Simulating crowding of urban green areas to manage access during lockdowns.

During the COVID-19 emergency, cities around the world introduced measures to guarantee physical distancing that restricted access to urban parks and green areas, with potentially negative effects on citizens' health and wellbeing. This study aims at providing insights to manage access to urban green space in physical distancing times, when the risk of crowding should be avoided. Using the city of Trento (Italy) as a case study, the study simulates policy scenarios corresponding to different restrictions and assesses their effects on green space access and crowding. Policy scenarios are obtained by combining different distances that people are allowed to travel, different types of green areas available for public use (only urban parks or parks and schoolyards), and different target populations (all residents or only people with no private gardens). The results unveil the trade-off between access and crowding of green areas, and can be used to suggest policy interventions and regulations that can be adopted in an emergency. Particularly, the study shows that: i) The relationship between distance threshold and the percentage of people with access to green areas is non-linear, and this should be carefully considered when proposing travel restrictions; ii) Changing the maximum travel distance does not produce major effects on the number of crowded green areas, hence additional or alternative measures need to be adopted; iii) Off-the-shelf measures, such as opening schoolyards, are beneficial and can be implemented rapidly in an emergency. Finally, the study reveals "hotspots" of green space deprivation/overcrowding in the city that should be addressed by urban planning to ensure that green space continues to benefit citizens also during emergency conditions.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2021 The Author(s).)