Radiometric calibration is a method that estimates the reflection of the target from the measured input radiation. The purpose of this study is to radiometrically calibrate three spectral bands of Sentinel-2A, including green, red and infrared. For this purpose, Landsat-8 OLI data are used. Because they have bands with the same wavelength range and they have the same structure. As a result, Landsat-8 OLI is appropriate for relative radiometric calibration.

    Design/methodology/approach

    The method used in this study is radiometric calibration uncorrected data from a sensor with corrected data from another sensor. Also, another aim of this study is a comparison between radiometric correction data and data that, in addition to radiometric correction, has been sharpened with panchromatic data. In this method, both of them have been used for radiometric calibration. Calibration coefficients have been obtained using the first-order polynomial equation.

    Findings

    This study showed that the corrected data has more valid answers than corrected and sharpened data. This method studied three land-cover types, including soil, water and vegetation, which it obtained the most accurate coefficients of calibration for soil class because R-square in all three bands was above 88%, and the root mean square error in all three bands was below 0.01. In the case of water and vegetation classes, only results of red and infrared bands were suitable.

    Originality/value

    For validating this method, the radiometric correction module of SNAP software was used. According to the results, the coefficient of radiometric calibration of the Landsat-8 sensor was very close to the coefficients obtained from the corrected data by SNAP.


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    Title :

    A fast radiometric correction method for Sentinel-2 satellite images


    Contributors:

    Published in:

    Publication date :

    2021-08-24


    Size :

    1 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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