Quality of life is the ability of environment to supplying and supporting the material and spiritual needs of people, which include concepts such as individual well-being (health, healthcare), social welfare (security, environmental quality, etc.) and spatial equity (access and the same distribution services and urban facilities). Quality of life used to be a key concept and an efficient tools for place ranking, identifying and documenting the causes of class differences in the cities and it have been interest to administrators and urban planners. This thesis aims to assess the quality of urban life on the dispersion of population parameters. For this purpose, three basic parameters for assessing the quality of urban life is considered. These parameters include the socio-economic, environmental and spatial equity.
For assessing the socio-economic aspect, census data is used. Pearson’s correlation was computed to analyze the relationships among the variables. Further, factor analysis was conducted to extract unique information from the combined dataset. four factors were identified and interpreted as Housing conditions, Working and literacy conditions, Educational status and activity status and income respectively. Each factor was viewed as a unique aspect of socio-economic parameter of the quality of life. As well as to assess the environmental parameter of quality of life by using satellite imagery and geospatial data some information like maps of NDVI index, land surface temperature, air pollution and noise pollution were extracted, and final index of the environmental parameter was obtained by integration of them.. For evaluating spatial equity two indicators, Accessibility and mixed land use was considered. Equal distribution and access to urban services was measured by these two indicators. This evaluation done for the educational, health, commercial, parks, sports, religious and cultural land use.
To investigate the spatial distribution of QOL index, Moran's spatial autocorrelation is used. The results showed that the quality of life index in the studied region is clustered and places by similar value are neighbor. Finally, for investigate the relationship between final extracted index for each aspect of quality of life with each other, the Pearson correlation analysis was used. The results showed a positive correlation between socio-economic index with spatial equity (0.543) and environmental index (0.415). Actually making some basic change in these aspect of QOL can result in reducing of difference between QOL of poor and rich zone of city and can supply the basis of improvement of them. Also it can change the situation of equality and justice in all aspect QOL.