Global Harmonization of Urbanization Measures: Proceed with Care

Abstract

By 2050, two-thirds of the world's population is expected to be living in cities and towns, a marked increase from today's level of 55 percent. If the general trend is unmistakable, efforts to measure it precisely have been beset with difficulties: the criteria defining urban areas, cities and towns differ from one country to the next and can also change over time for any given country. The past decade has seen great progress toward the long-awaited goal of scientifically comparable urbanization measures, thanks to the combined efforts of multiple disciplines. These efforts have been organized around what is termed the "statistical urbanization" concept, whereby urban areas are defined by population density, contiguity and total population size. Data derived from remote-sensing methods can now supply a variety of spatial proxies for urban areas defined in this way. However, it remains to be understood how such proxies complement, or depart from, meaningful country-specific alternatives. In this paper, we investigate finely resolved population census and satellite-derived data for the United States, Mexico and India, three countries with widely varying conceptions of urban places and long histories of debate and refinement of their national criteria. At the extremes of the urban-rural continuum, we find evidence of generally good agreement between the national and remote sensing-derived measures (albeit with variation by country), but identify significant disagreements in the middle ranges where today's urban policies are often focused.

Keywords: built environment; demographics; economic geography; remote sensing; rural–urban continuum; spatial; spatial demography; urban economics; urbanness.

Figure A1.. India.

Effects of varying τ percentage thresholds in the interval (1, 99) on the likelihood of correct urban and rural land classifications and test sensitivity. By “correct”, we mean classifications that are in agreement with the official country-specific urban and rural designations. (a) India correct classification percentages by τ threshold. (b) India test sensitivity percentages by τ threshold.

Figure A2.. Mexico.

Effects of varying τ percentage thresholds in the interval (1, 99) on the likelihood of correct urban and rural land classifications and test sensitivity. By “correct”, we mean classifications that are in agreement with the official country-specific urban and rural designations. (a) Mexico correct classification percentages by τ threshold (b) Mexico test sensitivity percentages by τ threshold.

Figure 1.

Official urban and Degree of Urbanization (DoU) gridded layers. Examples are from (a) New Delhi, India; (b) Mexico City, Mexico; and (c) New York City, United States. All images show a portion of the surrounding area. Administrative boundaries are indicated in blue. These are districts, in the Indian case; municipios, for Mexico; and counties, in the United States.

Figure 2.

Mean built-up land density by urban–rural category and country. (a) Mean built-up densities by official urban–rural designation (2011 census year for India, 2010 for Mexico and the U.S.; 2014 GHSL estimate). (b) Comparison of means in the four-cell categorization of GHSL and the official designation. (c) Means by DoU category (2014 GHSL and 2015 DoU estimates).

Figure 3.

Official urban percentages by DoU class, calculated as the percentage of officially urban cells among all grid cells in each DoU class: (a) India, (b) Mexico and (c) United States. Official figures from 2011 census year for India, 2010 census years for Mexico and the United States. DoU estimate for 2015.

Figure 4.

Built-up land densities near New Delhi, India. Official classification for 2011 census year; 2014 GHSL estimate.

Figure 5.

Built-up land densities near Mexico City. Official classification for 2010 census year; 2014 GHSL estimate.

Figure 6.

Built-up land densities near New York City. Official classification for 2010 census year; 2014 GHSL estimate.

Figure 7.

Population densities in selected regions of the study countries. Settlement boundaries and population from the 2011 census year for India (panel (a)) and the 2010 census year for both Mexico (panel (b)) and the United States (panel (c)).

Figure 8.

Three-way cross-classifications of official urban–rural categories, GHSL–official cross-classification and DoU classes. Official figures from 2011 census year for India and 2010 census years for Mexico and the United States. GHSL estimate for 2014; DoU estimate for 2015, with classes shown in the order of Table 4.