Spatio-temporal analysis of the covid-19 impacts on the using Chicago urban shared bicycles by tensor-based approach

 Cycling is a phenomenon in urban transportation that has the ability to allocate a specific location at any moment in time. Accordingly, spatial analysis of bicycle trips can be accompanied by temporal analysis. The use of a GIS environment is commonly recommended to display the extent of the phenomenon's spatial changes. However, in order to apply and display changes over time, it will require the production of other layers of information. In this study, it is possible to simultaneously display spatial and temporal information by tensor concept and tool. Using this tool, the ability to display and analyze a high volume of spatial information with the power of temporal resolution is created due to the simultaneous representation of information layers. This study tries to investigate spatial and temporal analyses at the same time using the concept of tensor to understand how users request Chicago's shared bikes at different times of the day. In addition, the number of bicycle trips over time, along with the amount of reduction and increase in trips from the neighborhoods, are studied separately from a spatial point of view. The results of this study show that the April 2020 coronavirus outbreak in Chicago resulted in a 68.4% decrease in the use of shared bicycles in the city compared to the same period in 2019. This rate was associated with a 64.3% decrease in the more detailed survey for the holidays of this month and 72.6% on normal and non-holiday days. Spatial attitude also shows that in April 2020, central neighborhoods experienced the greatest reduction in the use of shared bicycles. In addition, after the spread of the disease, requests to use bicycles from the same origins and destinations have increased.