A global map of travel time to cities to assess inequalities in accessibility in 2015

• Published in: Nature (London) Vol. 553; no. 7688; pp. 333 - 336
• Main Authors: Weiss, D. J., Nelson, A., Gibson, H. S., Temperley, W., Peedell, S., Lieber, A., Hancher, M., Poyart, E., Belchior, S., Fullman, N., Mappin, B., Dalrymple, U., Rozier, J., Lucas, T. C. D., Howes, R. E., Tusting, L. S., Kang, S. Y., Cameron, E., Bisanzio, D., Battle, K. E., Bhatt, S., Gething, P. W.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 18.01.2018; Nature Publishing Group
• Subjects: 704/844/685; 706/134; 706/2808; Accessibility; Cities; Cities - statistics & numerical data; Cities and towns; Demographic aspects; Development policy; Earth science; Economics; Educational Status; Equality; Evaluation; Geography; Ground transportation; Health Status; Healthcare Disparities - statistics & numerical data; Human motion; Humanities and Social Sciences; Humans; Income; Infrastructure; Internationality; letter; Maps as Topic; Measurement; multidisciplinary; Population; Roads & highways; Science; Socioeconomic Factors; Spatial discrimination; Spatial distribution; Spatial resolution; Spatio-Temporal Analysis; Studies; Sustainable development; Time Factors; Transportation networks; Travel; Travel - statistics & numerical data; Travel time; Travel time (Traffic engineering); Urban Population - statistics & numerical data; United Kingdom
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/nature25181

Travel time to cities in 2015 is quantified in a high-resolution global map that will be useful for socio-economic policy design and conservation research. The roads to equality Resources that sustain human wellbeing, such as education, jobs and health services, are distributed unequally, with higher concentrations in dense urban areas. Increasing access to such opportunities and services is a key factor in the advancement of fair and sustainable development. Integrating multiple large data sources for road and city geography, Daniel Weiss and colleagues have created a high-resolution global map that quantifies travel time to cities in the year 2015. This map provides a detailed view of the heterogeneity in accessibility to cities around the world, serving not just as a potential indicator for development but also as an input for future models in areas such as conservation biology. The economic and man-made resources that sustain human wellbeing are not distributed evenly across the world, but are instead heavily concentrated in cities. Poor access to opportunities and services offered by urban centres (a function of distance, transport infrastructure, and the spatial distribution of cities) is a major barrier to improved livelihoods and overall development. Advancing accessibility worldwide underpins the equity agenda of ‘leaving no one behind’ established by the Sustainable Development Goals of the United Nations 1 . This has renewed international efforts to accurately measure accessibility and generate a metric that can inform the design and implementation of development policies. The only previous attempt to reliably map accessibility worldwide, which was published nearly a decade ago 2 , predated the baseline for the Sustainable Development Goals and excluded the recent expansion in infrastructure networks, particularly in lower-resource settings. In parallel, new data sources provided by Open Street Map and Google now capture transportation networks with unprecedented detail and precision. Here we develop and validate a map that quantifies travel time to cities for 2015 at a spatial resolution of approximately one by one kilometre by integrating ten global-scale surfaces that characterize factors affecting human movement rates and 13,840 high-density urban centres within an established geospatial-modelling framework. Our results highlight disparities in accessibility relative to wealth as 50.9% of individuals living in low-income settings (concentrated in sub-Saharan Africa) reside within an hour of a city compared to 90.7% of individuals in high-income settings. By further triangulating this map against socioeconomic datasets, we demonstrate how access to urban centres stratifies the economic, educational, and health status of humanity.