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One of the most important pollutants that its surveillance in the atmosphere by remote sensing is possible is the suspended particles density using the MODIS sensor images. In the analyzing related to pollution study, the studies of distribution and relation between variables have an important role that the regression analyzing applications in these studies is inevitable. The main goals of this paper is preparing the particulate matter less than 10 micron distribution in Khuzestan province in both hourly/daily periods using the linear regression models the AOD product, the MODIS sensor also the ground stations data of the atmosphere pollution measurement and lateral insight of Ahvaz city in 2009 in order to estimating the pm10 were used. The results showed MODIS data have high accuracy to estimate the atmosphere pollutions and results indicates that the hourly period with R square 90% against daily period with R square 76% have a higher coefficient. After the model estimating correction by interpolating the produced plots by using the resultant relation in both time periods the suspended particles distribution maps were prepared. Key Word: ,MODIS,Ahvaz, suspended particles;linear regression Key Word: ,MODIS,Ahvaz, suspended particles;linear regression Key Word: ,MODIS,Ahvaz, suspended particles;linear regression Key Word: ,MODIS,Ahvaz, suspended particles;linear regression

Keywords: Key Word:, MODIS, Ahvaz, suspended particles, linear regression

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