Onboard calibrator devices are among the most reliable methods for post-launch satellite radiometric calibration. Some Earth observation satellites are equipped with multiple onboard calibrators—such as reference lamps and solar diffusers—to enhance radiometric accuracy and provide redundant systems. While multiple devices may improve overall performance, they also introduce challenges in maintaining consistent calibration curves and integrating data from different sources. To address these challenges, the Combined Radiometric Model (CRAM) algorithm was developed, establishing a foundational framework for systematically integrating data from multiple onboard calibration devices into a unified calibration strategy. By combining information from these multiple sources, CRAM produces a unified estimate of radiometric gain. The primary goal of this paper is to document the fundamental concepts behind the CRAM algorithm. The paper provides a comprehensive overview of the CRAM algorithm, detailing its methodology and highlighting its practical applications in satellite calibration workflows, particularly for Landsat-8 and Landsat-9 mission. Results demonstrate that CRAM consistently delivers accurate calibration outputs over time, significantly reducing the variability caused by multiple calibrator sources and ensuring reliable long-term radiometric performance. Specifically, the unified calibration gain curve exhibited a maximum combined error of less than 0.8% across all spectral bands for both Landsat-8 and Landsat-9 missions. The methodology remains adaptable and open to future refinement as new calibration technologies and statistical techniques emerge. • CRAM algorithm integrates multiple onboard calibrators • Addresses time-dependent variations and harmonizes onboard calibrator outputs • Operationally implemented in Landsat-8/9 radiometric calibration workflows • Methodology applicable across Earth observation satellite
Pinto et al. (Sun,) studied this question.