Monitoring the Spatio-Temporal Dynamics of Air Pollution in Tabriz by Using of Remote Sensing and GIS

pollutants and determining the effective factors in the concentration of elements of suspended particles, sulfur dioxide, nitrogen dioxide and ozone, in the city of Tabriz in the long-term average time period (4 years) for changes in concentration and from the average of two dry and wet periods. In 2022, geographic weighted regression and clustering of the study area were used for spatial modeling. In this study, out of 8 variables (normalized vegetation cover, population density, construction density, density density, size of industrial areas, NTL (night light) and surface temperature, average prevailing wind speed, digital model of height) the digital model variable of height and average speed were selected Wind was dominant due to multicollinearity or (VIF) were removed from the model in correlation studies, and the effective factors in pollution elements were processed and standardized. The results of this study showed that the accuracy of the GWR model is better compared to the OLS model. By generating coefficients for each of the selected factors in the model, GWR determines the location of polluting elements and the most influential factor. According to the results of industrial size density, among the modeled parameters, it had the highest coefficient in the spatial model of the concentration of pollution elements. K-means clustering method using the map of coefficients obtained with GWR for zoning the city of Tabriz according to the spatial-temporal relationship of polluting elements with factors into 6 clustering zones, where zone 1-3 has the largest area and has high influence coefficients in all four pollutants. In fact, zones 1-3 can be considered in the management of urban policies in pollution control.