A GPS-Based Classification of Visitors’ Vehicular Behavior in a Protected Area Setting
DOI:
https://doi.org/10.18666/JPRA-2018-V36-I1-8287Keywords:
GPS tracking, visitor behavior, vehicle movement, travel patterns, spatial classificationAbstract
As tourism and visitation increases to parks and protected areas worldwide, concerns regarding degradation of natural resources and visitor experiences also increase. As such, understanding visitor use patterns and spatial characteristics is important for better management of social and ecological resources. In many parks and protected areas, transportation systems (including park roads, parking lots, personal vehicles, public transit services, bicycle and/or pedestrian paths, and Intelligent Transportation Systems (ITS) that help deliver visitors to their destinations within parks) are a primary way for tourists and visitors to interact with and experience natural environments. Transportation systems designed with visitor use patterns in mind can both provide a positive experience for tourists as well as minimize impacts to natural resources within parks and protected areas. Our research used Global Positioning System (GPS)-based technology and a statistical classification procedure to examine spatial and temporal patterns of vehicular visitation in the Moose-Wilson corridor of Grand Teton National Park. While GPS-based technology has been used in parks and protected areas to study the spatial behavior of hikers and bikers, it has not been widely utilized to study the spatial behavior patterns of visitors travelling in vehicles to park destinations. Similarly, statistical classifications have been used to understand visitor behavior patterns in parks and protected areas, but are rarely applied to spatial data such as GPS tracks of visitor spatial movements. This classification based on spatial behavior resulted in the categorization of visitors into three types: Opportunistic Commuters, Wildlife/Scenery Viewers, and Hikers. These results expand existing literature suggesting that interpretable patterns of visitor spatial movements can result from classification studies using GPS-based collection of visitor behavior data. Understanding these patterns of visitor behavior is important for the management of social and natural resource conditions at park destinations as well as visitor experiences within the transportation corridor, as different types of visitors often exhibit different spatial behavior patterns. The classification and associated patterns of visitor behavior have important implications for managers of parks and protected area as different types of visitors may require different transportation and information needs in order to achieve their desired experience and minimize ecological impacts.
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