Fadila Muchsin, Kuncoro Adi Pradono, Indah Prasasti, Dianovita Dianovita, Kurnia Ulfa, Kiki Winda Veronica, Dandy Aditya Novresiandi, Andi Ibrahim


Landsat-8 and Sentinel-2 satellite imageries are widely used for various remote sensing applications because they are easy to access and free to download. A precise atmospheric correction is necessary to be applied to the optical satellite imageries so that the derived information becomes more accurate and reliable. In this study, the performance of atmospheric correction algorithms (i.e., 6S, FLAASH, DOS, LaSRC, and Sen2Cor) was evaluated by comparing the object's spectral response, vegetation index, and classification accuracy in the paddy field area before and after the implementation of atmospheric correction. Overall, the results show that each algorithm has varying accuracy. Nevertheless, all atmospheric correction algorithms can improve the classification accuracy, whereby those derived by the 6S and FLAASH yielded the highest accuracy.


atmospheric correction, Landsat-8, Sentinel-2, classification accuracy

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