Today, given the rapid growth of the world's population and its focus on cities, access to quality housing by urban dwellers is an essential component of influencing the long-term outlook of human communities. At the same time, considering the widespread impacts of housing on urban environments and on the economic, social and physical life of the city and its citizens, it is important to identify the factors that influence the choice of place of residence and housing. The residence has been emphasized on housing features. The type of research was applied and descriptive-analytical in nature; the method of data collection is library and field (questionnaire). The study population consisted of 384 households living in Tabriz metropolitan area. Then, tests (descriptive and inferential statistics) will be used and finally by diagnostic analysis using SPSS ₂₂ and GIS software will analyze the relationships between variables. The results showed that demographic and lifestyle indices affect residence and housing choice and when demographic characteristics are combined with lifestyle, the choice of residence by the households is examined based on differences. Individual and lifestyle are important. Also, based on the results of the research, selection of residence and housing has a significant relationship with access to business centers, childcare centers, cultural centers, pedestrian access, parking and home warning cameras.

In the history of humanity, human always has suffered all difficulties with effort to reach to comfort and well-being until the human provides a way to achieve the comfort. In the viewpoint of climate four elements have significant role in formation of human comfort and discomfort conditions that according to the climatic conditions in different areas, the type and effect of these elements on individuals are also different. The aim of this research is to determine the areas of climatic comfort. For this purpose, temperature, precipitation and humidity data were derived from database of Esfazari for Khuzestan province during statistical period 1965 to 2014. In this process, at first discomfort climate has been defined using temperature, precipitation and humidity based on distribution probability conditional. This research is to determine the areas of climatic comfort in Khuzestan province using multivariate analysis (Cluster analysis and Discriminant analysis) and spatial autocorrelation pattern (Hot Spot index and Moran index) with emphasis on architecture. The results showed that the areas with climatic comfort are included in north and east parts of Khuzestan province. However, the areas of climatic comfort by spatial method have been limited somewhat. Results further indicated that the areas of climatic comfort have decreased significantly towards recent periods especially in cluster analysis and discriminant analysis that a trend of reduction has been remarkable in cluster analysis (from 23.60% in the first period to 17.60% in the fifth period) and discriminant analysis (from 26.97% in the first period to 14.98% in the fifth period).