一种协同反演气溶胶与水汽含量的高光谱图像大气校正算法  

An atmospheric correction algorithm for hyperspectral imagery with collaborative retrieval of aerosol optical thickness and water vapor content

作　　者：佃袁勇[1] 方圣辉[2] 徐永荣[1] 

机构地区：[1]华中农业大学园艺林学学院,武汉430070 [2]武汉大学遥感信息工程学院,武汉430079

出　　处：《国土资源遥感》2015年第2期22-28,共7页Remote Sensing for Land & Resources

基　　金：国家863项目"多尺度遥感数据按需快速处理与定量遥感产品生成关键技术"(编号:2012AA12A304)和"作物生长信息的数字化获取与解析技术"(编号:2013AA102401);国家自然科学基金项目"基于叶面积指数的城市绿地固碳释氧与降温增湿功能反演"(编号:31270744);中央高校基本科研业务费专项资金项目"基于时间序列遥感影像的三峡库区森林覆盖及动态变化监测"(编号:2014QC018);地理国情监测国家测绘地理信息局重点实验室项目"多分辨率遥感影像的变化检测算法研究"(编号:2013NGC05)共同资助

摘　　要：大气校正是高光谱图像定量反演地表参数的前提。为充分利用高光谱数据本身的光谱特点,提出了一种协同反演大气气溶胶光学厚度(aerosol optical thickness,AOT)与水汽含量(water vapor content,WV)的大气校正方法,在同时考虑了气溶胶模式、AOT和WV这3个因素的综合影响基础上,采用循环迭代的思想,基于6S辐射传输模型,反演大气参数及地表反射率,弥补了现有反演算法中没有同时考虑AOT与WV的不足;并以武汉市Hyperion高光谱图像为例,验证了该算法的有效性。从与FLAASH算法及MOIDS提供的AOT和WV产品对比来看,该算法能较好地校正气溶胶与水汽对高光谱图像的影响,且反演过程中所有的输入均来自图像数据本身或6S辐射传输模型,无需输入额外的参数。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 6 S radiative transfer model in the inversion process.

关 键 词：气溶胶模式 气溶胶光学厚度(AOT) 水汽含量(WV) 高光谱 大气校正 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]