Measuring Ambient Populations during COVID in Leeds City Centre

Measuring Ambient Populations during COVID in Leeds City Centre

The COVID-19 pandemic caused a significant amount of disruption when lockdown measures were enforced, closing schools, non-essential retail, entertainment, leisure and hospitality services across the country.  With legal restrictions on non-essential travel and a mandate to work from home where possible, the UK effectively ground to a halt for all but key workers.  As lockdown policies were designed to prevent transmission of the virus by reducing social contact, a reduction in pedestrian volumes (the ‘ambient population’) of large urban areas was not only to be expected but a key goal in the government’s strategy.

With cities and other urban centres projected to hold approximately 68% of the global population by 2050, quantifying their ambient population is an important factor in ensuring that accurate socio-economic and environmental insights are developed.  Advances in technology have resulted in the availability of a wide range of mobility data.  Cameras positioned in areas of interest harness machine learning to count individual footfall, whilst most smartphones have access to satellite tracking services (such as GPS) that allow organisations such as Google and Apple to produce aggregated mobility reports.

This project builds on existing work conducted on estimating the ambient population in and around Leeds City Centre.  Several datasets are available that could be used to quantify pedestrian volumes:

 

The aim is to explore these in the context of the impacts of COVID-19 related policies, such as national and local lockdowns.  The expected outputs are a critical analysis of the use of these data to determine the impact of lockdown policies within Leeds, a data product that provides aggregate measures of ambient population over time, and research into suitable predictive models that could be used to quantify the difference in footfall that would have been expected without restrictions.