Synchronous Atmospheric Correction of Wide-Swath and Wide-Field Remote Sensing Image from HJ-2A/B Satellite  
[PERSON]  
1 Key Laboratory of Optical Calibration and Characterization, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; [EMAIL_ADDRESS] (H.H. ); [EMAIL_ADDRESS] (Y.W. ); [EMAIL_ADDRESS] (R.T.); [EMAIL_ADDRESS] (X.S. ); [EMAIL_ADDRESS] (Z.L. ); [EMAIL_ADDRESS] (C.L. );
2 Science Island Branch of Graduate School, University of Science and Technology of China, Hefei 230026, China 2  
[PERSON]  
1 Key Laboratory of Optical Calibration and Characterization, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; [EMAIL_ADDRESS] (H.H. ); [EMAIL_ADDRESS] (Y.W. ); [EMAIL_ADDRESS] (R.T.); [EMAIL_ADDRESS] (X.S. ); [EMAIL_ADDRESS] (Z.L. ); [EMAIL_ADDRESS] (C.L. );  
[PERSON]  
1 Key Laboratory of Optical Calibration and Characterization, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; [EMAIL_ADDRESS] (H.H. ); [EMAIL_ADDRESS] (Y.W. ); [EMAIL_ADDRESS] (R.T.); [EMAIL_ADDRESS] (X.  
the absence of ground spectral data or synchronous atmospheric measurements. However, this approach typically has limited accuracy. Currently, most optical satellites employ radiative transfer model-based methods to generate surface reflectance products [3; 4; 5]. Radiative transfer model-based atmospheric correction methods require synchronously acquired atmospheric parameters as inputs [6; 7; 8]. The Earth's atmospheric composition varies spatially and temporally, particularly for parameters such as water vapor and aerosols. To achieve high correction accuracy, fixed atmospheric models or distribution parameters are insufficient. Instead, synchronous atmospheric parameters for the target region must be acquired [9; 10; 11]. Radiative transfer model-based methods can be broadly categorized based on how atmospheric parameters are acquired. One such approach employs spectral bands specifically designed for atmospheric parameter retrieval, as demonstrated in the MODIS and Sentinel series. These bands typically have lower spatial resolutions and narrower bandwidths; they retrieve atmospheric parameters that are then used to correct higher-resolution bands [12; 13; 14]. The other approach involves equipping satellites with instruments for real-time atmospheric parameter acquisition. For instance, the Earth Observing-1 (EO-1) satellite features the Linear Etalon Imaging Spectrometer Array Atmospheric Corrector (LAC), while the WorldView-3 satellite includes the Clouds, Aerosols, Vapor, Ice, and Snow (CAVIS) instrument for cloud and aerosol detection. Similarly, China's Gao Fen Duo Mo satellite is equipped with the Synchronous Monitoring Atmospheric Corrector (SMAC) [15]. The HuanjingJianzai-2 (HJ-2) A/B satellites incorporate a Polarized Scanning Atmospheric Corrector (PSAC) [16]. Among these instruments, the SMAC and PSAC incorporate polarization observations, which can effectively enhance aerosol retrieval accuracy, particularly over highly reflective surfaces, thereby improving atmospheric correction precision. Therefore, this approach has become a key trend in the development of high-spatial-resolution atmospheric correction in recent years. The HuanjingJianzai satellite series focuses on disaster prevention, mitigation, and environmental protection while also addressing needs in land resources, agriculture, forestry, and seismology. Beyond acquiring clear imagery, these satellites aim to produce high-precision quantitative products such as surface albedo, vegetation indices, water body indices, snow cover indices, soil moisture, land cover change, and water quality indicators. These products are vital for disaster assessment, recovery, and resource monitoring, with their quality directly dependent on the accuracy of surface reflectance derived from atmospheric correction.