), addresses a process model for dealing with this crucial question. It develops a way of ensuring that it is problem based rather than an attempt to upgrade existing data wholesale, or fill gaps for the sake of it. Many different types of data are required, and to be able to prioritise where the value is greatest in securing fresh information is critical. A better system than we currently have to address this in a timely and balanced manner is needed.