Wei, J; Li, ZQ; Sun, L; Yang, YK; Zhao, CF; Cai, ZX (2019). Enhanced Aerosol Estimations From Suomi-NPP VIIRS Images Over Heterogeneous Surfaces. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 57(12), 9534-9543.
Abstract
The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (NPP) is a new-generation polar-orbiting satellite imaging sensor. It has generated a variety of operational products similar to the widely used Moderate Resolution Imaging Spectroradiometer (MODIS) products. However, there are high uncertainties in official VIIRS aerosol products based on our previous validations, and a reduction in these uncertainties is needed before they can be used with confidence. To this end, we developed a revised high-spatial-resolution aerosol retrieval algorithm which can considerably improve the aerosol optical depth (AOD) estimations. The improvements mainly arise from: 1) correction of the surface bidirectional reflectance using the RossThick-LiSparse model with parameters obtained from the MODIS bidirectional reflectance distribution function (BRDF)/Albedo products; 2) finer customized monthly aerosol types assumed from the historical Aerosol Robotic Network (AERONET) measurements of optical properties; and 3) improved cloud screening with the revised dynamic threshold cloud detection algorithm. The new 750-m AOD retrievals are validated against AERONET AOD measurements and compared with the official VIIRS AOD products from 2014 to 2017 over the BeijingTianjinHebei region in China. The results illustrated that the retrievals are highly consistent with ground measurements ($R = 0.926$ ), with 72 of them falling within the expected error of [(0.05 20)] on a regional scale. The mean absolute error is 0.082 and the root-mean-square error is 0.120. The new algorithm can significantly reduce the overestimations and improve the aerosol estimations over heterogeneous urban surfaces compared to the official aerosol products, especially in winter. This new VIIRS AOD product will thus be more useful for air pollution studies over medium- or small-scale areas.
DOI:
10.1109/TGRS.2019.2927432
ISSN:
0196-2892