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Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site
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 mo...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660066/ https://www.ncbi.nlm.nih.gov/pubmed/31348788 http://dx.doi.org/10.1371/journal.pone.0215266 |
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author | Guo, Jin-Hui Guo, Tian Lin, Kai-Miao Lin, Dan-Dan Leung, Yu-Fai Chen, Qiu-Hua |
author_facet | Guo, Jin-Hui Guo, Tian Lin, Kai-Miao Lin, Dan-Dan Leung, Yu-Fai Chen, Qiu-Hua |
author_sort | Guo, Jin-Hui |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6660066 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-66600662019-08-07 Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site Guo, Jin-Hui Guo, Tian Lin, Kai-Miao Lin, Dan-Dan Leung, Yu-Fai Chen, Qiu-Hua PLoS One Research Article 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. Public Library of Science 2019-07-26 /pmc/articles/PMC6660066/ /pubmed/31348788 http://dx.doi.org/10.1371/journal.pone.0215266 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Guo, Jin-Hui Guo, Tian Lin, Kai-Miao Lin, Dan-Dan Leung, Yu-Fai Chen, Qiu-Hua Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site |
title | Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site |
title_full | Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site |
title_fullStr | Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site |
title_full_unstemmed | Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site |
title_short | Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage Site |
title_sort | managing congestion at visitor hotspots using park-level use level data: case study of a chinese world heritage site |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660066/ https://www.ncbi.nlm.nih.gov/pubmed/31348788 http://dx.doi.org/10.1371/journal.pone.0215266 |
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