A national model for estimating US public land visitation
2022-2024
US Environmental Protection Agency
US Forest Service
Public land management relies on accurate visitor counts in order to understand and mitigate environmental impacts and to quantify the value of ecosystem services provided by natural areas. This project built and tested predictive models for estimating visitation to federally managed lands in the United States, based on multiple sources of digital mobility data including posts to social media, recreation report platforms, and a cellular device location dataset from a commercial vendor. Using observational visitation data series from the United States’ National Park Service, Forest Service and Fish and Wildlife Service, the team quantified the accuracy of statistical models to predict on-the-ground visitation using individual and combined sources of locational data. Research showed that models performed best in settings where some on-site visitation data can be integrated into models. On-site visitation data helped account for meaningful differences in modeled relationships both within and across the three agencies considered.