基于高光谱遥感影像的大气纠正:用AVIRIS数据评价大气纠正模块FLAASH

Atmospheric Correction of Hyper-spectral Imagery:Evaluation of the FLAASH Algorithm with AVRIS Data

高光谱遥感影像由于集中了高光谱分辨率和高空间分辨率的优点,在对地观测中具有不可替代的优势。实际应用当中,往往需要从遥感影像获取地物的地表反射率信息,这就要求首先从影像中去除大气的影响,即进行大气纠正及补偿。目前,对遥感影像进行大气纠正的算法有很多,详细介绍了基于遥感影像自身信息的大气纠正模块FLAA SH(Fast L ine of S ight A tm ospheric A nalysisof SpectralHypercubes)所涉及的算法,并利用该模块对AV IR IS航空遥感影像进行了大气纠正,对不同的结果进行了分析对比,从而对该算法进行了初步的评价。

With its combination of good spatial and spectral resolution, visible to near infrared spectral imaging from aircraft or spacecraft is a highly valuable technology for remote sensing of the earth＇s surface. In practice, it is desirable to eliminate atmospheric effects on the imagery, a process known as atmospheric correction or atmospheric compensation. At present, there are many atmospheric correction software packages for imagery atmospheric correction, such as ATREM （Atmospheric REMoval program）, ACORN （Atmospheric CORrection Now） and FLAASH （Fast Line of Sight Atmospheric Analysis of Spectral Hypercubes）. In this paper, the latest version of FLAASH atmosphere correction code derives its physics-based algorithm from the MODTRAN4 radiative transfer code was introduced, and some comparisons of with FLAASH-processed AVIRIS data, including results obtained using different processing options were showed. A preliminary evaluation to FLAASH algorithm was done in this paper and the result showed that the new automated spectral recalibration algorithm, which has been incorporated into FLAASH, is an extremely valuable addition. It improve the quality of the output reflectance cube for measured radiance data containing wavelength calibration errors and it also can be used as a tool to measure varying wavelength shifts in corss-track spatial dimension of an image, such are found in data from the AVIRIS sensor.