Spatial Analysis Quality of Life in Urban Areas Using Geographic Information System (GIS) (Case Study: District 2 of Mashhad)

The present study is descriptive-analytical and for the purpose of application. The main objective of the present research is to develop a combination of quality of life indicators for neighborhoods in District 2 of Mashhad. The required information was obtained from the municipality of Mashhad and the questionnaire was used. According to the population of Region 2 in 1395, which is 513365 people, according to the Cochran formula, 383 questionnaires were arranged. The questionnaire was completed after the preparation and implementation of experts' opinions by referring at the level of the studied sites. The required criteria were prepared and standardized in the form of spatial information in the GIS environment. Economic, social and access areas were selected as the main criteria for research and were identified for each of the following criteria. Subsequently, using spatial analysis and multi-criteria decision making model (ANP), the final quality of life index was derived from the integration of indicators. The results indicate a good quality of life in the central neighborhoods, and there are no marginal areas of desirable quality. It also increases the level of quality of life in the vicinity of the recreational centers and follows the spatial patterns. Part of the margin of the agent's neighborhoods, the martyr Basir and Hedayat, which are the marginal areas of the study area, are not in the best of all three territories; and other neighborhoods due to easy access to public services, including health services, training, and facility focus Modern welfare has a better quality of life than other neighborhoods, of which 11675700 square meters, which is equivalent to 30 percent of the area of ​​the study area, has a very good quality of life. Also, sites that are very low in terms of economic and social indicators are moderate in terms of access. In the following, the results of spatial statistics tests (spatial spatial correlation and J statistics) indicate the distribution of the cluster model of quality of life. In other words, quality of life indicators do not have the same spatial distribution in the study area.