Fostering Understanding of National Park Visitation Trends through Quantitative Methods and Visualization

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Torielli, Adrienne Camille

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Abstract

The United States Department of the Interior recognizes and protects over 400 entities, designated as National Park System Units, for public use and enjoyment. Celebrations for the National Park Service (NPS) centennial in 2016 highlighted the growth of the park system, particularly the recent uptick in visitors beginning in 2014. For the first time in 2016, overall visits reached over 500 million. Concerns over the ability to maintain the parks amid their resurgent popularity and financial constraints highlight the challenge of administering the areas comprising the parks. Historical visitation data is available for public use through the National Park Service dating back to 1979. This research sought to analyze the public use data set to determine if the current park popularity is part of an existing trend and discern the reasons for any changes. Annual summaries of visitation by NPS group certain trends by administrative region, as parks are located throughout the United States and its territories. However, visual representations of the park system are limited to charts depicting annual changes and aggregations of data by state. Previous reports indicate park visitors often do not come from communities that most closely and geographically surround the parks themselves. In addition, the parks are considered a tourist destination, influenced by variables impacting leisure expenditures, like economic conditions. Conducting exploratory visual analysis to identify spatial and temporal attributes of visitation allowed for an assessment of the entire historical data set, while other data science techniques provided methods for testing variables outside of park data. A web-based map highlighting the significant findings will serve as a reference for users interested in visualizing the information and exploring additional trends.

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Keywords

Geovisualization, National Park Service, KDD, Web Mapping

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