Aerosol Optical Depth (AOD) is one of the key parameters which can not only reflect the characterization of atmospheric
turbidity, but also identify the climate effects of aerosol. The current MODIS aerosol estimation algorithm over land is
based on the “dark-target” approach which works only over densely vegetated surfaces. For non-densely vegetated
surfaces (such as snow/ice, desert, and bare soil surfaces), this method will be failed. In this study, we develop an algorithm
to derive AOD over the bare soil surfaces. Firstly, this method uses the time series of MODIS imagery to detect the “
clearest” observations during the non-growing season in multiple years for each pixel. Secondly, the “clearest”
observations after suitable atmospheric correction are used to fit the bare soil’s bidirectional reflectance distribution
function (BRDF) using Kernel model. As long as the bare soil’s BRDF is established, the surface reflectance of “hazy”
observations can be simulated. Eventually, the AOD over the bare soil surfaces are derived. Preliminary validation results
by comparing with the ground measurements from AERONET at Xianghe sites show a good agreement.
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