The premise of this study was that transport impacts on land use are rarely given formal or adequate consideration in the strategic planning system in the UK. Therefore, this research examined current attitudes to transport impacts on land use, amongst a wide range of relevant planners, academics and consultants. It was found that there was little familiarity with either research into these relationships, or the methods that can be used to forecast impacts. However, there was acknowledgement that incorporating this relationship into planning
processes is necessary in order to integrate fully land use and transport planning.
The research therefore focused upon determining the necessary attributes of practical methods to examine transport impacts on land use. Three contrasting methods were applied to a single case study area (Lothian region). These were (1); a novel application of the Delphi technique, (2): an updated implementation of an existing static land use response model, and (3): a newly developed complex dynamic land use transport model. Each was
used to examine the land use response from hypothetical road pricing and light rail transit schemes. These methods and their forecasts were then assessed using the views of planners in a further round of more complex in-depth interviews.
From this several conclusions were reached. If transport impacts on land use are to be more commonly and formally assessed, then it is necessary to generate indicators that are directly relevant to the planners' needs. Examples of such indicators are discussed. Secondly, any method must be able to explain the forecasts in terms that are acceptable to the planners, in order to foster confidence in the method. The requirements for increasing confidence are
examined, and comprise both technical and qualitative issues. Neither of these issues specifically requires new methods but rather, better targeting of, and education in, the existing available techniques.
It was found that the planners favoured the more complex approaches, not for any increased accuracy that may be possible, but for the better interpretation of results that such methods allow. However, this complexity also requires a much greater understanding of the assumptions and processes in the model, in order to avoid drawing spurious conclusions from the results. Conclusions are drawn regarding the balance between confidence and complexity, and hence the practical value of these methods to strategic planning.