Visitors’ Perceived Crowding, Visual Attention, and COVID Infection Risks in National Parks: A Social Density Optimization Approach

Abstract

The COVID-19 pandemic has intensified the complexity of national park visitors’ perceived crowding and visual attention. Decision support frameworks are needed to monitor, quantify, and forecast visitors’ visual attention, perceived risks, and perceived crowding by different social density conditions before and during the COVID-19 pandemic. This study forecasts temporal patterns of visitors’ perceived crowding by varying perceived risk levels and visual attention in a national park. A mixed-methodology was developed using longitudinal monitoring, visitor surveys (n = 444), and eye-tracking experiments (n = 42). Results suggest that visitors’ perceived crowding and visual attention fluctuate dramatically by varying perceived risk levels. Moreover, Kernel Density analysis and mediation analysis indicate that perceived crowding is associated with inadequate visual attention to natural landscapes, and visual attention is a mediator between perceived risk and perceived crowding. Results developed a real-time analytical approach for visual attention and perceived crowding guided by the dual-process theory and attention restoration theory.