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Resilience analysis of urban commercial area under the COVID-19 epidemic using night-time light remote sensing data.

Authors :
Huang, Shiman
Hu, Shirui
Hu, Qingwu
Chen, Qihao
Source :
Annals of GIS; Sep2024, Vol. 30 Issue 3, p345-366, 22p
Publication Year :
2024

Abstract

The global outbreak of the novel coronavirus has had a great impact on commercial areas, particularly in Wuhan, the first city in China affected by the epidemic. Exploring the changing pattern of these areas during the epidemic period is crucial for effectively restoring the urban economic level and promoting economic development on the basis of epidemic prevention and control in the post-epidemic era. The paper proposes a resilience analysis of urban commercial areas during the COVID-19 epidemic using time-series night-time light remote sensing data. Based on the constructed time-series night-time light remote sensing dataset and considering the urban impervious surface, the urban commercial area was extracted under multi-scale segmentation. Based on night-time light data before and after the epidemic, the resilience of representative commercial areas in Wuhan City, Hubei Province during the COVID-19 epidemic was analysed using a modified improved resilience assessment framework. The results showed that the lighting values of commercial areas and impervious areas decreased by up to 30% following the implementation of city lockdown measures. The change of light brightness in the commercial areas was more prominent, and the range of change is larger than that in the non-commercial areas. The lighting brightness of the commercial areas exhibited a significant downward trend throughout the entire lockdown period, and the downward trend will still remain for a period of time after unlocking. Among all the commercial areas, Wuguang commercial area demonstrated the highest recovery rate during the lockdown period and instantaneous recovery rate after the lockdown, with relatively low closure loss and the highest level of resilience. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19475683
Volume :
30
Issue :
3
Database :
Complementary Index
Journal :
Annals of GIS
Publication Type :
Academic Journal
Accession number :
179255348
Full Text :
https://doi.org/10.1080/19475683.2024.2390412