Exploring impacts of COVID-19 on spatial and temporal patterns of visitors to Canadian Rocky Mountain National Parks from social media big data

COVID-19 posed challenges for global tourism management.Changes in visitor temporal and spatial patterns and their associated determinants pre-and peri-pandemic in Canadian Rocky Mountain National Parks are analyzed.Data was collected through social media programming and analyzed using spatiotemporal analysis and a geographically weighted regression(GWR)model.Results highlight that COVID-19 significantly changed park visitation patterns.Visitors tended to explore more remote areas peri-pandemic.The GWR model also indicated distance to nearby trails was a significant influence on visitor density.Our results indicate that the pandemic influenced tourism temporal and spatial imbalance.This research presents a novel approach using combined social media big data which can be extended to the field of tourism management,and has important implications to manage visitor patterns and to allocate resources efficiently to satisfy multiple objectives of park management.

利用SD法的国家公园森林景观美感评价--以武夷山国家公园为例

国家森林公园景观美感评价是景观美学研究重要内容之一。目前景观美感评价的研究基本集中在城市规划、园林绿化等领域,针对森林景观资源的美学评价也以总体评价研究为主,缺乏基于游客综合感知的森林景观美感评价相关研究。以武夷山国家公园作为研究对象,运用SD(semantic differential)法将森林美感受的评价项目归纳为14项,建立景观美感评价因子特征及总体满意度和美感受评分表,结合李克特5级量表,开展森林景观美感评价量化研究,分析人们对森林旅游的期望与追求标准。结果显示,人们对武夷山国家公园风景区的森林景观美感受整体呈现中上水平,对可视景观美感受大于听觉和嗅觉上的感受度,不同到访次数、年龄、学历人群对美感受满意度有差别。在森林旅游景观规划中,要加强可视景观打造,并从心理角度关注不同人群的需求和再访游客的审美心理变化。