Strava Metro mobility data provides accurate estimates of recreation use in Urban-Proximate Protected Areas
Noah Creany et al.
Abstract
This study evaluates the efficacy of Strava Metro data for estimating recreational trail use in protected areas, which targets a critical need to understand patterns of human movement given the increasing trends in visitation. We compare Strava Metro data, encompassing aggregated pedestrian and cycling activity, with calibrated TRAFx trail counter data across 13 trails within three protected areas in the greater Los Angeles region over a one-year period. Along with the Strava Metro data, we collected daily weather covariates to analyze the efficacy and utility of Strava Metro for predicting recreational trail use. Our findings demonstrate the potential of Strava Metro to provide robust estimates of recreational trail use, particularly for cycling use, while also acknowledging inherent limitations concerning representativeness and potential socio-demographic biases. This research contributes to the development of effective monitoring strategies using secondary data sources to understand human mobility patterns in protected area settings that inform park management decisions and support long-term conservation objectives. • Strava Metro data combined with weather covariates provides accurate daily estimates of trail use, expressly cyclingtrails. • While Strava Metro predicts trail use well, it's not demographically representative, biased toward male cyclists aged 35–54. • An integrated approach could combine Strava Metro with surveys to understand demographics and ensure equitable management.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.