Management of recreational activity in areas that are culturally or ecologically sensitive requires knowledge, and effective management, of recreationists' behaviour. In this paper we explore the role of spatial information systems, spatial modelling, and virtual reality in the analysis and prediction of visitor location and movement patterns. The quantitative modelling of the time spent by visitors on various aspects of the site attractions and of visitor conflict has not been widely attempted, having only recently become possible because of greater computer power, better spatial data storage options, and new modelling paradigms. Rule-driven autonomous agents can be used as surrogates for human visitors. Behavioural rules can be derived and calibrated from visitor surveys. This is, however, an expensive and time-consuming process and testing of people's decisions in a virtual environment may provide sufficient information for rule definition. Once a rule-set is determined, the autonomous agents move over a GIS-based model of the landscape. Rendering algorithms determine what an individual agent is able to 'see'. Based on the established rules, this and other factors (such as tiredness) determine behavioural choice. Recording of model runs to file allows managers to undertake additional analysis to quantify and explore the influence of alternative management options on recreationist movement, congestion, and crowding. Through the GIS, impacts such as erosion can also be modelled. In the longer term the combined models can become part of a decision support system for sustainable tourism in fragile environments.
ASJC Scopus subject areas
- Geography, Planning and Development
- Urban Studies
- Nature and Landscape Conservation
- Management, Monitoring, Policy and Law