Spatial Analysis of Development Levels of Provinces in Iran

Development after the end of World War II has been one of the most important issues in academic and planning circles. The main goal of development is to eliminate inequalities. Therefore, one of the important obstacles on the path of development is the existence of inequality and lack of economic and social balance at the level of the country or region. Iran also has inequality and imbalance in terms of different development indicators, so this regional inequality and imbalance is one of the prominent features of Iran's spatial development. Knowing the development levels of different regions of the country is the first step in the regional development planning process. Therefore, this research was carried out with the aim of spatial analysis of the development levels of Iran's provinces. Based on this, the specific objectives of the research are:Determining the importance of economic, social, cultural and infrastructure indicators;Determining the level of development of Iran's provinces;Determining the spatial distribution of development among Iran's provinces. 

The method used in this research is based on the analysis of a set of indicators to create a composite index of development by using different statistical techniques. In this research, based on the statistics available in the results of the general population and housing census of the country in 2018 and the results of the country's statistical yearbooks in 2018, 84 indicators related to the analysis of regional development in four groups: a) economic (30 indicators), b) social 24 indicators), c) cultural (10 indicators) and d) infrastructure (20 indicators) were developed. In order to solve the difference in the scale of the indicators, dividing by the mean was used in the factor analysis method, the standardization method was used in the taxonomy method, and the soft linear method was used in TOPSIS. The principal component analysis method was used to weigh the individual indicators of each regional development dimension, and the analytical hierarchy process (AHP) was also used to weigh the four dimensions of development. Then, the combined index of the four subgroups was calculated. For this purpose, the methods of factor analysis, numerical taxonomy and TOPSIS method were used to create a composite index of the development of the provinces. These four composite indices were combined, and the final composite index was calculated. Finally, geographic information systems and hierarchical cluster analysis were used to classify the development level of the provinces. 

The final results of determining the relative weight of the four dimensions of determining the degree of development of the provinces indicated that the economic dimension, with a relative weight of 0.536, is the most important in determining the degree of development of the provinces. After that, the infrastructure dimension, with a relative weight of 0.219, the social dimension, with a relative weight of 0.162, and finally, the cultural dimension, with a relative weight of 0.083, are located. Based on the findings of the overall composite index, the provinces of Tehran, Isfahan, Bushehr, Khuzestan and Razavi Khorasan are the best with TOPSIS composite indexes of 0.9524, 0.5428, 0.4941, 0.3449 and 0.2922 respectively. The provinces of Sistan and Balochistan, Kahgiluyeh and Boyer Ahmad, South Khorasan, Lorestan, and Kurdistan were ranked the lowest with TOPSIS composite indices of 0.0113, 0.0861, 0.0886, 0.0914 and 0.0961, respectively. The results of the ranking of the provinces based on the composite index show that Tehran, Isfahan, and Bushehr provinces are in the first level of development with a composite index between 0.95-0.344. Most central provinces and some northern, southern, western and eastern provinces are in the second category, i.e. medium development level with a composite index between 0.15-0.34. In the group of provinces with a low level of development, the composite index is between 0.15-0.011. It includes eastern, southeastern and southern provinces (South Khorasan, Sistan and Baluchistan and Hormozgan), northeastern and northwestern provinces (North Khorasan, Golestan, Gilan, Ardabil, West Azerbaijan), western provinces (Kermanshah, Ilam, Kurdistan, Zanjan, Hamadan, Lorestan, and Qom) and central Zagros (Kohgiluyeh, Boyerahmad, Chaharmahal, and Bakhtiari). The result of the hierarchical cluster analysis also shows three different levels of development among the provinces of Iran, which was also confirmed in the form of GIS maps. 

This research was conducted with the aim of spatial analysis of the development levels of Iran's provinces. The weighting results of the development dimensions were obtained in the order of the relative weight of the economic dimension, the infrastructure dimension, the social dimension and the cultural dimension. The leveling of different provinces based on the composite index of total development showed that. The identified spatial pattern included developed areas (including 3 provinces), areas with an average level of development (including 11 provinces) and undeveloped areas (including 17 provinces). As a result of hierarchical cluster analysis to classify the overall development level of the provinces, three clusters were identified, and it was indicative of the existence of three different levels of development among the provinces of Iran, which was also confirmed in the form of GIS maps. Moreover, it indicated the existence of a development gap between the provinces of Iran. The results of this research and the pattern of development obtained from GIS techniques and hierarchical cluster analysis indicated that the center-periphery model is established in Iran. Therefore, based on the research results, it is necessary to prioritize less developed provinces with a low level of development in any budget allocation for the development program. 

There is no funding support. Authors’ ContributionAuthors contributed equally to the conceptualization and writing of the article. All of the authors approved the content of the manuscript and agreed on all aspects of the work declaration of competing interest none. Conflict of InterestAuthors declared no conflict of interest. AcknowledgmentsWe are grateful to all the scientific consultants of this paper.