Abstract
Abstract Simulation techniques are used to explore the complex spatial interactions between recreationists and their environment as a way to improve wildland recreation management. The Recreation Behavior Simulator (RBSim) uses rule-driven autonomous agents as surrogates for human visitors coupled with geographic information systems to represent the environment for dynamically simulating recreation behavior. Behavioral rules are derived from visitor surveys conducted in Broken Arrow Canyon, Sedona, Arizona. Model runs allow both statistical and spatial analysis to quantify and explore recreationists' movement patterns, encounters, and the influence of management actions on visitor use levels.
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