An atmospheric correction algorithm for hyperspectral imagery with collaborative retrieval of aerosol optical thickness and water vapor content
DIAN Yuanyong1, FANG Shenghui2, XU Yongrong1
1. College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan 430070, China;
2. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Atmospheric correction is the basic step in quantitative retrieval of land surface parameters with hyperspectral imagery. Based on abundant spectral information in the hyperspectral image,this paper presents a new atmospheric correction algorithm for hyperspectral imagery characterized by collaborative retrieval of the aerosol optical thickness (AOT) and the water vapor content (WV). The algorithm takes into account the effects of aerosol type,AOT and WV,and uses the iteration method combined with the 6S(second simulation of the satellite signal in the solar spectrum)radiative transfer model to retrieve the atmospheric parameters and ground reflectance. This new method overcomes the weakness of the existing atmospheric correction algorithms which fail to consider the effects of both AOT and WV. Hyperion hyperspectral image data covering Wuhan City were used to verify the effectiveness of the algorithm proposed in this paper,with the results compared with those of FLAASH(fast line-of-sight atmospheric analysis of spectral hypercubes)method in ENVI and MODIS's AOT and WV products. It is shown that the proposed algorithm can better correct the effect of aerosol and water vapor in the atmosphere,and needs no additional parameters because all the inputs are taken from the image data themselves or the 6S radiative transfer model in the inversion process.
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2015, Vol. 27 
