The concentration of absorbable particulate matter less than 10 μm termed as PM10 is the most important urban air pollution index for air quality monitoring. This paper presents a space based PM10 monitoring algorith...The concentration of absorbable particulate matter less than 10 μm termed as PM10 is the most important urban air pollution index for air quality monitoring. This paper presents a space based PM10 monitoring algorithm based on QUAC （QUick atmosphere correction） for optical remote sensing data and SVR （support vector regression）. PM 10 concentration measurements from nine ground based stations in Hangzhou, China and the MODIS （moderate-resolution imaging spectroradiometer） images were analyzed. Experimental result indicates that the correlation between CD （correction differences） with actual measured data is better than correlation between AOD （aerosol optical depth） with measured data. In addition, the fitting performance of the SVR model established with CD and measured data is better than traditional regression models.展开更多
文摘The concentration of absorbable particulate matter less than 10 μm termed as PM10 is the most important urban air pollution index for air quality monitoring. This paper presents a space based PM10 monitoring algorithm based on QUAC （QUick atmosphere correction） for optical remote sensing data and SVR （support vector regression）. PM 10 concentration measurements from nine ground based stations in Hangzhou, China and the MODIS （moderate-resolution imaging spectroradiometer） images were analyzed. Experimental result indicates that the correlation between CD （correction differences） with actual measured data is better than correlation between AOD （aerosol optical depth） with measured data. In addition, the fitting performance of the SVR model established with CD and measured data is better than traditional regression models.
