Spatial imbalances and spatial inequalities exist at different levels, and the realization of spatial and social justice at these levels depends on eliminating these imbalances through spatial planning. Service organizations to clients and, most importantly, the Welfare Organization, may have a lot of data and figures from their clients, but in many cases, existing data does not have a spatial dimension, and they are purely descriptive. The main objective of this research is to analyses spatially clients covered by welfare in the scale of Mashhad, in both regional and neighborhood level. The statistics required for this study are collected from the Department of Welfare of Khorasan Razavi and Mashhad. The methods used for spatial analysis are the standard deviation elliptic index, regional and neighborhood demographic density, kernel density, basic graphic statistical methods including the nearest neighbor's index, spatial autocorrelation measurement models such as general Moran I and LISA. The results of this research, presented in various maps and diagrams, show that the welfare beneficiaries in the city of Mashhad have not been distributed equally and different regions and neighborhoods have a significant difference, with the highest number of clients in regions 2, 3 and 4, the city of Mashhad where tjeay are located in the north and northeastern parts of the city. Also, at the neighborhood level, Shahid Ghorbani, Northern Tabarsi, Derevey and Bahman neighborhoods include the most welfare-clients population. In a general analysis based on the kernel density analysis, it can be stated that four condensed nuclei and a subunit formed in the city of Mashhad. Also, the results of Moran indicator and others indicate that the spatial distribution pattern of welfare clients in Mashhad is quite clustered and in particular parts of Mashhad, which mainly coincide with the informal settlements of the city and the eastern and northern parts of the city are distributed in cluster form.

Understanding how to distribute economic, social, cultural and other opportunities as first step in spatial development planning can improve service delivery and increase equilibrium between regions. This research aimed at study and analysis of 31 provinces of Iran based on social indicatros enjoyment. Therefore, the present study is applied in terms of purpose and descriptive-analytical in terms of nature and method of research. Required data collected through the statistical yearbook of 1395 (2016) in the form of 52 important social indicators including social, cultural, welfare, educational and health components. Shannon entropy, coefficient of variation (C.V), WASPAS used to Wheightining of criterias, analysis of indicators dispersion and determining the level of development of provinces respectively in the context of MATLAB. The result shows that there is a lack of social development balance between Iran provinces. Tehran, Isfahan, Khorasan Razavi and Fars are four provinces that placed at higher level of social development and Alborz, Zanjan, Chaharmahal Bakhtiari, Semnan, South Khorasan, North Khorasan, Ilam and Kohgiluyeh and Boyer Ahmad are placed at the most deprived areas of the country in terms of social indicators. Overall, the results show that social development status in Iran's provinces is not synonymous with social and spatial justice and requires proper and effective attention and management.