Cross-calibration Method of Hyperspectral Remote Sensing Sensor Based on Radiation Invariant Points
In addressing the radiometric calibration issue in remote sensing image data processing,the key lies in accurately obtaining radiometric calibration coefficients to ensure a precise correla-tion between image digital number values and terrestrial radiative values.The article introduces EMIT L1B data and building upon previous experiences and methods from spectral imaging in-struments,proposes a cross-calibration method for hyperspectral remote sensing sensors.This method,utilizing multi-satellite data and automated processes,acquires calibration coefficients for hyperspectral satellites and enhances the accuracy and efficiency of invariant point selection for ra-diometric calibration.Utilizing the intersection points of data collected by EMIT and the ZY-1-02D satellite,accurate calibration coefficients were derived through regression analysis at ra-diometrically invariant points.Simultaneously,Sentinel-2 data are introduced for selecting radio-metric invariant points,employing an automated program to compare the similarity between two spectra.This approach further enhances the efficiency and reliability of point selection.The cali-bration results are evaluated using standard errors and correlation coefficients to assess errors and correlations between bands.The maximum standard error is found to be below 0.008,with 145 band correlation coefficients exceeding 0.90.This demonstrates that the cross-calibration method can yield high-quality reflectance spectral curves,underscoring its importance in improving the ac-curacy and usability of image data.
cross-calibrationZY-1-02 D satelliteEMIThyperspectral
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