Analysis of the spatial-temporal characteristics of residents' commuting trips under the impact of COVID-19: a case study in Shenzhen

During the outbreak of COVID-19, many cities adopted strict travel measures to quickly cut off the transmission chain. However, these measures hindered the development of the urban economy as time passed. In the face of the possible recurrence of the epidemic, how to develop reasonable operational measures to ensure commute trips and guarantee the normal operation of the urban economy has become an important issue facing the current transportation system. Therefore, this paper is based on the smart card data to explore the spatial-temporal characteristic changes of residents' commuting under the influence of the epidemic. Firstly, the temporal characteristics of each epidemic period are described from three dimensions. Then, travel hotspots are identified and the spatial distribution changes of them in each epidemic period are explored. Next, the correlation coefficient between hotspot metro stations and surrounding land use is calculated. Finally, the rules are summarized, and operational suggestions are proposed. This article analyzes the commuting characteristics of residents based on smart card data, which can provide data support for optimizing metro operation measures.