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This study presents a novel approach to the radiometric inter-calibration between two sensors onboard the same satellite based on pseudo-invariant pixels (PIPs) using iteratively re-weighted multivariate alteration detection (IR-MAD) method. The IR-MAD algorithm can statistically select pseudo-invariant pixels from the multispectral image pair to assess the radiometric differences between them. Analysis of multiple image pairs from different acquisition times can provide long-term inter-calibration results of the two sensors. The procedure is applied to Fengyun(FY)-3A&#x0026;3B Visible Infrared Radiometer (VIRR), with the Medium Resolution Spectral Imager (MERSI) onboard the same platform as the reference. Consistency of the spatial distribution of the PIPs selected by IR-MAD with pseudo-invariant calibration sites (PICS) given by other scientists demonstrates the effectiveness of our method. The long-term time series trending of top-of-atmosphere VIRR reflectance over LIBYA1 and LIBYA4 after inter-calibration correction shows that the inter-calibrated VIRR has good agreement with MERSI, with a mean bias of less than 1% and an uncertainty of less than 2% for most channels. The approach requires no prior knowledge of the inter-calibration targets and extends PICS to the pixel-level targets, which results in more diverse samples, broader dynamic ranges and lower uncertainty, yielding consistent and reliable long-term inter-calibration results.

A novel inter-calibration method for Fengyun(FY)-3 VIRR using MERSI onboard the same satellite based on pseudo-invariant pixels