Determining the Levels of Urbanization in Iran Using Hierar-chical Clustering

Abstract

Background: In this study, we used a variety of factors that affect urbanization in Iran to evaluate different provinces in Iran in terms of the level of urbanization.

Methods: Using information from census 2011, we collected data on 33 indicators related to urbanization in 31 provinces in Iran. To rank the provinces we used density-based hierarchical clustering scheme. To determine similarities or differences between the provinces, the square of the Euclidean distance dissimilarity coefficient; Ward’s algorithm was used to merge the provinces to minimize intra-cluster variance. One-way analysis of variance (ANOVA) was used to determine the variance between the variables used to rank the provinces in terms of different levels of urbanization. Statistical analysis was performed using SPSS.

Results: The provinces in Iran were combined with each other in 30 stages and classified into four levels. Taking into account the variables used to rank the level of urbanization, Tehran, and Alborz provinces were at the highest level of urbanization. On the other hand, the provinces of Sistan and Baluchistan, Kerman, North Khorasan, South Khorasan, Hormozgan, and Bushehr were at the lowest level of urbanization.

Conclusion: Identification of provinces at the same level of urbanization can help us to discover the strengths and weaknesses in the infrastructures of each of them. Given the differences between various levels of urbanization, the identification of factors that are effective in the process of urbanization can help to access more information required for designing plans for the years to come.