Affiliation:
1. St. Petersburg State University, Institute of Earth Sciences, 7/9, Universitetskaya emb., St. Petersburg, 199034, Russia,
Abstract
The continued rapid growth of metropolitan areas is being actively studied by urban researchers in different branches of science. The modern development of information technology has boosted the arsenal of available data and tools for researchers. One of these types of data are multiple dwellings data in Russia today, provided through the open data from Territorial Development Fund. Scientists from different areas of science actively use them, but their features are poorly covered precisely as spatial data and the possibilities for their application. The authors analyzed the possibilities and limitations of using such data to study metropolitan areas (on the materials of the St. Petersburg metropolitan area). The process used by the authors for obtaining spatial data and visualization options, including quantitative analysis, were described. The possibilities of visualization are demonstrated considering the ignoring of the administrative divisions and the analysis of spatial autocorrelation. The key features of the data are the ability to ignore the administrative divisions and the expansion of the time series for research. At the same time, indicated errors in the data, which in general should slightly distort the true picture of the housing stock differentiation. This is expressed in the low actual update efficiency from 2020 and the absence of about 10–20 % of attributive data. An important limitation of the data is the lack of information on individual housing construction. The impact of identified problems can be reduced by integrating with other types of data. An important feature of the data is the presence of an address in accordance with the federal address information system (FIAS), which allows for accurate geo-referencing of data on multiple dwellings, but with limitations associated with the shortcomings of FIAS. Based on the analysis of the experience of predecessors and the own experience of the study, options for using data are proposed, in particular, population density modeling, identification of urban morphotypes, visualization and quantitative analysis of changes in the spatial structure of metropolitan areas. This study is one of the first to analyze the data on multiple dwellings as a type of spatial data and possible directions of GIS-analysis.
Reference19 articles.
1. Babkin R.A. Experience of using the data of cellular operators in foreign economic and geographical studies. Vestnik of Saint-Petersburg University. Earth Sciences, 2021. V. 66. No. 3. P. 416–439 (in Russian). DOI: 10.21638/spbu07.2021.301.
2. Baryshkin P.A., Alekseenko N.A. Studying the structure of housing stock of mining mono-cities with the help of a cartographic method (by the example of Kimovsk and Kirovsk). Scientific researches of young cartographers, performed under the guidance of the staff of the Department of Cartography and Geoinformatics of the Geographical Faculty of Lomonosov Moscow State University. Moscow: KDU, Dobrosvet, 2022. P. 3–12 (in Russian).
3. Golovin A.V., Gudz’ T.V., Vitkov G.V., Karasel’nikova I.V., Kosolapov N.A. Sprawl Planning. Spatial Policy of Russian Cities. Moscow: Publishing House of the HSE (Publishing House of the Higher School of Economics), 2021. 248 p. (in Russian). DOI: 10.17323/978-5-7598-2578-4.
4. Kosareva N.B., Polidi T.D., Puzanov A.S. Economic urbanization. Moscow: Institute for Urban Economics Foundation, 2018. 418 p.
5. Kurichev N.K., Kuricheva E.K. The spatial structure of housing construction in the Moscow agglomeration: radial-sectoral differentiation. Vestnik of Saint-Petersburg University. Earth Sciences, 2020. V. 65. No. 1. P. 74–95 (in Russian). DOI: 10.21638/spbu07.2020.105.