Comparing Automated and Manual Visitor Monitoring Methods: Integrating Parallel Datasets on Mount Fuji’s North Face

A study on Mount Fuji's North Face reveals that automated visitor monitoring methods, such as passive infrared counters, significantly underreport climber traffic during peak periods like Friday and Saturday nights. The research integrated parallel datasets from the 6th (2390 m) and 8th (3000 m) stations, demonstrating temporal fluctuations in error rates between manual and automated counts. While a calibration correction coefficient was identified for more accurate data generation, the study underscores the need for further observational studies to refine monitoring methods. Improved visitor data reliability is crucial for addressing management challenges, including congestion and environmental impacts, and offers actionable insights for park planners and the Fujisan World Cultural Heritage Council.

Jones, T. E., Yang, Y., & Yamamoto, K. (2018). Comparing Automated and Manual Visitor Monitoring Methods: Integrating Parallel Datasets on Mount Fuji’s North Face. Journal of Park and Recreation Administration, 36(1), 22–38. https://doi.org/10.18666/jpra-2018-v36-i1-7976