The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B3-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 419–423, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-419-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 419–423, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-419-2021

  28 Jun 2021

28 Jun 2021

USING MODIS AEROSOL OPTICAL DEPTH TO PREDICT PM10 OVER AL AIN REGION, UAE

N. Saleous1, S. Issa2, and M. Alsuwaidi1 N. Saleous et al.
  • 1Dept. of Geography, College of Humanities and Social Sciences, UAEU, Al Ain, UAE
  • 2Dept. of Geology, College of Science, UAEU, Al Ain, UAE

Keywords: Air quality, Particulate matter, Aerosol optical depth, MODIS, regression, UAE

Abstract. PM10 concentrations are essential for assessing air quality in arid areas. They are usually measured at air quality monitoring stations. The limited number of monitoring stations can make difficult to study significantly the spatial variability of PM10 over relatively large areas. This study aimed at evaluating the use of Aerosol Optical Depth derived from satellite data to estimate PM10 concentrations. The continuous coverage offered by remote sensing data helps to address the limitation encountered with the spatial distribution of relevant monitoring stations. In the current study we compared MODIS AOD at 550 nm included in MCD19A2 and we established a regression equation between AOD and PM10. The use of daily AOD at 1 km resolution helped establish regression with acceptable correlation coefficient. The regression equation is then used to create daily maps of estimated PM10 concentrations over the study area and helped assessing their variability.