This paper develops a novel approach to identify areas of interest based on the degree of complementarity of digital activities, available amenities, and population levels.
We employed a series of multilevel models to explore the within and between city variations in the relationship across ethnic segregation, and key socioeconomic and built environment features of neighbourhoods.
Existing empirical work has focused on assessing the effectiveness of non-pharmaceutical interventions on human mobility to contain the spread of COVID-19. Less is known about the ways in which the COVID-19 pandemic has reshaped the spatial patterns of population movement within countries. Anecdotal evidence of an urban exodus from large cities to rural areas emerged during early phases of the pandemic across western societies. Yet, these claims have not been empirically assessed. Traditional data sources, such as censuses offer coarse temporal frequency to analyse population movement over short-time intervals. Drawing on a data set of 21 million observations from Facebook users, we aim to analyse the extent and evolution of changes in the spatial patterns of population movement across the rural-urban continuum in Britain over an 18-month period from March, 2020 to August, 2021. Our findings show an overall and sustained decline in population movement during periods of high stringency measures, with the most densely populated areas reporting the largest reductions. During these periods, we also find evidence of higher-than-average mobility from highly dense population areas to low densely populated areas, lending some support to claims of large-scale population movements from large cities. Yet, we show that these trends were temporary. Overall mobility levels trended back to pre-coronavirus levels after the easing of non-pharmaceutical interventions. Following these interventions, we also found a reduction in movement to low density areas and a rise in mobility to high density agglomerations. Overall, these findings reveal that while COVID-19 generated shock waves leading to temporary changes in the patterns of population movement in Britain, the resulting vibrations have not significantly reshaped the prevalent structures in the national pattern of population movement.
We provide high resolution estimates (450m2) of spatio-temporal changes in urban energy consumption in response to COVID-19.
The report seeks to summarise the views of the experts participants in the use of mobility data in the contect of urban science.
Data have become a central pillar of society. Technological advances in computational power, storage and network platforms have enabled the production, processing, analysis and storage of large volumes of digital data. Information that previously could not be stored, or captured can now be digitally recorded. Digital data have become a key asset for government, businesses and individuals supporting their decision making processes and shaping human behaviour. A notable example has been the use of digital data to monitor the COVID-19 pandemic and inform the development of appropriate interventions. A key data stream has been location data from mobile phones. These data have enabled monitoring the geographic spread of COVID-19 in near-real time with technological companies, such as Apple and Google releasing regular mobility reports. More generally, mobile phone data are a rich source of information offering a unique opportunity to capture human behaviour at an unprecedented geographic and temporal resolution. Yet, key challenges remain, such as issues about privacy, representativeness, biases and the use of large, noisy and complex data sets.
We use mobile phone, census, and volunteered geographical data to measure geographic variations in the relationship between origin-destination flows and local urban accessibility in Barcelona
This paper investigates the spatial choices of overseas graduates from Australian Higher Education Institutions for employment after graduation.