Frozen city: Analysing the disruption and resilience of urban activities during a heavy snowfall event using Google Popular Times

Abstract

Understanding the impact of climate change on cities is fundamental to address the increasing occurrence of extreme weather events. This research aims to raise awareness and emphasise the need and potential of proactive measures to mitigate the adverse effects of climate change. To do so, this article conducts a case study for a huge snowfall that occurred in the city of Madrid (Spain) in January 2021, blocking the city for several days. The analysis is based on geolocated big data sourced from Google Popular Times (GPT), which captures the occupancy of establish ments throughout the city over the entire study period. An exploratory spatial-temporal analysis has been conducted to examine the impact of the snowfall on the daily activities of the city, taking into consideration the demographic characteristics. The findings reveal a distinction in the impact of the snowfall on activities. Essential activities experience less impact compared to leisure ac tivities. Furthermore, at the socio-economic level, the impact on low-income neighbourhoods is observed to be less affected than on high-income neighbourhoods. The implications of this research contribute to the body of knowledge on climate change resilience and adaptation, providing valuable insights for urban management strategies and informing future research in this field.