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

Abstract

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. 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, 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.

Effectiveness of protected areas in conserving tropical forest birds

“…We characterised each site according to five characteristicscalculated in a 1-km radius buffer around its coordinatestwo binary and three continuous: protected (if coordinates fall within a protected area 47 ; Extended Fig. 5) versus non-protected; forest (if > 60% of the 1 km buffer around the point is forested 48 ) versus non-forest (< 10% forested; sites with intermediate forest cover were removed from analyses); altitude 49 ; agricultural suitability 50 ; and remoteness 51 . In addition, we classified each forest site according to three continuous variables: canopy height 52 ; forest contiguity (proportion of forest cover 48 , 0.6 to 1); and wilderness level (opposite of human footprint 53 ).…”

Measuring the spatial heterogeneity on the reduction of vaginal fistula burden in Ethiopia between 2005 and 2016

“…To account for disparities between rural and urban, we used gridded maps of urban accessibility obtained from the European Commission Joint Research Centre Global Environment Monitoring Unit (JRC) 28 and from the Malaria Atlas project 29,30 for 2000 and 2015, respectively ( Figure S6, Supplementary information). Accessibility is time (minutes) taken to travel from a grid cell in the map to a city using land-based travel and employing the minimum cost.…”

Potential Impacts of China 2030 High-Speed Rail Network on Ground Transportation Accessibility

“…Travel time is a widely used measure for accessibility, which reflects the ease of travel as determined by the quality of service provided by the transportation [23,30]. We employed a door-to-door approach to calculate times associated with every stage in a journey between origin and destination [31].…”

“…The study area (entire China) was divided into raster grid cells with a spatial resolution of 1 km [30] and the cell value indicated the time spent to traverse a cell. The cell value was calculated as Cost = 100/V × 60, where Cost is the travel time (min per 100 km) and V calculated based on following speed settings: 90, 70, 50 and 20 km/h for the expressway, national highway, provincial and county highway and other roads, respectively ( Figure 5a).…”