Abstract

The approaches to distinguishing urban agglomerations are analyzed. The authors assert that in Russian science a substitution of concepts exists: only major urban agglomerations are considered instead of the total number of urban agglomerations; as a result, the number of urban agglomerations in Russia is much underestimated. The known methods are too strict, complicated, and obsolete. It is proposed to switch over to the approach used in statistical studies in the United States. This approach is based on identifying socalled "standard metropolitan statistical areas" and makes it possible to identify "metropolitan" and "micropoli� tan" municipal districts in the oblasts of Central Russia. This identification is based on grouping of municipal districts according to classes of the centers of districts. The districts whose centers are midsize towns or big� ger cities are considered metropolitan. The districts with submidsize towns as centers are considered mic� ropolitan. The centers have been grouped using the "peak achieved population size" principle proposed ear� lier by the authors, which makes it possible to avoid the strict dependency of classification of the centers of districts by changes in population. The location of metropolitan and micropolitan districts makes it possible to obtain a clear representation about the territorial and urban structure of the studied region. The combination of this structure with the main railroad network shows that metropolitan and micropolitan districts are either located at railroad hubs or form banded structures along key directions. The above statements point to the formation of an agglomer� ated-network structure of territory. The data on the number of metropolitan and micropolitan districts and their share in the total number of municipal districts, territory, and population of central Russia are provided. Since a lot of municipal districts have a large territory, it is proposed to include in the metropolitan approach the concept of reachability of the center.

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