multiple large urban centers in proximity along with their hinterland. The salient features of a city– region and how it is represented continues to be debated, particularly the multi-scalar and multitemporal quality of city–regions and their governance (Moisio & Jonas, 2018; Neuman & Hull, 2009). Regional governance is an important area of research because different public services can have differing regional reaches and economies-of-scale in their delivery.

FEAs and city-region systems have been typically confined to developed countries due to a lack of commuting data elsewhere. More recently, scholars have proposed using satellite images, such as those of nighttime lights, to assess urban/rural regions in developing countries or to construct functional spatial units (usually metropolitan areas or cities), but this had until recently only been applied to a small set of countries (e.g. Dingel et al., 2019). There are no global examples of these different approaches yet.

The only global source of FEA data is Moreno-Monroy and co-authors (2020)<sup>3</sup> , who use travel times and a probabilistic model to delineate commuting zones – or FEAs – at the global scale even when commuting data is inadequate. Their method delineates agglomerations of people rather than concentrations of human activities, such as built-up areas or nightlights, thus capturing a larger array of human settlements, as well as differences in development levels and physical structures. This analysis makes it possible to assess some key features of metropolitan areas and to separately assess population dynamics in urban centers and commuting zones.

# _Rural–urban continuum_

In parallel with the development of the FEAs, starting in the mid-20<sup>th</sup> century, social scientists increased efforts to move away from a rural–urban dichotomy towards a continuum ranging from remote rural to dense urban settings with territorial classifications of the relative degree of “rurality” or “urbanicity.” A prominent example is the nine-category Rural–Urban Continuum Codes (RUCC) produced by the U.S. Department of Agriculture (USDA) beginning in the 1970s (Hines, Brown, & Zimmer, 1975). The RUCC either categorized counties as “metropolitan” based on total metropolitan population or “nonmetropolitan” based on their “urban” population and the county’s adjacency to metropolitan. USDA further supplemented the RUCC with other classifications including 1) Urban Influence Codes, which differ from the RUCC primarily in providing more nonmetropolitan categories, 2) Rural–Urban Commuting Area Codes (RUCA) that approximate labor markets, and 3) Frontier and Remote Codes (FAR) to identify challenges in accessing services in remote areas (Cromartie, 2015). These classifications generated broad multidisciplinary interest in empirical analyses. The codes have been used extensively in contexts of analyzing variation along the ruralurban continuum of obesity and physical activity, epidemiological studies, voting patterns, ethno-racial diversity, disaster resilience, food insecurity, and access to education (see Cattaneo and co-authors (2021) for a brief review).

Woods & Heley (2017) and Hopkins & Copus (2018) compare rural–urban categorizations across several countries. For example, they describe national efforts that distinguish across types of urban areas (Austria, Canada, New Zealand, Northern Ireland, and Scotland), as well as those emphasizing

> 3 Data can be downloaded from http://data.europa.eu/89h/347f0337-f2da-4592-87b3-e25975ec2c95 and visualized with http://www.worldcitiestool.org/.

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