Document Type : Original Article

Author

• Naser Ahmadi Sani

Associate Professor, Faculty of Agricultural and Natural Resources, Mahabad Branch, Islamic Azad University, Mahabad, Iran.

Abstract

The physical expansion s, leaving substantial impacts on the city’s environmental structure. Due to their proximity to northern foothills and location along the main urban development axis, these areas represent the focal zones of contemporary spatial transformations in Tehran. The present study aims to provide a multi-temporal and comprehensive analysis of land-use dynamics in these critical areas and to model their future development scenarios up to the horizon year 2035, employing remote sensing data and advanced urban growth models. Accordingly, land-use changes were extracted using multi-temporal Landsat imagery, and spatial metrics such as Shannon entropy and concentration index were calculated to characterize spatial development patterns. Subsequently, a hybrid Cellular Automata–Markov Chain model was applied to simulate future urban expansion with high accuracy. Results indicate a significant decline in barren and natural lands over the past twenty years, primarily converted into residential, service, and transportation uses. The spatial structure analysis revealed that District 21 follows a concentrated and near-saturation pattern, whereas District 22 exhibits a more dispersed, polycentric expansion. The 2035 scenario modeling further suggests that, if current trends persist, most of the remaining developable land will transition toward full urbanization. These findings highlight the urgent need to revise urban development policies and adopt an integrated approach to growth management and natural resource preservation. Understanding distinct spatial growth patterns can support more targeted planning, environmental risk mitigation, and optimized infrastructure allocation for the future.

Keywords

• Spatial entropy
• Land-use change
• Tehran urban development
• Cellular Automata Markov Chain model
• Remote sensing

Main Subjects

• Remote sensing and Gis