Comparing Automated and Manual Visitor Monitoring Methods: Integrating Parallel Datasets on Mount Fuji’s North Face
Keywords:visitor use monitoring, visitation, infrared trail traffic counter, calibration, national parks
AbstractDue to their ease of installation and use, durability, and low cost, the use of passive infrared counters has increased rapidly in protected areas. This study investigated the calibration of one such beam sensor on the 8th station of Mount Fuji (3000 m) using a parallel count system at the 6th station (2390 m) as a manual control. Analysis of secondary data revealed the degree or error between 6th and 8th stations to fluctuate temporally, especially during congestion flashpoints such as Saturday and Friday nights. This suggests that current monitoring methods are underreporting the volumes of climber traffic at peak periods, but a calibration correction coefficient could be calculated by integrating the local and central government datasets. This study thus contributes to the pursuit of reliable, costeffective visitor monitoring methods by demonstrating an opportunistic and holistic combination of two pre-existing, longitudinal data sources. However, additional observational studies are still needed to supplement the findings of the continuous manual clicker data at the 6th with stratified random sampling at the 8th station for optimum integration of parallel monitoring methods. Improving the reliability of climber numbers via the generation of more accurate data is only the first step. Targeted intervention is required that actively utilizes such data to mitigate the current crop of management challenges including impacts on visitor experience (e.g., congestion) and on the natural environment (e.g., toilets, trash, trail conditions). Results provide useful pointers for park planners, site managers and decision-makers such as the Fujisan World Cultural Heritage Council. This study is one of a limited number of empirical case studies that tackle the inaccuracies of mechanical counting devices in a transparent and replicable fashion, using parallel counting systems along a single trail on Mt. Fuji’s north face to contextualize the correction coefficient based on specific site characteristics.Subscribe to JPRA
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