Spatial analysis of human development index and Identify its determinants in Iran

The Human Development Index which is a combination Index, is currently one of an important tool in analyzing spatial justice and regional inequality in the national and regional context. The aim of this paper is to investigate and identify the inequality of human development index in the provinces and the related factors. For this, a kind of descriptive-analytical method has been used and the data was collected from the National Population and Housing Census. For data analysis, the Morris model, GIS and SPSS software were respectively used. The results show that three provinces of Tehran, Alborz and Mazandaran are in the highest and three provinces of Sistan and Baluchestan, Kurdistan and North Khorasan are at the lowest ranks regarding the human development index, and central and northern provinces have relatively better conditions than the eastern and western provinces. Regarding the factors affecting the human development index show that the percentage of rural population, household size, the dependency burden, the real dependency ratio, and percentage of employment in agriculture with the correlation coefficient of 0.709, 0.740, 0.553, 0.553, 0.505, and 0.599, respectively have a significant negative relationship with the human development index, and indicators of urbanization percentage, employment ratio, economic participation rate, percentage of employees in the industrial sector and the percentage of employees in the service sector with the correlation coefficient of 0.709, 0.407, 0.361, 0.499 and 0.358, respectively have a significant positive relationship with the human development index. indicators of urbanization percentage, employment ratio, economic participation rate, percentage of employees in the industrial sector and the percentage of employees in the service sector with the correlation coefficient of 0.709, 0.407, 0.361, 0.499 and 0.358, respectively have a significant positive relationship with the human development index.