Assessment of the image-based atmospheric correction of multispectral satellite images for geological mapping in arid and semi-arid regions

This paper aims to assess the image-based and physical atmospheric corrections of Landsat 8 images for geological mapping. This study was carried out in the central Jebilet inlier in Moroccan anti atlas, which is characterized by its geological diversity, its mining potential and an arid climate. Two physical atmospheric corrections FLAASH (Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes) and ATCOR (Atmospheric & Topographic Correction) were compared to the DOS1 (Dark Object Subtraction) image-based method. The assessment of the results was based on the ASD (Analytical Spectral Devices) spectroradiometric data as well as the SVM (Support Vector Machine) classifications issued from the atmospherically corrected images. The FLAASH provided the most accurate Bottom Of Atmosphere BOA reflectance estimation (R-2 = 0.95 and RMSE = 0.033) and slightly outperformed the DOS1 method (R-2 = 0.94 and RMSE = 0.034). For the SVM classification outputs, DOS1 gave results almost similar to those obtained by FLAASH and ATCOR. The similarity between the FLAASH and DOS1 SVM classifications was 97.77%. The results of this work demonstrate the effectiveness of the image-based method in atmospheric correction of multispectral data for geological and mineral mapping over the arid and semi-arid regions. The image-based atmospheric correction method is proved as an accurate, simple way and very straightforward to apply.