Management of recreational areas: GIS, autonomous agents, and virtual reality

Management of recreational activity in areas that are culturally or ecologi cally sensitive requires knowledge, and effective management, of recreation ists' behaviour. In this paper we explore the role of spatial information s ystems, spatial modelling, and virtual reality in the analysis and predicti on 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 bec ome 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 an d calibrated fi om visitor surveys. This is, however, an expensive and time -consuming process and testing of people's decisions in a virtual environme nt may provide sufficient information for rule definition. Once a rule-set is determined, the autonomous agents move over a GIS-based model of the lan dscape. Rendering algorithms determine what an individual agent is able to 'see'. Based on the established rules, this and other factors (such as tire dness) determine behavioural choice. Recording of model runs to file allows managers to undertake additional analysis to quantify and explore the infl uence of alternative management options on recreationist movement, congesti on, and crowding. Through the GIS, impacts such as erosion can also be mode lled. In the longer term the combined models can become part of a decision support system for sustainable tourism in fragile environments.