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作者

Xiaoyan Liu;Saini Yang;Xiao Huang;Rui An;Qiangqiang Xiong;Tao Ye

来源

CITIES,Vol.133,Issue1,Article 104104

语言

英文

关键字

COVID-19;Recovery quantification;Human mobility;Sustainable urban development

作者单位

State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Beijing Normal University, Beijing 100875, China;Key Laboratory of Environmental Change and Natural Disasters, Ministry of Education, Beijing Normal University, Beijing 100875, China;School of National Safety and Emergency Management, Beijing Normal University, Beijing 100875, China;Department of Geosciences, University of Arkansas, Fayetteville 72762, USA;School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China;Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing 100875, China;Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China;State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Beijing Normal University, Beijing 100875, China;Key Laboratory of Environmental Change and Natural Disasters, Ministry of Education, Beijing Normal University, Beijing 100875, China;School of National Safety and Emergency Management, Beijing Normal University, Beijing 100875, China;Department of Geosciences, University of Arkansas, Fayetteville 72762, USA;School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China;Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing 100875, China;Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

摘要

The COVID-19 pandemic has brought huge challenges to sustainable urban and community development. Although some recovery signals and patterns have been uncovered, the intra-city recovery process remains underexploited. This study proposes a comprehensive approach to quantify COVID-19 recovery leveraging fine-grained human mobility records. Taking Wuhan, a typical COVID-19 affected megacity in China, as the study area, we identify accurate recovery phases and select appropriate recovery functions in a data-driven manner. We observe that recovery characteristics regarding duration, amplitude, and velocity exhibit notable differences among urban blocks. We also notice that the recovery process under a one-wave outbreak lasts at least 84 days and has an S-shaped form best fitted with four-parameter Logistic functions. More than half of the recovery variance can be well explained and estimated by common variables from auxiliary data, including population, economic level, and built environments. Our study serves as a valuable reference that supports data-driven recovery quantification for COVID-19 and other crises.