In this paper, a novel algorithm for aerosol optical depth（AOD） retrieval with a 1 km spatial resolution over land is presented using the Advanced Along Track Scanning Radiometer （AATSR） dual-view capability at 0....In this paper, a novel algorithm for aerosol optical depth（AOD） retrieval with a 1 km spatial resolution over land is presented using the Advanced Along Track Scanning Radiometer （AATSR） dual-view capability at 0.55, 0.66 and 0.87μm, in combination with the Bi-directional Reflectance Distribution Function （BRDF） model, a product of the Moderate Resolution Imaging Spectroradiometer （MODIS）. The BRDF characteristics of the land surface, i.e. prior input parameters for this algorithm, are computed by extracting the geometrical information from AATSR and reducing the kernels from the MODIS BRDF/Albedo Model Parameters Product. Finally, AOD, with a i km resolution at 0.55, 0.66 and 0.87 μm for the forward and nadir views of AATSR, can be simultaneously obtained. Extensive validations of AOD derived from AATSR during the period from August 2005 to July 2006 in Beijing and its surrounding area, against in-situ AErosol RObotic NETwork （AERONET） measurements, were performed. The AOD difference between the retrievals from the forward and nadir views of AATSR was less than 5.72%, 1.9% and 13.7%, respectively. Meanwhile, it was found that the AATSR retrievals using the synergic algorithm developed in this paper are more favorable than those by assuming a Lambert surface, for the coefficient of determination between AATSR derived AOD and AERONET mearured AOD, decreased by 15.5% and 18.5%, compared to those derived by the synergic algorithm. This further suggests that the synergic algorithm can be potentially used in climate change and air quality monitoring.展开更多
基金an output from the research projects entitled "Study on the Na-tional AOD Retrieval System based on MODIS Data" supported by the Special Funds for the Basic Research in Chinese Academy of Meteorological Sciences (CAMS) of Chinese Meteorological Administration (CMA) (2007Y001)"Multi-scale Aerosol Optical Thickness Quantitative Retrieval from Remotely Sensing Data at Urban Area"(40671142)+2 种基金the project (Grant Nos. 40871173,40601068) funded by National Natural Science Foundation of ChinaInnovation Fund by State Key Laboratoryof Remote Sensing Sciences, Institute of Remote Sensing Applications of Chinese Academy of Sciences (Grant Nos.07S00502CX, 03Q0033049)"Aerosol over China and Their Climate Effect" supported by National Basic Research Program of China (2006CB403701)
文摘In this paper, a novel algorithm for aerosol optical depth（AOD） retrieval with a 1 km spatial resolution over land is presented using the Advanced Along Track Scanning Radiometer （AATSR） dual-view capability at 0.55, 0.66 and 0.87μm, in combination with the Bi-directional Reflectance Distribution Function （BRDF） model, a product of the Moderate Resolution Imaging Spectroradiometer （MODIS）. The BRDF characteristics of the land surface, i.e. prior input parameters for this algorithm, are computed by extracting the geometrical information from AATSR and reducing the kernels from the MODIS BRDF/Albedo Model Parameters Product. Finally, AOD, with a i km resolution at 0.55, 0.66 and 0.87 μm for the forward and nadir views of AATSR, can be simultaneously obtained. Extensive validations of AOD derived from AATSR during the period from August 2005 to July 2006 in Beijing and its surrounding area, against in-situ AErosol RObotic NETwork （AERONET） measurements, were performed. The AOD difference between the retrievals from the forward and nadir views of AATSR was less than 5.72%, 1.9% and 13.7%, respectively. Meanwhile, it was found that the AATSR retrievals using the synergic algorithm developed in this paper are more favorable than those by assuming a Lambert surface, for the coefficient of determination between AATSR derived AOD and AERONET mearured AOD, decreased by 15.5% and 18.5%, compared to those derived by the synergic algorithm. This further suggests that the synergic algorithm can be potentially used in climate change and air quality monitoring.
