Weiss, D., Nelson, A., Gibson, H. et al. A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature 553, 333–336 (2018).

Objective:

• Provide an a fine-grained quantification of accessibility worldwide
• Narrow gaps in oppotunity by improving accessibility for remote populations and/or reducing disparities between populations with differing degrees of connectivity to cities

Case:

• 13,840 global cities
• 1 km * 1 km

Methodology:

• travel time to the nearest city: least-cost-path
• Road and railroad speed: OSM
• River: CIA world data bank 2 vector rivers dataset
• Automotic identification system and the Voluntary Observing Ship
• Walking: survey
• Speed is adjusted with slope
• Google Earth Engine
• Validation:
• R2: 0.66
• Mean absolute error: 20.7 min

Data Source: Open

• Open Street Map: (Roads, railroads, rivers, bodies of water, topographical conditions, land cover, national borders (GAUL))
• Google roads database
• Global Human Settlement Grid of high-density land cover (represent cities)
• Demographi and Health Survey: 52 countries
• Inland water bodies: global surface-water occurrence dataset
• Centres: contiguous cells with a density of at least 1,500 inhavitants, or a density of built-up greater than 50% and a minimum of 50,000 inhabitants

Findings:

• Highly accessible areas include those with abundant transport infrastructure and/or many spatially disaggregated cities

• 80.7% of people reside within one hour of cities, but accessibility is not qually distributed across the development spectrum. The disparity is evident when comparing accessibility for income groups (World Bank)

• Association with education and treatment fever among children under five

Coding Reference:

• Code
• Result 1
• Result 2