星载光学载荷历史数据再定标综述

After more than thirty years of effort, China’s meteorological, land, ocean, and environmental disaster reduction constellations have formed a systematic and operational development trend. Domestically developed multi-series remote sensing satellites have accumulated long-term continuous observation data, which provide possibilities for climate change research and environmental change detection. To unleash the enormous potential of satellite observation historical data in climate change research, it is necessary to address the high-precision radiometric calibration problem of remote sensing payloads between different satellites and throughout the entire lifespan of a single satellite. This requires the establishment of a unified historical radiometric reference and a refined recalibration model, ensuring the comparability of observation data from different instruments and different time periods. This article provides an overview of the methods and approaches for historical data recalibration of spaceborne optical remote sensing instruments. It includes the development of radiometric reference models based on Earth-stable targets and celestial bodies such as the Moon, as well as the reconstruction of fine algorithm models for recalibrating long sequences of historical data. The paper systematically introduces how to construct radiometric reference models using Earth-stable targets such as deserts, ice and snow, DCC, as well as typical reference instruments and benchmark data evaluation for cross-calibration and benchmark traceability. This article also reviews several key aspects that need to be considered when reconstructing recalibration models for optical payload historical data. This includes the influence mechanisms of stray light, ghosting, polarization, and other factors affecting radiometric calibration uncertainty. It discusses the establishment of short-period fluctuation correction models and long-period decay models for instrument response through full-link simulation of instrument calibration, fine reconstruction of key calibration parameters, and the construction of fine calibration mechanism models related to spatial, spectral, thermal, and orbital elements. The article explores multi-objective tracking of instrument response, calculation of long sequence wide dynamic range calibration coefficients, and the application of computational intelligence for relative calibration techniques. This allows for automatic recalibration and long-period decay correction of satellite historical data, as well as the establishment of radiation response and decay characteristic models within the lifespan of a single instrument. By providing the latest research progress on historical radiometric references, recalibration models, and analysis of calibration mechanisms, this article offers a systematic approach to the recalibration of China’s historical remote sensing data. It lays the methodological foundation for further improving the long-term calibration quality and reliability of remote sensing data.