Analysis of quantitative and qualitative indicators of housing using Self-correlation spatial technique (Case Study: oroumieh city)

Today, housing not only serves as shelter for human settlements, but also as a place where most of the social, economic, and cultural needs of the population are formed and provided in residential units. But access to affordable housing is one of the most important issues in today's societies due to the rapid growth of the population and the increase in household expenses, So that With the growing of large cities, informal settlements and inappropriate housing in most urban areas have created an irrefutable perspective. Therefore, the aim of this study is to study the quantitative and qualitative indices of housing in the level of statistical blocks. The research is applied and the required information from the general census of population and housing in the range of statistical blocks (7096 blocks) for 2011 was prepared and 17 indicators were selected and evaluated by a factor analysis technique that resulted in 4 effective factors. The results of data analysis were transferred to Arc GIS10.3 software and to investigate the status of statistical blocks in terms of availability of housing indices, hot spots analysis was applied and spatial correlation technique was used to identify the distribution pattern of indicators. The results of combined factor analyze show that 31% of the blocks are very poor, 30% average, 28% are in very good condition. Based on Moran’s correlation analysis, oroumieh urban housing indices distribution pattern is a randomized cluster.