The Impacts of COVID-19 on the Rank-Size Distribution of Regional Tourism Central Places: A Case of Guangdong-Hong Kong-Macao Greater Bay Area

Abstract

It is well known that Zipf’s rank-size law is powerful to investigate the rank-size distribution of tourist flow. Recently, widespread attention has been drawn to investigating the impacts of COVID-19 on tourism for its sustainability. However, little is known about the impacts of COVID-19 on the rank-size distribution of regional tourism central places. Taking Guangdong-Hong Kong-Macao Greater Bay Area as a research case, this article aims to examine the fractal characteristics of the rank-size distribution of regional tourism central places, revealing the impacts which COVID-19 has on the rank-size distribution of regional tourism central places. Based on the census data over the years from 2008 to 2021, this paper reveals that before COVID-19, the rank-size distribution of the tourism central places in Guangdong-Hong Kong-Macao Greater Bay Area appears monofractal, and the difference in the size of the tourism central places has a tendency to gradually decrease; in 2020, with the outbreak of COVID-19, the characteristic of the rank-size distribution shows that the original monofractal is broken into multifractal; in 2021, with COVID-19 becoming under control, the structure of tourism size distribution, changes into bifractal based on the original multifractal, showing that the rank-size distribution of tourism central places in Guangdong-Hong Kong-Macao Greater Bay Area becomes more ideal and the tourism order becomes better than the last year. The results obtained not only fill in the gap about the impacts of COVID-19 on tourism size distribution, but also contribute to the application of fractal theory to tourism size distribution. In addition, we propose some suggestions to the local governments and tourism authorities which have practical significance to tourism planning.

Study on the temporal and spatial relationship between public health events and the development of air transport scale: A case of the Southwest China

“…COVID-19 cases and the passenger and freight volume of air transportation, as well as their changes, were used. The formula as Eq ( 1 ) [ 31 , 32 ]: where, P represents the scale, and R represents the rank order. K is the constant, while q is used to reflect the degree of concentration of the indexes.…”

“…COVID-19 cases and the passenger and freight volume of air transportation, as well as their changes, were used. The formula as Eq (1) [31,32]:…”

A Study of the Impact of COVID-19 on Urban Contact Networks in China Based on Population Flows

“…Resilient urban contact networks tend to remain stable when external shocks are relatively minor. Nevertheless, inter-city contact networks have undergone a process of fractalization, disintegration and remodeling in the face of pandemic shocks [8]. In the course of reshaping, the sensitivity of urban contact networks to the pandemic has equally demonstrated the intensity of urban resilience.…”

“…The results of numerous analyses of the externality of the development of the pandemic and exploration of the impact mechanisms demonstrate that the outbreak of the COVID-19 pandemic has brought about a tremendous impact on the development of cities and people's lives throughout the world while underlining the intimate and complicated relationship between population flows, urban contact and the pandemic [5][6][7][8].…”