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

doi:10.1007/s11676-024-01720-y

Abstract

Abstract:

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.

Key words: Tourism management, Social media big data, National parks, COVID-19, Geographical weighted regression

Dehui Christina Geng, Amy Li, Jieyu Zhang, Howie W. Harshaw, Christopher Gaston, Wanli Wu, Guangyu Wang. Exploring impacts of COVID-19 on spatial and temporal patterns of visitors to Canadian Rocky Mountain National Parks from social media big data[J]. JOURNAL OF FORESTRY RESEARCH, 2024, 35(1): 81-.

Dehui Christina Geng, Amy Li, Jieyu Zhang, Howie W. Harshaw, Christopher Gaston, Wanli Wu, Guangyu Wang. [J]. 林业研究(英文版), 2024, 35(1): 81-.

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