Retrieval of aerosol optical depth over bright land surfaces by coupling bidirectional reflectance distribution function model and aerosol retrieval model |
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| Authors: | Jie Guang Yingjie Li Shunlin Liang Linlu Mei Hui Xu |
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| Affiliation: | 1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University , Beijing , 100101 , PR China;2. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University , Beijing , 100101 , PR China;3. Graduate University of the Chinese Academy of Sciences , Beijing , 100049 , PR China;4. Department of Geography , University of Maryland , College Park , MD , 20742 , USA;5. College of Global Change and Earth System Science, Beijing Normal University , Beijing , 100875 , PR China |
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| Abstract: | A novel aerosol optical depth (AOD) retrieval algorithm is developed by integrating a kernel-driven bidirectional reflectance distribution function (BRDF) model and the multi-satellite AOD retrieval model for Moderate Resolution Imaging Spectroradiometer (MODIS) data. As there is close coupling of AOD and surface reflectance in satellite signal, one will be traditionally assuming a prior in order to solve another one. However, we build a group of equations to solve both AOD and surface reflectance at the same time in our algorithm. Applying this new algorithm to Terra and Aqua MODIS data in Beijing, China, allows AOD and surface reflectance of this region to be retrieved. Results indicate that the MODIS AOD derived from the new method is consistent with AErosol RObotic NETwork (AERONET), with correlation coefficient (R 2) of 0.812 and root mean square error (RMSE) of 0.04 at 0.55 μm. |
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