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8 November 2014 Retrieval of aerosol optical depth over bare soil surfaces using time series of MODIS imagery
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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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Zhengwu Yuan, Ranyin Yuan, and Bo Zhong "Retrieval of aerosol optical depth over bare soil surfaces using time series of MODIS imagery", Proc. SPIE 9259, Remote Sensing of the Atmosphere, Clouds, and Precipitation V, 92591Q (8 November 2014);

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