SSOAR Logo
    • Deutsch
    • English
  • English 
    • Deutsch
    • English
  • Login
SSOAR ▼
  • Home
  • About SSOAR
  • Guidelines
  • Publishing in SSOAR
  • Cooperating with SSOAR
    • Cooperation models
    • Delivery routes and formats
    • Projects
  • Cooperation partners
    • Information about cooperation partners
  • Information
    • Possibilities of taking the Green Road
    • Grant of Licences
    • Download additional information
  • Operational concept
Browse and search Add new document OAI-PMH interface
JavaScript is disabled for your browser. Some features of this site may not work without it.

Download PDF
Download full text

(1.276Mb)

Citation Suggestion

Please use the following Persistent Identifier (PID) to cite this document:
https://nbn-resolving.org/urn:nbn:de:0168-ssoar-51575-8

Exports for your reference manager

Bibtex export
Endnote export

Display Statistics
Share
  • Share via E-Mail E-Mail
  • Share via Facebook Facebook
  • Share via Bluesky Bluesky
  • Share via Reddit reddit
  • Share via Linkedin LinkedIn
  • Share via XING XING

Changes in the population distribution and transport network of Saint Petersburg

Изменения в пространственном распределении населения и дорожной сети Санкт-Петербурга
[journal article]

Xiaoling, Li
Anokhin, Anatolii A.
Shendrik, Alexander V.
Chunliang, Xiu

Abstract

The authors explores the interdependence between demographic changes and transport network centrality, using Saint Petersburg as an example. The article describes the demographic data for the period 2002-2015 and the transportation network data of 2006. The authors employ several methods of demograp... view more

The authors explores the interdependence between demographic changes and transport network centrality, using Saint Petersburg as an example. The article describes the demographic data for the period 2002-2015 and the transportation network data of 2006. The authors employ several methods of demographic research; they identified the centre of gravity of the population, produce the standard deviational ellipsis and use the kernel density estimation. The street network centrality of Saint Petersburg was analyzed using the Multiple Centrality Assessment Model (MCA) and the Urban Network Analysis Tool for ArcGIS. The analysis of the population distribution in Saint Petersburg shows that each area of the city has seen their population grow over the last thirteen years. However, it is the population of suburban areas that increased the most. The core area of the city has the tendency of outward diffusion, and the population gravity centre has been moving northwards. Spatial characteristics of the population growth, changes in the population gravity centre, the standard deviational ellipse and characteristics of the street network centrality show that Saint Petersburg is at the final stage of urbanization and its development pattern is similar to that of other major cities.... view less

Keywords
population; regional distribution; town; Russia; population density; road network; municipal area; transport network

Classification
Area Development Planning, Regional Research
Economic and Social Geography
Sociology of Traffic
Sociology of Settlements and Housing, Urban Sociology

Free Keywords
St. Petersburg

Document language
English

Publication Year
2016

Page/Pages
p. 39-60

Journal
Baltic Region (2016) 4

DOI
https://doi.org/10.5922/2079-8555-2016-4-4

ISSN
2079-8555

Status
Published Version; peer reviewed

Licence
Free Digital Peer Publishing Licence


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.
 

 


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.