High-resolution aerosol retrieval over urban areas using sentinel-2 data

Accurate retrieval of Aerosol Optical Depth (AOD) data from satellite remote sensing images over urban areas is of great importance, e.g. for air-quality monitoring. However, limited by coarse spatial resolution, available aerosol products are unable to fulfil the increasing demand of aerosol retrieval below the city scale. To address this issue, a new high-resolution (60 m) aerosol retrieval algorithm based on Sentinel-2 data over urban areas was developed. To improve the estimation of surface reflectance, two algorithms: (1) the new visible/2.19 μm surface reflectance relationships as a function of normalized difference vegetation index (NDVI) for vegetated areas; and (2) the surface reflectance database preconstructed from the operational high-quality and high-resolution Landsat 8 surface reflectance products for bright areas, were adopted depending on the surface types. For validation, the derived retrievals from Sentinel-2, along with the operational MODerate resolution Imaging Spectrometer Collection 6 (C6) aerosol products (MOD04_L2 and MCD19A2), were compared with measurements from Aerosol Robotic Network (AERONET) stations. The validation results show that the Sentinel-2 AOD retrievals agreed well with the AERONET AOD measurements, with an overall correlation coefficient of 0.907, expected error (EE) of 73.76%, mean absolute error (MAE) of 0.087, and root mean square error (RMSE) of 0.117. Comparison of the results with MOD04_L2 products (10 km) show that the Sentinel-2 AODs were superior in the situations considered, indicating that the new algorithm performed better in AOD retrieval over urban areas. Compared with the fine spatial resolution MCD19A2 products (1 km), retrievals of the proposed algorithm were comparable. The new algorithm is able to retrieve high-resolution AODs reasonably well from Sentinel-2 images over urban areas, and can provide continuous and detailed aerosol spatial distributions. Owing to the ability of the Sentinel-2 satellite to provide observations at 5-day intervals, the proposed algorithm is capable of monitoring aerosol distributions at relatively fine temporal resolution.