Retrieval of aerosol optical depth over bright land surfaces by coupling bidirectional reflectance distribution function model and aerosol retrieval model
Jie Guang, Yong Xue, Yingjie Li, Shunlin Liang, Linlu Mei, Hui Xu
- Year
- 2011
- Citations
- 12
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.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992