High-resolution aerosol remote sensing retrieval over urban areas by synergetic use of HJ-1 CCD and MODIS data

Satellite aerosol remote sensing over urban areas is still a difficult task because of the high reflectance of the underlying surface. Many aerosol retrieval algorithms are appropriate for ‘dark’ pixels and provide aerosol products with low resolutions. In this paper, we present a new aerosol retrieval algorithm that applies the synergetic use of small satellite data and Moderate Resolution Imaging Spectroradiometer (MODIS) data. The algorithm was applied to data from the China HJ-1A/1B of the Environment and Disasters Monitoring Microsatellite Constellation Charge-Coupled Device (CCD) camera and Terra MODIS data. To downscale 500 m MODIS data, a new method based on mutual information was developed. By applying this algorithm to aerosol retrieval over Beijing City, we obtain the aerosol optical depth (AOD) with a 100 m × 100 m resolution. A comparison of our results to the ground measurement data from Aerosol Robotic Network (AERONET) sites and Huailai Remote Sensing Test Field, which are measured by CE318 automatic sun tracking photometer, shows a correlation coefficient of approximately 0.89 and a root-mean-square error (RMSE) of about 0.24. The uncertainty for AOD (τ) is found to be Δτ = ±0.05 ± 0.20τ. The algorithm could potentially be useful for other small satellite constellation data. High-resolution AOD is very useful and powerful for urban air quality monitoring and other applications.

► A new AOD retrieval algorithm that applies the synergetic use of small satellite HJ-1 data and MODIS data over land.
► To downscale 500-m MODIS data, a new method based on mutual information (MI) was developed.
► Validation shows an RMSE of less than 0.24 and a correlation coefficient of approximately 0.89.
► The uncertainty for AOD (τ) is found to be Δτ = ±0.05 ± 0.20τ.
► The algorithm could potentially be useful for small satellite constellation data to derive AOD data at a high resolution.