Abstract

Atmospheric aerosol optical depth (AOD) products based on orbiting satellites such the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS) and National Oceanic and Atmospheric Administration (NOAA)'s Geostationary Operational Environmental Satellite (GOES) Aerosol Smoke Products (GASP) can provide global and regional daily AOD distributions. Their application to air quality monitoring at local scales such as urban environments is rather limited due to their coarse spatial resolution. Recently, there has been a growing interest in retrieving AOD products based on high resolution optical imagery. The primary objectives of this research study are to assess AOD retrieval over urban city areas using high spatial resolution satellite imagery. With the assumption of Lambertian surface, the principle of AOD retrieval developed is based on the radiative transfer theory using Tanré Equation. To solve the radiative transfer equation, the study adopted the radiative transfer model Second Simulation of the Satellite Signal in the Solar Spectrum (6S) and constructed a Look-Up-Table (LUT) assuming a continental aerosol model. The land surface reflectance (LSR) over the entire study period using Landsat 8 OLI for the period 2016–2017 showed very little variability. The retrieval of AOD is performed by comparing measured and simulated TOA reflectance. The validation is performed using an AERONET Masdar Institute ground based site located within the study area and the 10 km resolution MODIS Collection (C6) Deep Blue AOD (MOD04) products. The validation shows that AOD retrieval approach yields a root mean square error (RMSE) of 0.04, a good correlation with an R2 equivalent to 67% and that the 58% of the retrieved values fall within the expected error (EE). Also, results show that Landsat-OLI retrieval are better and less biased as compared to MOD04 AOD products and that the used approach can provide much more details compared to the 10 km Deep Blue MODIS AOD products.

Full Text
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