Evaluating Mobility Data for Recreation Monitoring

Citation

Duff, C., Antia, A., Hilger, J., Horsch, E., Merrill, N., Murray, J., … Wood, S. & Zafonte, M. (2026). Evaluating Mobility Data for Recreation Monitoring: Diagnostics and Implications for Best Practice. Land Economics. doi.org/10.3368/le.102.3.011626-0006

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Mobile device location data (often called mobility data) is an emerging and promising way to understand how people use recreational areas. This paper examined data from four commercial providers across three real-world examples to highlight some key challenges.

Their findings show that patterns in the data—such as where and when people appear to visit—are not always consistent, and they don’t always match counts collected on-site. Based on these results, the authors outline a simple framework to explain where these differences and potential errors may come from when estimating visitation using mobility data.

They also discuss practical ways to assess the quality of this data and recommend additional information that data providers could offer to make these insights more reliable and useful for recreation planning and management.

Abstract

Mobile device location data (or mobility data, MD) are a novel and exciting source of information for recreational monitoring. In this paper we analyze datasets from four commercial vendors across three case studies to illustrate some important challenges. Our results show inconsistent spatial-temporal patterns and correlations with on-site counts. Given this evidence, we describe a conceptual model of the potential sources of error and structural variability in visitation estimates derived from MD. We discuss approaches for evaluation of data quality and suggest a range of supplemental data products that vendors could provide to support recreation analysis.