Assessing the validity of mobile device data for estimating visitor demographics and visitation patterns in Yellowstone National Park. (1st September 2022)

• Record Type: Journal Article
• Authors: Liang, Yun; Yin, Junjun; Pan, Bing; Lin, Michael S.; Miller, Lauren; Taff, B. Derrick; Chi, Guangqing
• Is Part Of: Journal of environmental management. Volume 317(2022)
• Publication Date: 2022-09-01
• Subjects: Mobile device data -- Visitor demographics -- Temporal visitation patterns -- National park; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2022.115410
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Monitoring visitor demographics and temporal visitation patterns can help national park managers understand their visitors and allocate resources more effectively. Traditional approaches, such as visitor surveys or vehicle counts, are limited by time, space, labor, and financial resources. More recently, mobile device data have been adopted for monitoring visitors in park-related or tourism research. However, few studies validated mobile device data with traditional visitor surveys or count data. Combining mobile device data with the American Community Survey (ACS), this study assessed mobile device data's validity in a national park context with three approaches: Points of Interest (POIs), visitor demographics, and temporal visitation patterns. The results revealed that only half of the POIs inside Yellowstone National Park are valid. Compared to traditional visitor surveys, mobile device data are limited due to platform bias and the exclusion of international visitors, resulting in discrepancies in visitor demographics, such as education and income levels. Conversely, mobile device data have strong correlations with count data regarding monthly and daily visitation patterns. The results suggest that with careful consideration, mobile device data can serve as an additional and complementary source of information to traditional survey data for understanding visitor demographics and temporal visitation patterns. Highlights: Mobile data are validated from three aspects: POIs, visitor demographics, and temporal visitation patterns. Mobile data are unable to accurately estimate certain visitor demographics, such as income levels. Mobile data have strong correlations with monthly and daily visitor counts, representing more nuanced visitation patterns.