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A critical look at representations of urban areas in global maps

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Abstract

According to the UN, the number of urban dwellers is expected to increase from roughly 3.2 billion today to more than 4.9 billion by 2030. An accurate and regularly updated estimate of the extent and spatial distribution of urban land is an important first step in our search for realistic responses to the ecological and social consequences of what promises to be the most rapid urbanization in world history. By employing circa-2000 satellite remote sensing imagery, geographic information systems, and census data, six groups from government and academia in both the EU and the US have created global maps that can be used to describe urban land. We compare these maps from global to sub-national scales, for the first time applying Discrete Global Grids to the problem of global-scale map comparison. Although most of these maps share common data inputs, they differ by as much as an order of magnitude in their estimates of the total areal extent of the Earth’s urban land (from 0.27 to 3.52 million km2). A sub-national analysis of the spatial distribution of urban land reveals that inter-map correlations are highest in North America ( \( \ifmmode\expandafter\bar\else\expandafter\=\fi{r} \) = 0.90), intermediate in Europe, South and Central America, and Sub-Saharan Africa (\( \ifmmode\expandafter\bar\else\expandafter\=\fi{r} \) = 0.78), and lowest in Asia (\( \ifmmode\expandafter\bar\else\expandafter\=\fi{r} \) = 0.63). Across most regions, our analysis uncovers a degree of variance that is high enough to call into question the consistency of each group’s approach to urban land, pointing to the need for both a common urban taxonomy and a global urban assessment effort.

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Notes

  1. The level of urbanization describes the fraction of a population living in urban areas. Urban expansion refers to an increase in the areal extent of urban land.

  2. The DMPS-OLS satellite is sensitive to radiation in the visible-near infrared region of the electromagnetic spectrum (0.44–0.94 μm). Light intensity is encoded in 6-bit digital numbers.

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Acknowledgments

This research was made possible in part by the Department of Energy Computational Science Graduate Fellowship (GSGF) and Princeton University’s Office of Population Research (OPR). We’d like to thank Professor Shlomo Angel of New York University for his thoughtful comments and suggestions at all stages of this work. Thanks also to Professors Doug Massey and Burt Singer of Princeton’s Office of Population Research for their comments, as well as the recommendations of three anonymous reviewers.

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  1. Office of Population Research, Princeton University, 207 Wallace Hall, Princeton, NJ, 08544, USA

    David Potere

  2. Geography Department and the Institute for Computational Earth System Science, University of California at Santa Barbara, 5703 Ellison Hall, Santa Barbara, CA, 93106-4060, USA

    Annemarie Schneider

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Potere, D., Schneider, A. A critical look at representations of urban areas in global maps. GeoJournal 69, 55–80 (2007). https://doi.org/10.1007/s10708-007-9102-z

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