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

作　　者：Dehui Christina Geng Amy Li Jieyu Zhang Howie W.Harshaw Christopher Gaston Wanli Wu Guangyu Wang 

机构地区：[1]National Park Research Centre,Faculty of Forestry,University of British Columbia,Vancouver V6T 1Z4,Canada [2]Faculty of Applied Science,University of British Columbia,Vancouver V6T 1Z3,Canada [3]Paul G.Allen School of Computer Science&Engineering,University of Washington,Seattle,WA 98195,USA [4]Faculty of Kinesiology,Sport,and Recreation,University of Alberta,Edmonton T6G 2J9,Canada [5]Department of Wood Science,Faculty of Forestry,University of British Columbia,Vancouver V6T 1Z4,Canada

出　　处：《Journal of Forestry Research》2024年第4期13-33,共21页林业研究（英文版）

基　　金：This research was supported by the UBC APFNet Grant(Project ID:2022sp2 CAN).

摘　　要：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.

关 键 词：Tourism management Social media big data National parks COVID-19 Geographical weighted regression 

分 类 号：F597.11[经济管理—旅游管理]