Ranking of Urban Areas in Terms of Quantitative and Qualitative Housing Indicators (Case Study: 22 Regions of Arak City)

Abstract

Aim: This research attempts to rank the 22 districts of Arak based on quantitative and qualitative housing indicators and to identify the spatial distribution pattern of these indicators at the city level. Material & Method: Subsequently, using Shannon's Entropy for weighting and multi-criteria decision-making methods, including Saw, Moora, and Copras, we evaluated and weighted 31 quantitative and qualitative indices at the regional level of Arak City. The final ranking of these indices was accomplished through the Copland aggregation method. The conclusive map was generated by invoking data in Arc-GIS software. Additionally, the global Moran's model was employed to identify the spatial pattern of quantitative and qualitative housing indicators. Finding: The findings reveal a "random" distribution pattern of quantitative and qualitative housing indicators in Arak City, indicating the influence of multiple factors on this randomness. Deteriorated areas (Regions 15 and 18), informal settlements (Regions 1 and 22), and the city center (Regions 6 and 18) are identified as the primary factors contributing to this random spatial pattern, consequently affecting the absence of quantitative and qualitative housing indicators in certain regions. In contrast, well-planned areas like Regions 3, 5, 18, 20, 10, and 7 exhibit a favorable status regarding the possession of these indicators. Conclusion: The study's outcomes reveal that the primary contributors to spatial inequality in possessing quantitative and qualitative housing indicators across Arak City's regions are deteriorated urban texture, informal settlements, urban decay, high population density, and land scarcity in central areas. Innovation: An innovative and practical dimension of this research involves using expert groups for indicator monitoring and applying the Copland aggregation model in the research process. This study could mitigate the gap in housing research within the domain of Arak.

Keywords

• housing planning
• housing spatial analysis
• arak city
• housing quality
• housing indicators