Equitable distribution of services at the regional scale and achieving a balanced spatial structure in the region are among the most important goals of sustainable regional planning, especially in developing countries such as Iran. In this regard, one of the most important strategies and policies in regional spatial planning is the decentralization of development. The purpose of this study is to identify the most important urban areas of Fars province in order to determine the priorities of development and decentralization of the unipolar development of the province. To this end, the regional network modelling based on graph theory and the concepts of social network analysis are used to conduct the spatial analysis of Fars province. The data used in this study includes  the Fars province road network extracted from the OSM open source system, as well as the spatial information of the urban and rural areas of Fars province extracted from the website of the Statistics Center of Iran. Regarding research methods, Pandas Library and NetworkX Library were used in the Python programming platform to form the network graph and analyze the centrality indicators, while ARC GIS software was for final processing and visualization of data and information. According to thenetwork centrality indices and the location of the province cities, notwithstanding Shiraz as the main hub of development in the province, Zarghan, Sadra, Kavar, Lepui, Khane Zenian and Noorabad are the main development priorities. In addition, the Shiraz-Marvdasht and Shiraz-Khaneh Zenian roads were determined to be the most important transportation paths and communication corridors. The results and findings of this study showed that network-based modeling and the use of graph-based analytics (in particular, social network analysis techniques) can be useful and effective as new analytical methods in regional studies and planning.

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.

One of the important aspects of development from the spatial perspective is the evaluation of the effective long-term processes on the institutional mechanisms of a land and the determination of share of the respective areas in this regard. For many years, economy has been hurriedly moving toward a knowledge-based stance, and the countries that have neglected this movement have been deprived of fundamental developments. In this applied study, which adopts an analytical approach and a quantitative view, the necessity of the proposition of a strategic attitude to the two-way relationship between higher education and the industry sector of Iran is addressed. To this end, first an overview of the previous studies and theoretical principles are made. Then, following the questions and hypotheses and determining the evaluation and analysis methods, the detailed information on over 11 variables (including panel data of 31 provinces of Iran from 2016 to 2019) are collected. These are then analyzed and tested using Excel, Eviews, and Arc GIS through spatial econometrics, generalized method of moments (GMM), weight matrix and geographic-spatial correlation (λ), and KP-HET diagnostic tests. According to the results, the spatial correlation between higher education and industry in Iran is highly significant, and the shock resulting from the industrial and educational development is completely mutual. That is to say, the shock inflicted upon a given province has spread to other provinces of Iran. The findings of this study confirm the effects of the emphasis on the centralization policy stereotype and the prescriptive – rather than land-use-based – roles given to certain parts of Iran. In fact, the very high spatial correlation demonstrates that the nine less-developed provinces of Iran have experienced trivial industrial growth due to a lack of higher education infrastructure. On the other hand, the results of this study shows how the market demand for labor of the university graduates is aligned with the functions of the knowledge-based industries of Iran.