4.7 Article

Improved Aerosol Optical Depth and Angstrom Exponent Retrieval Over Land From MODIS Based on the Non-Lambertian Forward Model

期刊

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 11, 期 9, 页码 1629-1633

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2014.2303317

关键词

Aerosol optical depth; Angstrom exponent (AE); bidirectional reflectance distribution functions (BRDF); dark target (DT); Moderate Resolution Imaging Spectroradiometer (MODIS); non-Lambertian forward model (FM) (NL_FM)

资金

  1. Ministry of Science and Technology of China [2013CB733403]
  2. National Science Foundation of China [41271371, 41101323]
  3. Young Scientist Foundation of Henan Polytechnic University [Q2012-35]

向作者/读者索取更多资源

In this letter, an improved algorithm for aerosol retrieval is presented by employing the non-Lambertian forward model (forward model) (NL_FM) in the Moderate Resolution Imaging Spectroradiometer (MODIS) dark target (DT) algorithm to reduce the uncertainties induced when using the Lambertian FM (L_FM). This new algorithm was applied to MODIS measurements of the whole year of 2008 over Eastern China. By comparing the results with that of AERONET, we found that the accuracy of the aerosol optical depth (AOD) retrieval was improved with the regression plots concentrating around the 1 : 1 line and two-thirds falling within the expected error (EE) envelope EE = +/- 0.05 +/- 0.1 tau (from 53.6% with L_FM to 68.7% with NL_FM at band 0.55 mu m). Surprisingly, more accurate retrieval of the AOD demonstrated significantly improved the Angstrom exponent (AE) retrieval, which is related to particle size parameters. The regression plots tended to concentrate around the 1 : 1 line, and many more fell within the EE = +/- 0.4 from 53.6% with L_FM to 80.9% with NL_FM. These results demonstrate that including the NL_FM in the MODIS DT algorithm has the potential to significantly improve both AOD and AE retrievals with respect to AERONET in comparison to the L_FM used in the current MODIS operational retrievals.

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