Evaluation of imaging spectroscopy and atmospheric correction of multispectral images (Aster and LandsaT 7 ETM+)

After Landsat satellite launched in 1972, multispectral satellite images (Landsat TM/ETM+, Aster, ALI, Spot, Ikonos, Quickbird etc.) were used in many disciplines such as geology, environment, hydrogeology and ore deposits, etc. For several decades, imaging spectroscopy or hypespektral images are used with an increasing importance in many applications and various disciplines of geology. Imaging Spectroscopy is one of the new and fast growing technologies in remote sensing. One of the goals of this study is the atmospheric correction of Advanced Spaceborne Thermal Emission and Reflection Radiometer (Aster) and Landsat 7 ETM+ images using different methods and to evaluate the effect to results of imaging spectroscopy applications of these calibrations. Another objective is more quantitatively to map the hydrothermal alteration minerals using imaging spectroscopy or spectral mapping tools methods with multispectral images (Aster and Landsat 7 ETM+). Imaging spectroscopy or spectral mapping methods are methods usually used to produce information hyperspektral images. In this study, unlike, imaging spectroscopy or spectral mapping methods were applied to multispectral imaging to map the hydrothermal alteration minerals. A lot of different methods are used in order to remove the atmospheric effect from satellite image and to convert from DN values to reflectance data. There are mainly two general approaches for atmospheric corrections of satellite images. One of this is the relative (Image-based empirical or statical) approach such as Flat Field, IAR Reflectance, Log Residual and Emperical Line. The other is the absolute (Radiative Transfer Modeling) approach such as Flaash, Atcor, Acorn. In this study, Flaash (Fast-sight Atmospheric Analysis of Spectral Hypercubes Lineof), Atcor (Atmospheric and Topographic Correction), Log Residual and IAR Reflectance (Internal Average Relative Reflectance) was used as calibration tools for atmospheric corrections. Calibrated Aster and - - Landsat 7 ETM + images (converted from DN value to reflectance) are used in imaging spectroscopy or spectral mapping to map the kaolinite, illite and goethite minerals. In this study, Spectral Angle Mapper (SAM), the Spectral Feature Fitting (SFF), Matched Filtering (MF), and Mixture Tuned Matched Filtering (MTMF) were used as the spectral mapping tools. Results of the four methods were evaluated separately for each mineral and multispectral image. The results of image analysis were controlled by field studies. As results of the image analysis and evaluations, the absolute atmospheric corrections (Flaash and Atcor) of Aster and Landsat 7 ETM + images have been achieved more than the relative methods of atmospheric corrections. Particularly, the kaolinite, illite and goethite minerals were succefully mapped by the spectral mapping of calibrated Aster and Landsat 7 ETM+ images by using Flaash and Atcor methods.