Understanding mobility dynamics using urban functions during the COVID-19 pandemic: comparison of pre-and post-new normal eras

Creative Commons License

Hayrullahoglu G., VAROL ÖZDEN Ç.

ASIA-PACIFIC JOURNAL OF REGIONAL SCIENCE, vol.6, no.3, pp.1087-1109, 2022 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 6 Issue: 3
  • Publication Date: 2022
  • Doi Number: 10.1007/s41685-022-00247-6
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus
  • Page Numbers: pp.1087-1109
  • Keywords: Community mobility, COVID-19, Urban functions, Artificial neural network, ARTIFICIAL NEURAL-NETWORK, COMMUNITY MOBILITY, PHONE, PARAMETERS, COMPLEXITY, PATTERNS
  • Gazi University Affiliated: Yes


Several changes in urban mobility patterns have been observed in response to COVID-19 since March 2020 when the World Health Organization (WHO) declared COVID-19 a pandemic. However, whether mobility changes are entirely pandemic related has not been investigated for each urban function. This paper evaluates the potential determinants of urban mobility changes for six different urban functions during the COVID-19 pandemic via community mobility data collected by Google. Using artificial neural networks (ANN), the dynamics that affect mobility changes in the following urban functions; grocery/pharmacy, residential, parks, retail/recreation, transport stations, and workplaces, were analysed for cankaya, one of the densest districts in the capital of Turkey. Results of the prediction model show that responses to the pandemic differed considerably by urban function. Before the new normal era, changes in urban mobility trends were strongly dependent on the pandemic as a public health threat and represented by restrictive government measures. However, impacts of the pandemic on intracity mobility decreased in the new normal era when rules were relaxed. These results are useful for developing proactive policies to ensure rapid post-pandemic recovery in urban economics and planning.