A Refined Radiometric Cross-Calibration of HJ-2B/IRS Over Plateau Lakes Using the Double-Difference Method

The infrared scanner (IRS) onboard the HJ-2B satellite is a high-resolution, dual-channel thermal infrared sensor suitable for applications such as land-surface temperature retrieval and smoke detection. Radiometric calibration is a fundamental prerequisite for ensuring the quality and reliability of IRS observation data and is typically performed via two-point (high- and low-temperature) calibration using the instrument’s onboard blackbody. However, the effectiveness of this procedure can be constrained by performance degradation of the calibration hardware and by its frequency of usage. In response to these limitations, this article proposes a refined radiometric cross-calibration method for the HJ-2B/IRS sensor over plateau lakes, which adopts the double-difference method as the technical basis and uses the high-accuracy Terra/MODIS as the reference sensor. Implemented through rigorous screening of calibration sites and sampling points, the method explicitly accounts for viewing geometry, as well as contemporaneous surface and atmospheric conditions. First, calibration points between IRS and MODIS are screened by setting a CV threshold and using the RANSAC algorithm. Next, given the surface and atmospheric conditions at the satellite overpass time, radiances at calibration points with large viewing zenith angles were corrected to their nadir-equivalent values, and a temperature-dependent simulated brightness temperature difference function is constructed, from which the fitted calibration coefficients (FCCs) are derived using the double-difference method. Finally, validation with Landsat-8/TIRS indicates that IRS brightness temperatures calculated by the FCCs deviate less from the TIRS observations than those computed with the official calibration coefficients (OCCs) issued by the China Centre for Resources Satellite Data and Application. Furthermore, when compared with the top-of-atmosphere brightness temperatures derived from forward modeling of in situ measurement data, the IRS at-aperture brightness temperature computed using the FCCs shows mean deviations of −1.04 K and −0.92 K for Band 8 and Band 9, respectively. These values are superior to the corresponding deviations of −1.32 K and −2.43 K obtained using the OCCs. Following a quantitative analysis of various factors influencing the FCCs, the total uncertainty for IRS Band 8 and Band 9 was determined to be below 0.937% and 1.257%, respectively.