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Cross calibration technology for the same platform of FY-3 optical imager based on IR-MAD no-change pixels

  • role： First author第一作者
  • Affiliation：

    Beijing Institute of Technology, School Optics and Photonics, Key Laboratory of Optoelectronic Imaging Technology and System of Ministry of Education, Beijing 100081, China

  • Email：lgr_BIT@163.com
  • Introduction：李国荣，研究方向为光学传感器辐射定标。E-mail：lgr_BIT@163.com
LI Guorong1,  
  • Affiliation：

    Beijing Institute of Technology, School Optics and Photonics, Key Laboratory of Optoelectronic Imaging Technology and System of Ministry of Education, Beijing 100081, China

HE Yuqing1,  
  • role： Corresponding author通信作者
  • Affiliation：

    National Stellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

  • Email：huxq@cma.gov.cn
  • Introduction：胡秀清，研究方向为卫星遥感器定标理论及技术方法、遥感反演科学算法。E-mail：huxq@cma.gov.cn
HU Xiuqing2*,  
  • Affiliation：

    National Stellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China

WANG Junwei2

resumen

During the operation of the satellite in orbit, the radiation detection performance and stability of the sensor changes, and the accuracy of the acquired radiation observation signal decreases. Accurate on-orbit calibration of sensors is crucial to ensure the validity of their data products. The stable target site based cross calibration method is limited by the pseudo-invariant target, which is manually selected by the satellite synchronous transit and has simple spectral characteristics. Thus, multi-frequency and high-precision cross calibration are difficult to carry out.MethodThis study proposes a cross calibration method based on iterative reweighted multivariate alteration detection (IR-MAD). Taking the FY-3B medium resolution spectral imager (MERSI) as the reference, the cross-calibration of visible and infrared radiometer (VIRR) on the same platform is studied. Initially, the IR-MAD algorithm linearly combines the simultaneous multi-channel images of the two sensors to construct canonical correlation variables and performs canonical correlation analysis to eliminate the correlation between different channels of a single sensor and unmatched channels of different sensors. Then, through multiple probability reweighting iterations, the IR-MAD algorithm can automatically identify the no-change pixels (NCPs) in the same phase scene of the two sensors. The radiance of the NCPs has the largest linear correlation between VIRR and MERSI matching channels. The cross-calibration coefficients can be obtained using a linear regression model based on the apparent reflectance information of the NCPs by correcting the spectral differences between matched channels of two sensors. This study implements this procedure with data from Northwest China region and North Africa region and compares it with the calibration results obtained from other related studies.ResultExperimental results show that the proposed method is consistent with the operational calibration and the Dunhuang desert site calibration. The relative deviation of the radiometric information between VIRR and MERSI after calibration exceeds 2%. The cross-calibration results of IR-MAD obtained in northwest China and north Africa are consistent (most channels are better than 2%), verifying the generalization and stability of this method. The long-time sequence results show a correlation between the channel response decay trend and wavelength. In general, the shorter wavelength indicates a more serious decay. In addition, some seasonal fluctuations are found in the relative calibration slope time series of near-infrared and shortwave infrared channels.ConclusionThis method can automatically and efficiently select pseudo-invariant targets in satellite observation scenes and realize high precision cross calibration based on the selected pseudo-invariant targets. It is applicable to the re-calibration of historical satellite data and the relative response monitoring of sensors on the same platform. Our future work will focus on the application of algorithms in different platforms and nonlinear problems.

palabra clave

visible and infra-red radiometer (VIRR);medium resolution spectral imager (MERSI);IR-MAD;no-change pixels;cross calibration

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