OpenMed/multicare-articles huggingface dataset:
Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site
Authors: Jin-Hui Guo, Tian Guo, Kai-Miao Lin, Dan-Dan Lin, Yu-Fai Leung, Qiu-Hua Chen
Journal: PLoS One (2019)
MeSH terms: Parks, Recreational, Research Support, Non-U.S. Gov't, China, Conservation of Natural Resources, Humans, Photography, Records, Recreation, Travel

Tourist congestion at hot spots has been a major management concern for UNESCO World Heritage Sites and other iconic protected areas. A growing number of heritage sites employ technologies, such as cameras and electronic ticket-checking systems, to monitor user levels, but data collected by these monitoring technologies are often under-utilized. In this study, we illustrated how to integrate data from hot spots by camera-captured monitoring and entrance counts to manage use levels at a World Heritage Site in Southeastern China. 6,930 photos of a congestion hotspot (scenic outlook on a trail) were collected within the park at a 10-minute interval over 105 days from January to November 2017. The entrance counts were used to predict daily average and maximum use level at the hotspots. Results showed that the average use level at the congestion hotspot did not exceed the use limit mandated by the park administration agency. However, from 9:20 am to 12:00 pm, the use level at hotspots exceeded visitor preferred use level. Visitor use level was significantly higher at the hotspot during a major Chinese "Golden Week". The daily entrance counts significantly predicted the average and maximum use level at the hotspot. Based on our findings, park managers can achieve the management goals by permitting the corresponding number of visitors passing the entrances. The gap manifested the complexities in visitor capacity management at high-use World Heritage Sites and other protected areas and calls for innovative monitoring and management strategies.