Spatial Assessment and Analysis of Urban Poverty: A case study of Mahabad City

ABSTRACT
Studies on urban poverty are undertaken to identify the underlying causes and driving factors behind the emergence and persistence of deprivation in urban areas, propose scientifically grounded and practical strategies for reducing socioeconomic inequalities, and enhance living conditions in disadvantaged neighborhoods. Such studies enable urban planners and policymakers to design and implement targeted and effective interventions for sustainable urban development by providing an accurate understanding of existing conditions. The objective of this research is to identify and analyze the factors influencing urban poverty through economic, social, physical, and public service accessibility indicators, to evaluate their effects on poverty conditions, and to clarify the spatial distribution of urban poverty in Mahabad City. To achieve this objective, 20 key criteria influencing urban poverty were initially classified into four main dimensions. These criteria were subsequently weighted using the Analytic Network Process (ANP). The weighted criteria were then integrated using the fuzzy gamma model to produce a spatial model of urban poverty. The results indicate that the northwestern and central neighborhoods of the city exhibit lower levels of urban poverty, while poverty levels gradually increase toward the peripheral areas. Overall, 30.97 percent of the study area falls within favorable or relatively favorable conditions, 21.08 percent is classified as moderate, and 47.95 percent exhibits unfavorable or relatively unfavorable conditions. The Moran’s I spatial autocorrelation index, with a value of 0.24, confirms the non-random spatial distribution of urban poverty and indicates the presence of a clustered pattern across the study area.
Extended Abstract
Introduction
Urban poverty, as a consequence of structural inequalities embedded in the urban development process, not only undermines the quality of life of residents in impoverished neighborhoods but also poses serious challenges to the social, economic, and environmental sustainability of cities. The rapid expansion of urbanization and large-scale migration to cities in recent decades has generated a wide range of emerging issues across multiple domains, including urban poverty. Urban poverty is not confined to income deprivation but also includes limited access to essential services such as education, healthcare, recreational spaces, and cultural facilities. This phenomenon, which stems from the unequal distribution of resources and urban amenities, often manifests in distinct spatial patterns that require rigorous and systematic analysis.
Mahabad City, as one of the important urban areas in West Azerbaijan Province, faces a range of economic and social challenges. Spatial analysis of urban poverty can assist in identifying poverty hotspots and clarifying the spatial distribution of poverty across the city. This study aims to identify and analyze the factors influencing urban poverty through economic, social, physical, and public service accessibility indicators, to assess their effects on poverty conditions, and to clarify the spatial pattern of urban poverty in Mahabad City.
 
Methodology
This study is applied in nature and adopts a descriptive–analytical research design. To model the spatial distribution of urban poverty across neighborhoods in Mahabad City, an integrated approach combining spatial and statistical data was employed.
 
Results and discussion
The results indicate that the northwestern and central neighborhoods of Mahabad City experience lower levels of urban poverty. In contrast, poverty levels gradually increase toward the peripheral areas of the city. Overall, 30.97 percent of the study area is classified as favorable or relatively favorable, 21.08 percent as moderate, and 47.95 percent as unfavorable or relatively unfavorable. The Moran’s I spatial autocorrelation index, with a value of 0.24, indicates a non-random spatial distribution of urban poverty and the presence of a clustered pattern across the study area.
The economic criterion was identified as the most influential factor in the assessment of urban poverty, followed by social, physical, and public service accessibility criteria. Moran’s I analysis further demonstrates that all analyzed criteria significantly deviate from a random spatial pattern, exhibiting weak positive spatial correlation among areas with different levels of poverty. This finding suggests that high-poverty areas tend to cluster in proximity to one another; however, the observed pattern is neither strong nor highly concentrated.
 
Conclusion
Urban poverty remains a major challenge for contemporary societies, exerting profound impacts on residents’ quality of life and the pursuit of sustainable urban development. The findings of this study identify the economic criterion as the most critical factor shaping urban poverty in the study area. Social and physical factors rank next in importance, whereas public service accessibility plays the least significant role. Overall, 30.97 percent of the study area is classified as favorable or relatively favorable, 21.08 percent as moderate, and 47.95 percent as unfavorable or relatively unfavorable.
The spatial distribution of poverty reveals more favorable conditions in the northwestern and central neighborhoods, with conditions gradually deteriorating toward the eastern and southern peripheries. These results underscore a clear spatial divide between the central and northwestern neighborhoods and other parts of the study area. To reduce poverty and spatial inequality, improving access to public services in peripheral areas is essential. This includes creating job opportunities as a key and influential factor in addressing urban poverty in marginal areas, as well as promoting the development of health, educational, and welfare infrastructure to achieve spatial justice. Implementing social empowerment programs, such as vocational training and literacy initiatives, can contribute to improving residents’ quality of life.
By combining mixed methodologies with multidimensional indicators, this study reveals deeper layers of spatial inequality and emphasizes the need to redesign poverty reduction programs through space-sensitive approaches that simultaneously address economic, social, and physical dimensions.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
The authors declare that there is no conflict of interest regarding the authorship and or publication of this article.
 
Acknowledgments
The authors would like to thank all those who assisted us in conducting this research, especially those who performed the article quality assessment tasks.