The article reviews and substantiates research methods and data sources on the dynamics of the spatial structure of the largest urban agglomerations in Russia. The object of the study is modern methods for studying urban agglomerations based on new data sources. A case study of the number two urban agglomeration in Russia—St. Petersburg urban agglomeration—shows that interdisciplinary synthesis of socioeconomic geography, regional economics, urban studies, geoinformatics and cartography, land management,
and variety of data sources (mobile network operators’ data, tax statistics, housing construction, satellite observations, retail chain activity, and road networks), as well as modern GIS equipment, make it possible to evaluate this structure, its changes, and fluctuations. The main objective of the study is to critically rethink
the methods of studying the spatial structure of one of the largest urban agglomerations in Russia that developed
in the turbulent period between 2014 and 2022. Using a deductive approach, the authors inventoried the
available methods for studying urban agglomerations and traditional data sources and obtained updated
methods and new sources. Next, the advantages and disadvantages of each group of methods are identified.
Using bibliographic analysis, the authors identified the limitations and possibilities for empirical content
(availability of specific data sources). Based on their own critical analysis, the authors offer a final expert
assessment of the applicability and usefulness of the methods specifically for the St. Petersburg urban agglomeration.
The authors’ contribution lies in the adaptation of modern groups of methods for studying the spatial
structure of cities to study the considered urban agglomeration, taking into account the local specifics. It is
expected that development of a modern methodology for studying the spatial structure of the St. Petersburg
urban agglomeration, based on a symbiosis of modern methods and data sources, will contribute to studying
Russia’s largest urban agglomerations
