Urban Fabric Typologies Based on Air Ventilation Indicators: A Case Study of District 1, Tehran

Document Type : Original Research

Authors
Sima Ferdosian 1
Mohammad Mehdi Azizi 2
1 PhD Candidate, School of Urban Planning, College of Fine Arts, University of Tehran, Tehran, Iran
2 Professor of School of Urban Planning, College of Fine Arts, University of Tehran, Tehran, Iran
10.48311/bsnt.2025.1023
Abstract
Aims: A proper typology of urban fabrics based on morphology-related ventilation indicators can play a significant role in explaining ventilation performance across different urban contexts. However, previous studies in this area have often lacked comprehensiveness, typically combined only a few indicators and resulted in a limited number of heterogeneous types. This paper aims to address this gap by systematically identifying urban fabric types based on key indicators that influence air ventilation.



Methods: This quantitative study utilizes data collected from available maps and satellite sources. Drawing on specialized literature in urban ventilation and considering constraints in accessing detailed morphological data, ten key indicators were selected. The study applied the “spatial signatures” method, incorporating the average characteristics of neighboring areas. Clustering was then performed using the K-Means algorithm.



Findings: A comparative analysis of clustering outcomes with varying cluster numbers showed that selecting eight clusters provides a balanced approach between generalization and detailed accuracy. The resulting types represent a diverse range of urban fabric patterns and help ensure that significant morphological configurations are neither overlooked nor excluded.



Conclusion: The “spatial signature method” proved to be a robust and systematic tool for typologizing urban fabrics based on ventilation-related morphological indicators. By integrating key indices and accounting for neighborhood-level characteristics, the method effectively identifies fabric types that reflect both structural diversity and ventilation potential. The approach demonstrates high accuracy in capturing detail and offers valuable insights for future studies and practical applications in the domain of urban ventilation analysis.

Keywords

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