For 3.4 billion people living in rural areas, the size of nearby cities and towns and the travel time to reach them are critical. They affect the extent of services and opportunities available as well as their accessibility. A freely downloadable GIS dataset – the Urban–Rural Catchment Areas (URCAs) – shows the diversity of urban-rural systems worldwide and the importance of the links between cities of different sizes and their surrounding rural areas.[1]
The URCA can be explored online on the FAO Hand-in-Hand Geospatial Platform.[2]
Urban–Rural Catchment Area Classifications
The URCA classifies urban centers by population size – large, intermediate and small cities and towns. Their influence into rural areas – “catchment areas” – outside of the built environment are then mapped by categorizing each rural pixel if it is within 1 hour, 1 to 2 hours, and 2 to 3 hours travel to the edge of an urban area.
Rural areas over 3 hours away from a town of at least 20,000 inhabitants are considered as hinterland. Similarly, very small towns over 3 hours from an urban center of at least 20,000 inhabitants are considered “dispersed towns”. The classification is based on a hierarchy of urban centers by population size (largest to smallest) to determine which center is the point of reference for a given rural location: proximity to a larger center dominates over a smaller one in the same travel time category.
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The rural pixels are matched with an urban center of reference using the most updated version[3] of the least-cost-path algorithm that was presented in the Global Map of Access to Cities in 2015[4]. This method determines the time required to travel across each 1-km pixel of the world’s surface.
A continuum from urban to rural can be seen in the map, as shown below. The darkest colors represent urban centers. Each catchment is color coded for city size: black for large cities; blue for intermediate; and orange for small cities and towns. The darker the color of a given rural location, the more easily connected it is to an urban center.
In the PNAS article launching the URCA, it emerges that the influence of large cities over rural areas may be less than often perceived. By coupling the URCA with the GHS Population grid (GHS-POP)[5] for the year 2015, the researchers estimated that on average only 14 percent of the global population lives within the catchment areas of large cities. This is opposed to the one-third of the global population that lives in rural catchment areas of intermediate and small cities and towns. In low-income countries, this is nearly 45 percent of the population. Around the world, only 1 percent of the population lives in dispersed towns or the hinterland.
To provide further granularity, the downloadable catchment areas are disaggregated into 7 urban center sizes that range from large cities with i) populations greater than 5 million and ii) between 1 to 5 million; intermediate cities with iii) 500,000 to 1 million and iv) 250,000 to 500,000 inhabitants; small cities with populations v) between 100,000 and 250,000 and vi) between 50,000 and 100,000; and vii) towns of between 20,000 and 50,000 people.[6]
The Urban-Rural Catchment Areas dataset is a major step in moving away from the traditional urban-rural dichotomy. Until now, this type of detailed breakdown existed for only a handful of high per-capita income countries, such as in the United States Urban-Rural Continuum Codes which applies a similar breakdown at the county-level.[7]
The URCA is unique in its gridded approach and offers a consistent methodology that provides comparable results across 190 countries. The dataset can be applied in a variety of disciplines where a person’s place of residence is an important factor, such as poverty reduction, food systems, health, and education.
References
[1] Related journal article: Cattaneo, A., Nelson, A. and McMenomy, T., 2021. Global mapping of urban–rural catchment areas reveals unequal access to services. Proceedings of the National Academy of Sciences, 118(2).http://dx.doi.org/10.1073/pnas.2011990118
[2] Accessing the dataset interactively from the FAO Hand-in-Hand Geospatial Platform: https://data.apps.fao.org/?share=g-3c88219e20d55c7ce70c8b3b0459001a
[3] Weiss, D. J., Nelson, A., Vargas-Ruiz, C. A., Gligorić, K., Bavadekar, S., Gabrilovich, E., … & Gething, P. W. (2020). Global maps of travel time to healthcare facilities. Nature Medicine, 26(12), 1835-1838. https://doi.org/10.1038/s41591-020-1059-1
[4] Weiss, D. J., Nelson, A., Gibson, H. S., Temperley, W., Peedell, S., Lieber, A., … & Gething, P. W. (2018). A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature, 553(7688), 333-336.https://doi.org/10.1038/nature25181
[5] Schiavina, M., Freire, S. and MacManus, K., Data from “GHS-POP R2019A – GHS population grid multitemporal (1975-1990-2000-2015).” Joint Research Centre Data Catalogue. http://data.europa.eu/89h/0c6b9751-a71f-4062-830b-43c9f432370f.
[6] Accessing the dataset from figshare: https://figshare.com/articles/dataset/Urban-rural_continuum/12579572/4
[7] Related dataset: United States Urban-Rural Continuum Codes https://www.ers.usda.gov/data-products/rural-urban-continuum-codes.aspx
About the Author
Theresa McMenomy is an economist for the Food and Agriculture Organization of the United Nations where she contributes to the research and writing of the annual flagship publication, The State of Food and Agriculture. She has an undergraduate degree from the University of Minnesota, Morris in Latin American Studies and Spanish and Portuguese and a masters in Agriculture, Food and the Environment from Tufts University Friedman School of Nutrition Science and Policy.
