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Understanding changes in park visitation during the COVID-19 pandemic: A spatial application of big data.了解新冠疫情期间公园游客量的变化:大数据的空间应用
Wellbeing Space Soc. 2021;2:100037. doi: 10.1016/j.wss.2021.100037. Epub 2021 May 11.
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Changes in physical activity and sedentary behaviours from before to during the COVID-19 pandemic lockdown: a systematic review.2019冠状病毒病疫情封锁期间身体活动和久坐行为的变化:一项系统综述
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新冠疫情期间爱尔兰休闲步道使用情况的趋势:对实践的启示

Trends in recreational walking trail usage in Ireland during the COVID-19 pandemic: Implications for practice.

作者信息

Power Dylan, Lambe Barry, Murphy Niamh

机构信息

Centre for Health Behaviour Research, Department of Sport and Exercise Science, Waterford Institute of Technology, Ireland.

出版信息

J Outdoor Recreat Tour. 2023 Mar;41:100477. doi: 10.1016/j.jort.2021.100477. Epub 2021 Dec 15.

DOI:10.1016/j.jort.2021.100477
PMID:37521264
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8830802/
Abstract

UNLABELLED

Despite its potential utility for the outdoor recreation sector, there is no centralised surveillance system for recreational walking trails in Ireland and thus trail usage in Ireland during the COVID-19 pandemic is unknown. This paper aims to report trends in footfall count data on Irish trails during the COVID-19 period and to triangulate findings with openly available mobility data. This descriptive study analysed changes in footfall counts gathered from passive infrared sensors on 33 of Ireland's recreational walking trails between January 2019 and December 2020. The relationship between Google Community Mobility Report (GCMR) data and footfall counts was analysed to corroborate trends in footfall data. Total footfall increased by 6% between 2019 and 2020 on trails included in this analysis. Notably, mean trail usage was between 26% and 47% higher in October-December 2020 than during the same period in 2019. A strong correlation between GCMR data from 'parks' and footfall count data was found. The conclusions of this study are twofold. Firstly, the COVID-19 pandemic increased trail usage in Ireland, especially on trails closer to urban areas and there is potential for this to be a lasting legacy. Secondly, combining multiple data sources can provide trail managers with more detailed representations of trail usage and currently these are not harmonised. Future research should examine ways to encourage sustained recreational walking trail use in new users and implement novel ways to coordinate datasets across systems to monitor visitors on Irish recreational walking trails.

MANAGEMENT IMPLICATIONS

This paper presents a number of implications for trail management teams to consider:•Openly available datasets pertaining to mobility, such as Google Community Mobility Reports, can be utilised to corroborate data collected from footfall sensors in place on trails. Furthermore, there may be potential for Google Trends data to help trail management teams gauge interest in specific trails and parks during defined time frames.•There is considerable potential to sustain the COVID-19 legacy of increased trail use, especially for trails closer to urban areas, through promotional campaigns and continued trail maintenance.•There is a need to work across sectors and disciplines within the recreational walking system to identify potential data sources and opportunities for further data collection.

摘要

未加标签

尽管其对户外休闲部门具有潜在用途,但爱尔兰没有针对休闲步道的集中监测系统,因此在新冠疫情期间爱尔兰步道的使用情况不明。本文旨在报告新冠疫情期间爱尔兰步道人流量计数数据的趋势,并将研究结果与公开可用的出行数据进行三角测量。这项描述性研究分析了2019年1月至2020年12月期间从爱尔兰33条休闲步道上的被动红外传感器收集的人流量计数变化。分析了谷歌社区出行报告(GCMR)数据与人流量计数之间的关系,以证实人流量数据的趋势。在本分析所涵盖的步道上,2019年至2020年期间总人流量增加了6%。值得注意的是,2020年10月至12月的平均步道使用率比2019年同期高26%至47%。发现“公园”的GCMR数据与人流量计数数据之间存在很强的相关性。本研究的结论有两个方面。首先,新冠疫情增加了爱尔兰步道的使用率,尤其是靠近城市地区的步道,而且这种情况有可能成为一种持久的影响。其次,结合多个数据源可以为步道管理者提供更详细的步道使用情况描述,而目前这些数据并未得到统一。未来的研究应探讨如何鼓励新用户持续使用休闲步道,并采用新方法协调各系统之间的数据集,以监测爱尔兰休闲步道上的游客。

管理启示

本文为步道管理团队提出了一些需要考虑的启示:

• 可以利用与出行相关的公开可用数据集,如谷歌社区出行报告,来证实从步道上的人流量传感器收集的数据。此外,谷歌趋势数据可能有助于步道管理团队在特定时间段内衡量对特定步道和公园的兴趣。

• 通过宣传活动和持续的步道维护,有相当大的潜力延续新冠疫情期间步道使用率增加的影响,尤其是对于靠近城市地区的步道。

• 需要在休闲步道系统内跨部门和跨学科合作,以确定潜在的数据来源和进一步数据收集的机会。