# **1. Introduction**

What is a city? The most candid answer may be “I know one when I see it.” The subjectivity of the city concept is understandable because of the continuum between urban and rural spaces. The many terms used to describe this in‐betweensuburb, exurb, edge city, and urban sprawl, among otherstestifies to the absence of a clear divide. Just like beauty, a city is in the eyes of the beholder.

Official answers to this question are less straightforward, varying substantially across national governments and international organizations. A glimpse at this diversity is provided by World Urbanization Prospects, a comprehensive source of international urban data that builds primarily on official information. About 45 percent of the 232 countries reported in its 2014 revision used each country’s own administrative definition as the sole or primary criterion for distinguishing urban from rural. Some 27 percent used population size as the sole criterion, and another 25 percent adopted a combination of metrics. The remaining 3 percent of countries had no official definition (UN 2015). Moreover, many countries change their definitions of cities periodically.

Not surprisingly, this diversity of criteria results in a lack of consensus on which urban agglomerations should be considered cities. It is thus not clear how urban areas can be compared across countries and over time.

This seemingly trivial issue has important implications. The rural‐urban transformation drives economic development and is often intertwined with structural transformation. Because cities create prosperity by bringing together households and firms and making everyone more productive, the rural‐urban transformation is central to development economics, and cities are at the core of economic geography (Fujita, Krugman, and Venables 2001; Henderson 1974; Krugman 1991; Lewis 1954).

However, the difficulties in identifying urban areas have undermined empirical efforts to connect with the theoretical literature and even to establish the stylized facts with confidence. For example, it is widely accepted that a country’s urban population share is related to its income per capita. And it is also said that India’s urban population share is too low relative to its income level. However, some studies suggest that many areas of India are misclassified as rural by the official definition, and so the level of urbanization is underestimated (Denis and Marius‐Gnanou 2011; World Bank 2013).

This disconnect is unlikely to occur only in India. At the global level, the diversity of urban metrics could challenge regularities taken for granted. For example, it could well be that urbanization rates are more accurate in agrarian societies and in advanced economies but underestimated in between these two extremes. If so, the relationship between the urban population share and income per capita would have a different gradient relative to what is commonly accepted.

Recognition of this measurement problem has led to alternative approaches to defining the urban extent in ways that could ensure comparability across countries and over time. One approach is to rely on information from the ground, such as highly disaggregated data from population and economic censuses. An example of this more systematic approach is the paper by Rozenfeld and others (2011) on the Great Britain and the United States.

Another promising approach is the use of remote sensing technology to identify urban areas from outer space. A number of methods that rely on images taken by sensors aboard satellites have been proposed in this respect. Methods to identify cities from outer space can be broadly classified into three groups, 2