نوع مقاله : مقاله پژوهشی
موضوعات
عنوان مقاله English
نویسندگان English
Introduction
Spatial justice, as a fundamental principle of urban planning, emphasizes the equitable distribution of resources, services, and opportunities among all societal groups, playing a pivotal role in reducing social inequalities, enhancing quality of life, and achieving sustainable urban development. In large cities, particularly metropolises like Mashhad, which face rapid population growth, expanding informal settlements, and pressures from religious tourism, achieving spatial justice presents significant challenges. Mashhad, Iran’s second-largest city and a key religious and tourism hub, with a population of approximately three million and an urban area of 351 square kilometers, exhibits considerable disparities in the distribution of urban services. These disparities affect residents’ quality of life and pose serious challenges during crises such as natural disasters or pandemics. Previous studies have indicated that inequitable service distribution is often linked to factors such as land value, urban planning policies, and infrastructure deficiencies. However, a detailed analysis of service distribution in Mashhad and its alignment with spatial justice principles has received limited attention. This study aims to analyze the distribution pattern of urban services across Mashhad’s 17 districts, identify advantaged and disadvantaged areas, and propose strategies for improving equitable access to services. The key research questions are: How are urban services distributed across Mashhad’s districts? Does this distribution align with spatial justice principles? And which areas are in favorable or unfavorable conditions regarding service access?
Materials and Methods
This research adopts an analytical-applied approach, with data collected from Mashhad’s Comprehensive Urban Plan and land-use maps from 2018. To analyze the distribution of urban services across the city’s 17 districts, 11 informational layers were utilized, including commercial, higher education, education, parks and green spaces, urban facilities, and equipment, recreational, healthcare, cultural-artistic, religious, sports, and bus and metro stations. Data analysis was conducted using Geographic Information Systems (GIS) and models such as the Average Nearest Neighbor (ANN), Gini coefficient, and fuzzy weighted overlay technique. The ANN method was initially applied to determine whether services are distributed in a clustered, dispersed, or random pattern. Subsequently, informational layers were standardized based on each service’s performance radius (as per the Comprehensive Plan) using Euclidean distances and integrated via the fuzzy overlay technique. The final assessment of district-level service access was performed using the Gamma operator in GIS, and a comprehensive map was generated. The Gini coefficient and Lorenz curve were employed to assess service distribution inequality, while Pearson’s correlation coefficient was used to evaluate the relationship between population density and service access levels. These methods enabled a precise analysis of spatial patterns and the identification of existing disparities.
Findings
The findings reveal that urban services in Mashhad are predominantly clustered in the central and western districts (e.g., Districts 1, 9, and 11). In contrast, eastern and peripheral areas (notably Districts 4, 5, 15, and 17) suffer from severe service shortages. The ANN model yielded a ratio below 1, confirming a clustered distribution pattern. Fuzzy maps and Hotspot Analysis indicated that northwestern and northeastern districts are population hubs, yet essential services such as healthcare and education are scarce in these areas. The Gini coefficient ranged from 0.38 (metro stations) to 0.62 (higher education), indicating that education and metro services are relatively evenly distributed, whereas higher education, healthcare, and BRT stations exhibit high inequality. The Lorenz curve corroborated these disparities, highlighting the recreational, sports, and commercial services concentration in specific districts. Pearson’s correlation analysis (coefficient: 0.0003, P-value: 0.999) showed no significant relationship between population density and service access, suggesting that densely populated areas do not necessarily receive more services. Advantaged districts (1, 9, 11) with lower population density and high economic value benefit from extensive services, while disadvantaged districts (4, 5, 15, 17) with high population density suffer from limited access. These disparities were attributed to factors such as service concentration in affluent areas, inefficient location policies, inadequate public transportation, and the deteriorated urban fabric of deprived districts.
Conclusion
This study demonstrates that the distribution of urban services in Mashhad does not align with spatial justice principles, and existing spatial inequalities threaten social welfare and urban sustainability. The concentration of services in central and western districts, coupled with the deprivation of peripheral and eastern areas, has deepened socio-economic divides. The lack of a direct correlation between population density and service access underscores the influence of factors such as land value, infrastructure, and urban policies on these disparities. To achieve spatial justice, it is recommended that urban management increase investments in disadvantaged areas, expand public transportation networks (BRT and metro), develop healthcare, recreational, and educational facilities in deprived districts, and incentivize private sector participation through measures like tax exemptions. The experience of cities like Medellín, Colombia, suggests that integrated urban projects can enhance spatial justice. Adopting multi-criteria policies, revising service location strategies, and incorporating citizen participation and smart technologies can reduce inequalities and pave the way for sustainable development in Mashhad.
کلیدواژهها English
