Developing a Structural Model of Urban Image and Landscape Based on the Zendevari Framework in Mâdis (Urban Greenways): The Case of Niasarm Mâdi, Isfahan

Abstract

This study aimed to identify and structurally organize the factors affecting urban image and landscape based on the Zendevari framework and to determine the driving and dependent relationships among these factors in the Niasarm Mâdi urban greenway in Isfahan. This applied study employed a descriptive-analytical design and a mixed qualitative-survey approach. Data were collected through documentary review and field-based expert assessment. In the first stage, urban image and landscape indicators were derived from the 25 layers of the Zendevari framework and screened through the Delphi technique using the judgments of 10 experts in architecture and urban planning in Isfahan Province. Indicators with mode and median values above 3 were retained, resulting in 17 indicators for subsequent analysis. In the second stage, Interpretive Structural Modeling (ISM) was used to determine the interrelationships and hierarchical structure of the selected indicators. A Structural Self-Interaction Matrix was developed using judgments from 25 researchers in architecture and design, followed by construction of the initial and final reachability matrices, hierarchical level partitioning, and MICMAC analysis. The ISM results organized the selected indicators into six hierarchical levels. The kinetic/movement layer occupied the deepest and most influential level of the structural model, followed by the biological layer, indicating that these two dimensions functioned as the principal driving foundations of urban image and landscape quality. Historical, imaginary/visual, and climatic layers were positioned at subsequent levels and also exerted important structural effects. The final reachability matrix demonstrated high driving power for several dimensions, including movement, formative, physical, biological, environmental, climatic, social, and aesthetic layers. MICMAC analysis further indicated that most of the 17 indicators possessed substantial driving power, with 14 indicators classified within the independent or linkage categories, confirming their central role in shaping the urban image and landscape system. Integrating the Zendevari framework with ISM and MICMAC provides a coherent analytical model for understanding urban greenway image and landscape. The results emphasize that movement-related and biological dimensions should receive priority in planning and design interventions, particularly through improved accessibility, pedestrian and vehicular organization, ecological protection, biodiversity enhancement, and preservation of environmental qualities.