Management of Recreational Areas: GIS, Autonomous Agents, and Virtual Reality

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.

[1]  Terry J. Brown.  Conceptualizing smoothness and density as landscape elements in visual resource management , 1994 .

[2]  C. Badcock,et al.  Simulating Societies: The Computer Simulation of Social Phenomena , 1995 .

[3]  Randy Gimblett,et al.  Multiple use management: Using a GIS model to understand conflicts between recreationists and sensitive wildlife , 1995 .

[4]  N. Gilbert,et al.  Artificial Societies: The Computer Simulation of Social Life , 1995 .

[5]  Jacques Ferber,et al.  Multi-agent simulation as a tool for analysing emergent processes in societies , 1992 .

[6]  John Rohlf,et al.  IRIS performer: a high performance multiprocessing toolkit for real-time 3D graphics , 1994, SIGGRAPH.

[7]  Jan W. van Wagtendonk,et al.  Travel time variation on backcountry trails , 1980 .

[8]  K.Ch. Graf,et al.  Perspective terrain visualization - A fusion of remote sensing, GIS, and computer graphics , 1994, Comput. Graph..

[9]  H. Randy Gimblett.  Simulating recreation behaviour in complex wilderness landscapes using spatially-explicit autonomous agents , 1998 .

[10]  Rudy Darken,et al.  Wayfinding strategies and behaviors in large virtual worlds , 1996, CHI.

[11]  J. L. Fridley,et al.  The validity of computer-generated graphic images of forest landscape , 1995 .

[12]  John C. Ellsworth,et al.  Perceived Scale Accuracy of Computer Visual Simulations , 1994, Landscape Journal.

[13]  Ian D. Bishop,et al.  Comparing regression and neural net based approaches to modelling of scenic beauty , 1996 .

[14]  Thomas C. Brown,et al.  Is motion more important than it sounds?: The medium of presentation in environment perception research , 1993 .

[15]  George H. Stankey,et al.  The ROS planning system: Evolution, basic concepts, and research needed , 1987 .

[16]  Ian D. Bishop,et al.  Prediction of scenic beauty using mapped data and geographic information systems , 1994 .

[17]  Ian D. Bishop,et al.  Automated mapping of visual impacts in utility corridors , 1988 .

[18]  S. Forrest,et al.  Modeling Complex Adaptive Systems with Echo , 1994 .

[19]  Eckart Lange.  Integration of computerized visual simulation and visual assessment in environmental planning , 1994 .

[20]  Kyu Shik Oh,et al.  A perceptual evaluation of computer-based landscape simulations , 1994 .

[21]  JoAnna Ruth Wherrett.  Natural landscape scenic preference : techniques for evaluation and simulation , 1998 .

[22]  H. R. Gimblett,et al.  Some practical issues in designing and calibrating artificial human recreator agents in GIS-based simulated worlds , 1996 .