Abstarct: Air pollutants include ozone (O3), nitrous oxide (NOX), carbon monoxide (CO), particulate matter, sulfur dioxide (SO2), etc. Most of these pollutants are the result of combustion of fossil fuels. Daily air quality is determined by the AQI index. The AQI index or air quality index is an indicator for predicting daily air quality, which indicates whether the air is clean or polluted and how it relates to our health levels. Air pollution in Mashhad has been increasing in recent years and according to available statistics, the city of Mashhad is facing the phenomenon of temperature inversion about 260 days a year. Accordingly, in this study, air pollution has been monitored in Mashhad using ground data and satellite data to determine the distribution of air pollution indicators. This research is practical in terms of purpose because it tries to identify pollution zones in Mashhad and in terms of data is field and spatial type. Google Earth systems are engines. To prepare air pollution maps using Sentinel satellite, Google Earth Engine system has been used and to prepare maps using ground stations after collecting field data through interpolation in arc gis environment, pollution maps have been prepared. The maximum concentration of carbon monoxide is 1.68. The concentration of sulfur dioxide in winter has the highest amount of 37.84. The amount of ozone in spring is 19.28. Also, the amount of nitrogen dioxide in winter is 37.84 more than other seasons, in which Karimi and Khayyam Shomali stations have the highest amount of this pollutant. The highest concentrations of sulfur dioxide occur in spring and winter. Building, grass and target stations had the highest values. The Moran index coefficient for the spatial distribution of pollution is 0.4617, which indicates the clustering of pollution. Considering that the value: Z core = 23.81 and is greater than the expected value (E_I = 2.58) Also, the values of R2 and R2 (Adjusted R2) of the geographic weight regression model in this research are 0.6678 and 0.5727, respectively, which indicates Acceptable accuracy of the research variables in modeling the spatial relationships of industrial land uses, population density and land use of green spaces and gardens with air pollution. The model was able to evaluate up to %66 of the existing relationship.