Urban fringes of million-plus cities in the Republic of Kazakhstan: a methodology for delineation

DOI: 10.35595/2414-9179-2025-3-31-258-272

View or download the article (Rus)

About the Author

Tolegen B. Akynzhanov

Lomonosov Moscow State University, Kazakhstan Branch, Department of Ecology and Environmental Management,
11, Kazhymukana str., Astana, 010000, Kazakhstan,
E-mail: akynzhanovtb@my.msu.ru

Abstract

In the context of rapid urbanization in major cities of Kazakhstan—such as Astana, Almaty, and Shymkent—the need for spatial analysis of the urban fringe has become increasingly pressing. These areas are characterized by pronounced socio-environmental heterogeneity, unstable land use patterns, and insufficient infrastructure provision. This study proposes a methodological framework for delineating the urban fringe based on the integration of geoinformation analysis and landscape metrics. The outer boundary of the fringe is defined as the intersection of the administrative boundary and the “real city” boundary, derived from nighttime light data (VIIRS) and built-up surface data (GHS-BUILT). To identify the inner boundary, the Shannon Diversity Index was calculated using GlobeLand30 land cover data within a 960 m moving window. The entire study area was aggregated into a regular hexagonal grid with cells of approximately 1 km2, enabling detailed spatial analysis of land use mosaic patterns. The results revealed a clear division into three territorial types: the city core, the urban fringe, and peripheral subcenters. Urban fringes occupy more than 80 % of the total area of cities studied, highlighting their significance for urban planning. The proposed methodology demonstrates both universality and applicability across flat and mountainous terrains, ensuring high accuracy and reproducibility of results. The findings can inform infrastructure optimization, land use management, and the development of sustainable urban development strategies. Future research will focus on a more in-depth analysis of the socio-economic and environmental characteristics of fringe areas, as well as on adapting the methodology to other cities with consideration of their specific contexts.

Keywords

urban fringe, urbanization, spatial analysis, Shannon index, remote sensing

References

  1. Angel S., Parent J., Civco D. Urban Sprawl Metrics: An Analysis of Global Urban Expansion Using GIS. Proceedings of ASPRS 2007 Annual Conference, Tampa, Florida May. Citeseer, 2007. V. 7. 12 p.
  2. Bhatta B. Analysis of Urban Growth Pattern Using Remote Sensing and GIS: A Case Study of Kolkata, India. International Journal of Remote Sensing, 2009. V. 30. P. 4733–4746. DOI: 10.1080/0143-1160-8026-51967.
  3. Elvidge C.D., Zhizhin M., Ghosh T., Feng-Chi H., Jay T. Annual Time Series of Global VIIRS Nighttime Lights Derived from Monthly Averages: 2012 to 2019. Remote Sensing, 2021. V. 13. Iss. 5. Art. 922. DOI: 10.3390/rs13050922.
  4. Feng X. Modelling the Spatial Pattern of Urban Fringe. International Institute for Geo-information Science and Earth Observation, Enschede Netherlands, 2004. 80 p.
  5. Günay E. Interaction of Urban Fringe and Transportation System: Istanbul Case. MS thesis. Izmir Institute of Technology (Turkey), 2007. 77 p.
  6. Huang J., Zhou Q., Wu Z. Delineating Urban Fringe Area by Land Cover Information Entropy—An Empirical Study of Guangzhou-Foshan Metropolitan Area, China. ISPRS International Journal of Geo-Information, 2016. V. 5. Iss. 5. Art. 59. DOI: 10.3390/ijgi5050059.
  7. Ludwig J.A., Reynolds J.F. Statistical Ecology: A Primer in Methods and Computing. John Wiley & Sons, 1988. V. 1. 146 p.
  8. Martin L.R.G. A Comparative Urban Fringe Study Methodology. Environment Canada, Lands Directorate. Environnement Canada, Direction générale des terres, 1975. 101 p.
  9. Wilson E.H., Hurd J.D., Civco D.L., Prisloe M.P., Arnold C. Development of a Geospatial Model to Quantify, Describe and Map Urban Growth. Remote Sensing of Environment, 2003. V. 86. P. 275–285.
  10. Yang Y., Ma M., Tan C., Li W. Spatial Recognition of the Urban-Rural Fringe of Beijing Using DMSP/OLS Nighttime Light Data. Remote Sensing, 2017. V. 9. Iss. 11. Art. 1141. DOI: 10.3390/rs9111141.
  11. Zhao Q., Yu L., Li X., Peng D., Zhang Y., Gong P. Progress and Trends in the Application of Google Earth and Google Earth Engine. Remote Sensing, 2021. V. 13. Iss. 18. Art. 3778. DOI: 10.3390/rs13183778.

For citation: Akynzhanov T.B. Urban fringes of million-plus cities in the Republic of Kazakhstan: a methodology for delineation. InterCarto. InterGIS. Moscow: MSU, Faculty of Geography, 2025. V. 31. Part 3. P. 258–272. DOI: 10.35595/2414-9179-2025-3-31-258-272 (in Russian)