Travel Time to Major Market Cities

The travel time maps indicate the degree of accessibility from a pixel to a populated place. The patterns shown here describe the geographic accessibility between places in Sub-Saharan Africa. We define accessibility as the time in hours required to travel from a given single point (1x1km pixel) to the nearest market center. Travel time to market centers is used as a proxy for market accessibility and shows the likely extent to which farming households are physically integrated with or isolated from markets.

It is important to farming households and other producers to have access to markets in order to trade/sell their goods. The more accessible markets are to the given population, the greater the population’s ability to remain economically self sufficient and maintain food security. These travel time maps indicate the degree of accessibility from a pixel to a populated place. The patterns shown here describe the geographic accessibility between places in Sub-Saharan Africa (SSA). We define accessibility as the time in hours required to travel from a given single point (1x1km pixel) to the nearest market center. Travel time to market centers is used as a proxy for market accessibility and shows the likely extent to which farming households are physically integrated with or isolated from markets.  Our travel time approach is estimated based on the combination of different global spatial data layers which represent the time required to cross each single point.

Accessibility is determined using a cost distance function to measure the ‘cost’ in time (hours) to the nearest market for each 1km pixel. The ‘friction’ or adjusted speed is based on a number of input variables, including: road locations, road type, elevation, slope, country boundaries, water bodies, & land cover. Each input variable was converted to a value representing the time it takes to travel 1 km. For example,  paved roads were given a value of 60km/hour whereas gravel roads may be given a value of 15km/hour. Water, landcover, slope, country boundaries, and elevation were used to modify the speed of travel (e.g. steeper areas were assigned slower speeds). The results are not intended to be accurate travel times between places but serve only as estimates of accessibility. To be accurate, we would need to have much better road data and more accurate assessments of average travel times over each component of the friction surface. Even then, it is doubtful that this could be achieved on a global scale. However, we would be very interested to know how the current travel times in the access surface relate to known travel times between locations.

Data

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Maps

References

• Nelson, A. 2000. Accessibility, transport and travel time information. CIAT Hillsides Project Report, CIAT, Cali, Colombia. pp 16.
• Nelson, A. 2008. Travel time to major cities: A global map of Accessibility. Global Environment Monitoring Unit - Joint Research Centre of the European Commission, Ispra Italy. Available at http://gem.jrc.ec.europa.eu/
• Nelson, A. and Leclerc, G. 2007. A spatial model of accessibility: Linking population and infrastructure to land use patterns in the Honduran Hillsides. In Hall, C. and Leclerc, G. (eds), Making World Development Work: Scientific Alternatives to Neoclassical Economic Theory. University of New Mexico Press, Alburquerque, NM. USA.

 

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