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Proceedings Paper

Satellite aerosol retrieval using dark target algorithm by coupling BRDF effect over AERONET site
Author(s): Leiku Yang; Yong Xue; Jie Guang; Chi Li
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Paper Abstract

For most satellite aerosol retrieval algorithms even for multi-angle instrument, the simple forward model (FM) based on Lambertian surface assumption is employed to simulate top of the atmosphere (TOA) spectral reflectance, which does not fully consider the surface bi-directional reflectance functions (BRDF) effect. The approximating forward model largely simplifies the radiative transfer model, reduces the size of the look-up tables, and creates faster algorithm. At the same time, it creates systematic biases in the aerosol optical depth (AOD) retrieval. AOD product from the Moderate Resolution Imaging Spectro-radiometer (MODIS) data based on the dark target algorithm is considered as one of accurate satellite aerosol products at present. Though it performs well at a global scale, uncertainties are still found on regional in a lot of studies. The Lambertian surface assumpiton employed in the retrieving algorithm may be one of the uncertain factors. In this study, we first use radiative transfer simulations over dark target to assess the uncertainty to what extent is introduced from the Lambertian surface assumption. The result shows that the uncertainties of AOD retrieval could reach up to ±0.3. Then the Lambertian FM (L_FM) and the BRDF FM (BRDF_FM) are respectively employed in AOD retrieval using dark target algorithm from MODARNSS (MODIS/Terra and MODIS/Aqua Atmosphere Aeronet Subsetting Product) data over Beijing AERONET site. The validation shows that accuracy in AOD retrieval has been improved by employing the BRDF_FM accounting for the surface BRDF effect, the regression slope of scatter plots with retrieved AOD against AEROENET AOD increases from 0.7163 (for L_FM) to 0.7776 (for BRDF_FM) and the intercept decreases from 0.0778 (for L_FM) to 0.0627 (for BRDF_FM).

Paper Details

Date Published: 13 November 2012
PDF: 12 pages
Proc. SPIE 8523, Remote Sensing of the Atmosphere, Clouds, and Precipitation IV, 85231J (13 November 2012); doi: 10.1117/12.977186
Show Author Affiliations
Leiku Yang, Beijing Normal Univ. (China)
Institute of Remote Sensing Applications (China)
Henan Polytechnic Univ. (China)
Yong Xue, Institute of Remote Sensing Applications (China)
London Metropolitan Univ. (United Kingdom)
Jie Guang, Institute of Remote Sensing Applications (China)
Chi Li, Ctr. for Earth Observation and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 8523:
Remote Sensing of the Atmosphere, Clouds, and Precipitation IV
Tadahiro Hayasaka; Kenji Nakamura; Eastwood Im, Editor(s)

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