Spatial Distribution Analysis of Urban Services and Its Relationship with Housing Prices in Karaj City

Articles in Press

Document Type : Research Paper

Authors

1 Master’s student, Department of Geography and Urban Planning, Faculty of Geographical Sciences, Kharazmi University, Tehran, Iran

2 Associate Professor of Geography and Urban Planning, Kharazm Universitya

3 Associate Professor of Geography and Urban Planning: Faculty of Geographical Sciences, Kharazmi University, Tehran

10.22034/gp.2026.68175.3429

Abstract

This study is applied in nature and follows a descriptive–analytical approach. The data analyzed includes spatial information and statistics related to housing prices and the distribution of six categories of urban services, primarily obtained from the Municipality of Karaj and the Statistical Center of Iran. To produce digital layers, the Spatial and Spatial Analyst tools within the GIS environment were employed. The analytical models used in this research include Geographically Weighted Regression (GWR) anReclassify tool were applied. Subsequently, the Raster Calculator was used to combine service-related components. To calculate the correlation between urban services and housing prices, the Fuzzy Overlay tool within the Spatial Analyst extension was utilized. In addition, the Band Collection Statistics tool was used to compute correlation coefficients and covariances between the dependent and independent variables.

Findings:

The highest level of access to urban services is observed in the eastern and northeastern areas of Karaj. The central areas of the city have moderate to low levels of access, while the western, southwestern, and parts of the northern regions exhibit medium levels. The northern and northwestern zones show the lowest levels of urban services. The highest housing prices are found in the northeastern and eastern parts of the city, while the western and southern peripheral areas have lower prices. The strongest correlations between housing prices and urban services are associated with health–medical services (0.58) and administrative–security services (0.52), while the weakest correlation pertains to cultural–religious services (0.36).

Conclusion:

The uneven distribution of urban services in Karaj plays a significant role in shaping spatial inequalities in housing prices. Areas characterized by a high diversity and density of essential services—such as healthcare, administrative, transportation, and educational services—tend to have higher land and housing values. This, in turn, contributes to the reproduction of privileged and disadvantaged urban spaces across the city.

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Journal of Geography and Planning

Articles in Press, Accepted Manuscript
Available Online from 14 February 2026

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