Spatiotemporal Modeling of Urban Expansion Patterns in Iran

Document Type : Research Paper

Authors

1 Assistant Professor of Urban Engineering at Lorestan University

2 Remote sensing & GIS department, faculty of geography, university of Tehran

10.22111/gdij.2025.48393.3638

Abstract

Urbanization has intensified in developing countries over recent decades, making it crucial to understand not only the rate of urban growth but also the spatiotemporal patterns of land-use change. This study proposes a national-scale framework for mapping and analyzing predictable urban expansion patterns in Iran. Multi-temporal DMSP/OLS nighttime light data (1992, 2002, 2013) and Landsat imagery (1992, 2002, 2013, 2022) were employed to extract urban extents and validate the results using maximum likelihood classification for selected cities, including Tehran-Karaj, Isfahan, Tabriz, and Shiraz. The DMSP/OLS-derived urban patterns demonstrated strong agreement with Landsat-based results, with an average overall accuracy of 84.11% and a kappa coefficient of 0.51. Regression analysis revealed a significant linear relationship between constructed land area, population, and GDP, with the highest correlation observed between GDP and urban land (R² = 0.894). Using the CA–Markov model, urban land is projected to increase from approximately 14,948 km² in 2013 to over 26,156 km² by 2031 (kappa = 0.709). These findings provide a robust basis for policymakers to evaluate urban development strategies and support sustainable urban planning at the national level.

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History

  • Receive Date: 20 April 2024
  • Revise Date: 15 December 2025
  • Accept Date: 21 December 2025

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