Measuring social resilience in cities: An exploratory spatio-temporal analysis of activity routines in urban spaces during Covid-19

Abstract

Covid-19 has dramatically changed life in cities across the globe. What remains uncertain is how national policies and appeals to comply with suggested rules translate to changes in the behaviour of citizens in urban areas. This lack of local knowledge leaves urban policy makers and planners with few clues as to the determinants of social resilience in cities during protracted crises like a pandemic. Methods are required to measure the capacity of people to conduct routine activities without risking exposure to a prevalent disease, particularly for those most vulnerable during a health crisis. By spanning the fields of urban resilience, human geography, mobility studies and the behavioural sciences, this study explores how to measure social resilience in cities during a protracted crisis. Using a public participation GIS online platform, we observe changes in citizen behaviour within urban spaces during the Covid-19 pandemic. Inhabitants from three districts of a Dutch city mapped their activity routines during the lockdown period and during the year before the pandemic. Spatio-temporal analysis reveals changes in the clustering of activities into what we describe as 'activity bubbles'. We reflect on the influence of the urban space on these changes and assess the contribution of this exploratory research methodology for gaining insights into behavioural change. Implications for urban planning and resilience theory are discussed.

Keywords: Activity bubbles; PPGIS; Protracted crisis; Social capital; Urban space.

Fig. 1

3-Layer conceptual framework depicting key theoretical concepts (in all caps) and their operationalization.

Fig. 2

Study area and three case districts in the city of The Hague, the Netherlands.

Fig. 3

Activity routine section of the survey showing the during Covid-19 period routine activity options and window with follow-up questions.

Fig. 4

Average temporal weekday activity pattern - timing β. The x-axis represents time, an hour of the day, and the y-axis shows the % of people doing an activity at the given hour on an average over all week days.

Fig. 5

Activity duration γ. How much time respondents from a district (column) spend on a certain activity (row) on an average over all week days.

Fig. 6

Travel distances δ. Haversine distances between residents' homes and destinations by activity category. The colour of the boxplots represents the period: pre-pandemic 2020 or pandemic 2021.

Fig. 7

Spatial activity bubbles E. The radius of each bubble is calculated from the travel distances aggregated by category: red - 25 % percentile, orange - median, and blue - 75 % percentile. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)