Yu. V. Faronova, A. Akhunov, T. P. Telnova, S. Litvinova, A. Khalilova
{"title":"GEOGRAPHICAL EXPERTISE OF POPULATION DENSITY OF THE RUSSIAN FEDERATION","authors":"Yu. V. Faronova, A. Akhunov, T. P. Telnova, S. Litvinova, A. Khalilova","doi":"10.17513/USE.37613","DOIUrl":null,"url":null,"abstract":"Population distribution and population density are relevant economic and geographical indicators of spatial planning and management. The Russian Federation as a unique territorial entity needs economic and geographical analysis and expertise in order to determine the types of subjects of the country by population density in conjunction with the socio-economic interpretation of this geographical indicator. Research objectives: 1) implementation of the socio-economic assessment of population density; 2) determination of the types of subjects of the Russian Federation by density levels and the level of socio-economic assessment of population density; 3) geographical examination of population density – a conclusion on the geographical patterns and paradoxes of population density and the socio-economic situation of the constituent entities of the Russian Federation by comparing the constituent entities of the country with models of territories based on the World Bank review. To solve the problem of performing a socio-economic assessment of population density, the authors calculated an integral indicator of the socio-economic assessment of population density. To determine the types of subjects of the Russian Federation by levels of density and the level of socio-economic assessment of population density, the subjects were grouped according to these indicators and a corresponding geographic matrix was compiled. The regions of the country with low population density, located in the Ural, Siberian, and Far Eastern Federal Districts of the country, far from the European center, became the nuclei of the high estimate of the population density.","PeriodicalId":246793,"journal":{"name":"Успехи современного естествознания (Advances in Current Natural Sciences)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Успехи современного естествознания (Advances in Current Natural Sciences)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17513/USE.37613","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Population distribution and population density are relevant economic and geographical indicators of spatial planning and management. The Russian Federation as a unique territorial entity needs economic and geographical analysis and expertise in order to determine the types of subjects of the country by population density in conjunction with the socio-economic interpretation of this geographical indicator. Research objectives: 1) implementation of the socio-economic assessment of population density; 2) determination of the types of subjects of the Russian Federation by density levels and the level of socio-economic assessment of population density; 3) geographical examination of population density – a conclusion on the geographical patterns and paradoxes of population density and the socio-economic situation of the constituent entities of the Russian Federation by comparing the constituent entities of the country with models of territories based on the World Bank review. To solve the problem of performing a socio-economic assessment of population density, the authors calculated an integral indicator of the socio-economic assessment of population density. To determine the types of subjects of the Russian Federation by levels of density and the level of socio-economic assessment of population density, the subjects were grouped according to these indicators and a corresponding geographic matrix was compiled. The regions of the country with low population density, located in the Ural, Siberian, and Far Eastern Federal Districts of the country, far from the European center, became the nuclei of the high estimate of the population density.