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机构地区:[1]西南林业大学环境科学与工程系,云南昆明650224 [2]西南林业大学国有资产管理处,云南昆明650224 [3]西南林业大学资源学院,云南昆明650224
出 处:《浙江农林大学学报》2011年第4期590-596,共7页Journal of Zhejiang A&F University
基 金:国家林业局重点学科资助项目(XKZ200904);国家林业局林业公益性行业科研专项(200904045);云南省教育厅科学研究基金资助项目(2010Y300);西南林业大学重点基金资助项目(200503Z;200702Z)
摘 要:FLAASH(fast line-of-sight atmospheric analysis of spectral hypercubes)大气校正模块被越来越多地应用到遥感图像大气校正中,但是ENVI(the environment for visualizing images)中没有预先设定有新谱传感器的参数,因此限制了FLAASH模块的使用范围。采用FLAASH模块对ENVI中没有预设的高级陆地成像仪传感器所拍摄的图像进行大气校正,初步探讨了FLAASH模块对未知多光谱传感器图像的大气校正。通过比较大气校正前后典型地物的光谱曲线和归一化植被指数(NDVI,normalized difference vegetation index),表明FLAASH模块能够有效地减少大气对ALI图像的影响。The fast line-of-sight atmospheric analysis of spectral hypercubes(FLAASH) atmospheric correction module has often been used to correct the atmospheric influence of remote sensing images,however,in the Environment for Visualizing Images(ENVI),there is no pre-defined parameter for a new sensor in ENVI,which limits the range of application for a FLAASH module.To discuss atmospheric correction for an unknown multispectral sensor using the FLAASH module,an atmospheric correction process of images from the Advanced Land Imager(ALI) sensor was introduced.According to contrast and analysis uncorrected and corrected reflectance spectrum for water,vegetation and wasteland,the corrected reflectance spectrum was restored;according to qualitative and quantitative analysis of the whole image of corrected and uncorrected normalized differential vegetation index(NDVI),vegetation region was more brightness;non-vegetation region was darker;the peak value of histogram was improved from 0.454 to 0.754;the mean value was improved from 0.417 to 0.694;the standard deviation was improved from 0.139 7 to 0.141 0.Results showed that by using the FLAASH module,the atmospheric influence of ALI image was effectively weakened.The FLAASH module can be used to correct the atmospheric influence of new sensor,which is no pre-defined in the ENVI.
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