Assessment of Regional Polycentricity of the Settlement Pattern: Analysis of Modern Methods Based on Russian Data

The concept of polycentric development has taken center stage in European strategic planning documents as a tool for reducing economic asymmetry and increasing territorial connectivity. At the same time, there is a methodological problem in measuring the degree of polycentricity/monocentricity of settlement systems, which complicates the use of the concept of polycentric development in territorial administration. The aim of this article is to identify contradictions in assessing the polycentricity/monocentricity of settlement systems using various methods and options for resolving these contradictions by compensating for the disadvantages of some methods with the advantages of others. The analysis was carried out on data on the population of 132 344 population centers of 83 federal subjects in 2020. The analysis revealed differences in assessments of the level of polycentricity/monocentricity, due to (1) a different number of object of observations taken into account; (2) the methods used, focusing on the concentration of objects of observation, variation, or rank distribution. For cases with significant differences in the obtained estimates, a detailed analysis was carried out, which made it possible to identify the shortcomings of the methods and the possibilities of specifying the estimates as a result of their joint use. The study showed that existing methods in some cases give different results. This is due to the different sensitivity of the methods to individual settlement options (including cases with two centers of equal population size, with a group of equal subcenters) and with the number of observations included in the assessment. The identified features of assessing polycentricity using the example of regional settlement systems in Russia can be used to improve assessment methods and tools, which will contribute to the formation of a policy for the territorial development of regions and population centers.