Analysis the spatial pattern of distributive justice in the rural area of south of West Azerbaijan Province

The study of the pattern of spatial justice in rural areas is one of the important scientific topics that has attracted the attention of the scientific community, policy makers and planners. Rural areas have different levels of achievement affected by spatial processes. Some of them have a good level of achievement and the others have a more inappropriate level of achievement. This feature has embodied different spatial distribution patterns of (distributive) justice. Therefore, the present article has been prepared to study and discover this model (distributive justice model) in rural areas of the south of West Azerbaijan province. the purpose of this study is Investigating and analyzing the pattern of distributive justice in rural areas of south of West Azerbaijan province. In this research, quantitative methodologyhas been used, based on the Critical Positive Approach.the research method is descriptive-analytical and the purpose of this study is practical.The statistical population of the study is 1143 inhabited villages with a total population of 418948 in 9 cities of South West Azerbaijan. This study used 8 rural service indicators and 77 indicators. A library method was used to collect the data. “IDW method” was used to identify the spatial pattern of rural services distribution, the “Getis-. Ord-Gi” method was used for spatial clustering of rural areas based on hexagonal models, and the Moran's statistic was used for confirming the spatial clustering model.Also, geographic weight regression was used to assess rural areas' need for rural services.Based on the findings, the present study achieved the following The pattern of rural servicesdistribution follows a completely clustered pattern the region. This pattern has resulted inequality for the villages.Also, the pattern of need for rural services does not match the cluster pattern of spatial distribution of services, and the increase in rural services in many low-income villages will not affect their population size.