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Urban dynamics through the lens of human mobility.
Xu, Yanyan; Olmos, Luis E; Mateo, David; Hernando, Alberto; Yang, Xiaokang; González, Marta C.
Afiliación
  • Xu Y; MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China.
  • Olmos LE; Department of City and Regional Planning, University of California, Berkeley, CA, USA.
  • Mateo D; Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
  • Hernando A; Department of City and Regional Planning, University of California, Berkeley, CA, USA.
  • Yang X; Facultad de Ciencias Básicas, Universidad de Medellín, Medellín, Colombia.
  • González MC; Kido Dynamics SA, Lausanne, Switzerland.
Nat Comput Sci ; 3(7): 611-620, 2023 Jul.
Article en En | MEDLINE | ID: mdl-38177741
ABSTRACT
The urban spatial structure represents the distribution of public and private spaces in cities and how people move within them. Although it usually evolves slowly, it can change quickly during large-scale emergency events, as well as due to urban renewal in rapidly developing countries. Here we present an approach to delineate such urban dynamics in quasi-real time through a human mobility metric, the mobility centrality index ΔKS. As a case study, we tracked the urban dynamics of eleven Spanish cities during the COVID-19 pandemic. The results revealed that their structures became more monocentric during the lockdown in the first wave, but kept their regular spatial structures during the second wave. To provide a more comprehensive understanding of mobility from home, we also introduce a dimensionless metric, KSHBT, which measures the extent of home-based travel and provides statistical insights into the transmission of COVID-19. By utilizing individual mobility data, our metrics enable the detection of changes in the urban spatial structure.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Pandemias / COVID-19 Límite: Humans Idioma: En Revista: Nat Comput Sci Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Pandemias / COVID-19 Límite: Humans Idioma: En Revista: Nat Comput Sci Año: 2023 Tipo del documento: Article País de afiliación: China