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Overview of historical data retrospective calibration for space-borne optical payloads

  • role： First author第一作者
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), 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方法，遥感反演科学算法和遥感大数据应用。E-mail：huxq@cma.gov.cn
HU Xiuqing123,  
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

WANG Ling123,  
  • role： Corresponding author通信作者
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

  • Email：zhangp@cma.gov.cn
  • Introduction：张鹏，研究方向为卫星大气遥感及应用、卫星遥感仪器定标、大气辐射传输理论与方法。E-mail：zhangp@cma.gov.cn
ZHANG Peng123*,  
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

XU Na123,  
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

QI Chengli123,  
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

XU Hanlie123,  
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

HE Xingwei123,  
  • Affiliation：

    Key Laboratory of Optoelectronic Imaging Technology and Systems, Ministry of Education, School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China

HE Yuqing4,  
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

CHEN Lin123,  
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

SUN Ling123,  
  • Affiliation：

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

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

    Innovation Center for FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

LU Naimeng123

Resümee

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.

Schlüsselwort

retrospective calibration;radiometric reference;fine recalibration model;calibration mechanism model;instrumental degradation model

References

  1. 1.
    Arai K. 2001. A reflectance based vicarious calibration with on-site instruments monitoring. Advances in Space Research, 28(1): 11-20
  2. 2.
    Bannari A, Omari K, Teillet P M and Fedosejevs G. 2005. Potential of Getis statistics to characterize the radiometric uniformity and stability of test sites used for the calibration of Earth observation sensors. IEEE Transactions on Geoscience and Remote Sensing, 43(12): 2918-2926
  3. 3.
    Bhatt R, Doelling D, Scarino B, Haney C and Gopalan A. 2017. Development of seasonal BRDF models to extend the use of deep convective clouds as invariant targets for satellite SWIR-band calibration. Remote Sensing, 9(10): 1061
  4. 4.
    Bojinski S, Verstraete M, Peterson T C, Richter C, Simmons A and Zemp M. 2014. The concept of essential climate variables in support of climate research, applications, and policy. Bulletin of the American Meteorological Society, 95(9): 1431-1443
  5. 5.
    Brest C L and Rossow W B. 1992. Radiometric calibration and monitoring of NOAA AVHRR data for ISCCP. International Journal of Remote Sensing, 13(2): 235-273
  6. 6.
    Cao C Y, Ma L L, Uprety S, Li C R and Tang L L. 2010. Spectral characterization of the Dunhuang calibration/validation site using hyperspectral measurements//Proceedings Volume 7862, Earth Observing Missions and Sensors: Development, Implementation, and Characterization. Incheon: SPIE: 137-146
  7. 7.
    Chander G, Xiong X, Choi T and Angal A. 2010. Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites. Remote Sensing of Environment, 114(4): 925-939
  8. 8.
    Chang, T. Xiong, X. 2011. Assessment of MODIS Thermal Emissive Band On-orbit Calibration. IEEE Trans. Geosci. Remote Sens., 49(6), 2415-2425.10.1109/TGRS.2010.2098881.
  9. 9.
    Chen L, Hu X Q, Xu N and Zhang P. 2013. The application of deep convective clouds in the calibration and response monitoring of the reflective solar bands of FY-3A/MERSI (Medium Resolution Spectral Imager). Remote Sensing, 5(12): 6958-6975
  10. 10.
    Chen L, Zhang P, Wu R H, Hu X Q and Zhang L. 2018. Monitoring radiometric response change of visible band for FY-2 geostationary meteorological satellite by lunar target. Journal of Remote Sensing, 22(2): 211-219
  11. 11.
    De Vries C, Danaher T, Denham R, Scarth P and Phinn S. 2007. An operational radiometric calibration procedure for the Landsat sensors based on pseudo-invariant target sites. Remote Sensing of Environment, 107(3): 414-429
  12. 12.
    Doelling D R, Morstad D, Scarino B R, Bhatt R and Gopalan A. 2013. The characterization of deep convective clouds as an invariant calibration target and as a visible calibration technique. IEEE Transactions on Geoscience and Remote Sensing, 51(3): 1147-1159
  13. 13.
    Eplee RE, Sun JQ, Meister G, et al., 2011. Cross calibration of SeaWiFS and MODIS using on-orbit observations of the Moon. Appl Opt, Jan 10;50(2):120-33. doi: . PMID: 21221136.
  14. 14.
    Fox N, Aiken J, Barnett J J, Briottet X, Carvell R, Frohlich C, Groom S B, Hagolle O, Haigh J D, Kieffer H H, Lean J, Pollock D B, Quinn T, Sandford M C W, Schaepman M, Shine K P, Schmutz W K, Teillet P M, Thome K J, Verstraete M M and Zalewski E. 2003. Traceable radiometry underpinning terrestrial- and Helio-studies (TRUTHS). Advances in Space Research, 32(11): 2253-2261
  15. 15.
    Fraser G T and Datla R V. 2006. Achieving satellite instrument calibration for climate change (ASIC3)//Proceedings of the National Conference Center. NIST
  16. 16.
    Goldberg M, Ohring G, Butler J, Cao C, Datla R, Doelling D, Gärtner V, Hewison T, Iacovazzi B, Kim D, Kurino T, Lafeuille J, Minnis P, Renaut D, Schmetz J, Tobin D, Wang L, Weng F, Wu X, Yu F, Zhang P and Zhu T. 2011. The global space-based inter-calibration system. Bulletin of the American Meteorological Society, 92(4): 467-475
  17. 17.
    Gu X F, Tian G L, Yu T, Li X Y, Gao H L and Xie Y. 2013. Principle and Method of Radiometric Calibration for Space Optical Remote Sensor. Beijing: Science Press
  18. 18.
    He X W, Hu X Q, He L L, Wang L, Tao B C, Hu W J and Feng X H. 2022. Surface reflectance spectral characteristic model of desert calibration site network in northwest China. Acta Optica Sinica, 42(6): 0628003
  19. 19.
    He Y Q, Hu W J, Hu X Q, Zhu J B, He X W and Jin W Q. 2023. Calibration site BRDF modeling method based on ground and low-altitude UAV joint observation. Acta Optica Sinica, 43(15): 1528001
  20. 20.
    He Y Q, Jiang M D, Hu X Q, Liu M Q, Jin W Q and Hu Q. 2022. Retrieval and analysis of MERSI polarization radiation characteristics based on ocean scene. Acta Optica Sinica, 42(6): 0628002
  21. 21.
    Heidinger A K, Foster M J, Walther A and Zhao X P. 2014. The pathfinder atmospheres-extended AVHRR climate dataset. Bulletin of the American Meteorological Society, 95(6): 909-922
  22. 22.
    Heidinger A K, Straka W C III, Molling C C, Sullivan J T and Wu X Q. 2010. Deriving an inter-sensor consistent calibration for the AVHRR solar reflectance data record. International Journal of Remote Sensing, 31(24): 6493-6517
  23. 23.
    Heidinger A K, Sullivan J T and Rao C R N. 2003. Calibration of visible and near-infrared channels of the NOAA-12 AVHRR using time series of observations over deserts. International Journal of Remote Sensing, 24(18): 3635-3649
  24. 24.
    Helder D L, Basnet B and Morstad D L. 2010. Optimized identification of worldwide radiometric pseudo-invariant calibration sites. Canadian Journal of Remote Sensing, 36(5): 527-539
  25. 25.
    Hollmann R, Merchant C J, Saunders R, Downy C, Buchwitz M, Cazenave A, Chuvieco E, Defourny P, De Leeuw G, Forsberg R, Holzer-Popp T, Paul F, Sandven S, Sathyendranath S, Van Roozendael M and Wagner W. 2013. The ESA Climate Change Initiative: satellite data records for essential climate variables. Bulletin of the American Meteorological Society, 94(10): 1541-1552
  26. 26.
    Hu X Q. 2012. Unified Radiometric Recalibration Study on Long-term Historical Data Record of Meteorological Satellite Sensors. Beijing: Institute of Remote Sensing Applications, Chinese Academy of Sciences
  27. 27.
    Hu X Q, Liu J J, Sun L, Rong Z G, Li Y, Zhang Y, Zheng Z J, Wu R H, Zhang L J and Gu X F. 2010. Characterization of CRCS Dunhuang test site and vicarious calibration utilization for Fengyun (FY) series sensors. Canadian Journal of Remote Sensing, 36(5): 566-582
  28. 28.
    Hu X Q, Wang L, Wang J W, He L L, Chen L, Xu N, Tao B C, Zhang L, Zhang P and Lu N M. 2020. Preliminary selection and characterization of pseudo-invariant calibration sites in Northwest China. Remote Sensing, 12(16): 2517
  29. 29.
    Hu Y B, Wielicki B A, Yang P, Stackhouse P W, Lin B and Young D F. 2004. Application of deep convective cloud albedo observation to satellite-based study of the terrestrial atmosphere: monitoring the stability of spaceborne measurements and assessing absorption anomaly. IEEE Transactions on Geoscience and Remote Sensing, 42(11): 2594-2599
  30. 30.
    Huang S S, Zeng Y, Chen W R and Yi W. 2021. Status and application of China’s civil land observation satellites. Satellite Applications, (10): 12-16
  31. 31.
    Jing Z H, Hu X Q, Wang Y, Wu R H, Chen L, Zhang L, Huang Y, Wang S, Li S and Zhang P. 2023. Activities to promote the moon as an absolute calibration reference. Remote Sensing, 15(9): 2431
  32. 32.
    Li G R, He Y Q, Hu X Q and Wang J W. 2023. Cross calibration technology for the same platform of FY-3 optical imager based on IR-MAD no-change pixels. National Remote Sensing Bulletin, 27(10): 2337-2349
  33. 33.
    Li X T, Ye Z Z, Ye Y M and Hu X Q. 2022. A convolutional neural network-based relative radiometric calibration method. IEEE Transactions on Geoscience and Remote Sensing, 60: 5403611
  34. 34.
    Lin M S, He X Q, Jia Y J, Bai Y, Ye X M and Gong F. 2019. Advances in marine satellite remote sensing technology in China.Acta Oceanologica Sinica, 41(10): 99-112
  35. 35.
    Loveless M, Knuteson R, Revercomb H, Borg L, DeSlover D, Martin G, Taylor J, Iturbide-Sanchez F and Tobin D. 2023. Comparison of the AIRS, IASI, and CrIS infrared sounders using simultaneous nadir overpasses: novel methods applied to data from 1 October 2019 to 1 October 2020. Earth and Space Science, 10(7): e2023EA002878
  36. 36.
    Lu N M, Ding L, Zheng X B, Ye X, Li C R, Lü D R, Zhang P, Hu X Q, Zhou C H, You Z, Fang J C, Gong J Y, Jiang X W, Li J J, Ma L L and Xu N. 2020. Introduction of the radiometric benchmark satellite being developed in China for remote sensing. Journal of Remote Sensing (Chinese), 24(6): 672-680
  37. 37.
    Ma L L, Wang N, Gao C X, Zhao Y G, Yang B Y, Wang X H, Han Q J, Xu N, Song P L and Liu Y K. 2023. On-orbit absolute radiometric calibration for optical remote sensing satellites: progress and trends. National Remote Sensing Bulletin, 27(5): 1061-1087
  38. 38.
    Masonis S J and Warren S G. 2001. Gain of the AVHRR visible channel as tracked using bidirectional reflectance of Antarctic and Greenland snow. International Journal of Remote Sensing, 22(8): 1495-1520
  39. 39.
    Miesch C, Cabot F, Briottet X, et al. 2003. Assimilation method to derive spectral ground reflectance of desert sites from satellite datasets[J]. Remote Sensing of Environment,87(2/3):359-370.
  40. 40.
    Molling C C, Heidinger A K, Straka W C III and Wu X Q. 2010. Calibrations for AVHRR channels 1 and 2: review and path towards consensus. International Journal of Remote Sensing, 31(24): 6519-6540
  41. 41.
    Ohring G, Tansock J, Emery W, Butler J, Flynn L, Weng F Z, St Germain K, Wielicki B, Cao C Y, Goldberg M, Xiong J, Fraser G, Kunkee D, Winker D, Miller L, Ungar S, Tobin D, Anderson J G, Pollock D, Shipley S, Thurgood A, Kopp G, Ardanuy P and Stone T. 2007. Achieving satellite instrument calibration for climate change. EoS, Transactions American Geophysical Union, 88(11): 136
  42. 42.
    Pagano T S, Aumann H H, Broberg S E, Cañas C, Manning E M, Overoye K O and Wilson R C. 2020. SI-traceability and measurement uncertainty of the atmospheric infrared sounder version 5 level 1B radiances. Remote Sensing, 12(8): 1338
  43. 43.
    Platnick S, Meyer K G, King M D, Wind G, Amarasinghe N, Marchant B, Arnold G T, Zhang Z B, Hubanks P A, Holz R E, Yang P, Ridgway W L and Riedi J. 2017. The MODIS cloud optical and microphysical products: collection 6 updates and examples from Terra and Aqua. IEEE Transactions on Geoscience and Remote Sensing, 55(1): 502-525
  44. 44.
    Popp T, Hegglin M I, Hollmann R, Ardhuin F, Bartsch A, Bastos A, Bennett V, Boutin J, Brockmann C, Buchwitz M, Chuvieco E, Ciais P, Dorigo W, Ghent D, Jones R, Lavergne T, Merchant C J, Meyssignac B, Paul F, Quegan S, Sathyendranath S, Scanlon T, Schröder M, Simis S G H and Willén U. 2020. Consistency of satellite climate data records for Earth system monitoring. Bulletin of the American Meteorological Society, 101(11): E1948-E1971
  45. 45.
    Smith D L, Mutlow C T and Rao C N. 2002. Calibration monitoring of the visible and near-infrared channels of the Along-Track Scanning Radiometer-2 by use of stable terrestrial sites. Applied Optics, 41(3): 515-523
  46. 46.
    Stone T C and Kieffer H H. 2004. Assessment of uncertainty in ROLO lunar irradiance for on-orbit calibration//Proceedings Volume 5542, Earth Observing Systems IX. Denver: SPIE: 300-310
  47. 47.
    Stone T C, Rossow W B, Ferrier J and Hinkelman L M. 2013. Evaluation of ISCCP multisatellite radiance calibration for geostationary imager visible channels using the moon. IEEE Transactions on Geoscience and Remote Sensing, 51(3): 1255-1266
  48. 48.
    Sun L, Hu X Q and Xu N. 2019. Temperature sensitivity and on-orbit calibration analysis for FY-3B MERSI shortwave infrared bands. Journal of Atmospheric and Environmental Optics, 14(5): 374-384
  49. 49.
    Sun L, Qiu H, Wu R H, Wang J, Zhang L Y and Zhang P. 2021. Long-term consistent recalibration of VIRR solar reflectance data record for Fengyun polar-orbiting satellites. Journal of Meteorological Research, 35(6): 926-942
  50. 50.
    Swanson R, Kehoe M, Stebbins M, Courrier H, Lukashin C, Jackson T, Cooney M, Davis W, Kopp G, Smith P, Buleri C, Stone T C. 2020. The ARCSTONE project to calibrate lunar reflectance//Proceedings of the 2020 IEEE Aerospace Conference. Big Sky: IEEE: 1-10
  51. 51.
    Tao B C, Hu X Q, Yang L K, Zhang L, Chen L, Xu N, Wang L, Wu R Q, Zhang D F and Zhang P. 2021. BRDF feature observation method and modeling of desert site based on UAV platform. National Remote Sensing Bulletin, 25(9): 1964-1977
  52. 52.
    Teillet P M, Barsi J A, Chander G and Thome K J. 2007. Prime candidate Earth targets for the post-launch radiometric calibration of space-based optical imaging instruments//Proceedings Volume 6677, Earth Observing Systems XII. San Diego: SPIE: 304-315
  53. 53.
    Walton C C, Sullivan J T, Rao C R N and Weinreb M P. 1998. Corrections for detector nonlinearities and calibration inconsistencies of the infrared channels of the advanced very high resolution radiometer. Journal of Geophysical Research: Oceans, 103(C2): 3323-3337
  54. 54.
    Wang J W, Hu X Q, He Y Q and Gao K. 2019. Response degradation analysis of Fengyun-3A medium-resolution spectral imager based on intelligent detection of invariant pixels. Acta Optica Sinica, 39(9): 0912001
  55. 55.
    Wang L, Hu X Q, Chen L and He L L. 2018. Consistent calibration of VIRR reflective solar channels onboard FY-3A, FY-3B, and FY-3C using a multisite calibration method. Remote Sensing, 10(9): 1336
  56. 56.
    Wang L, Hu X Q, Xu N, Chen L, Zhang P and Xu H L. 2023. Research on construction of directional reflectance reference model for desert stable earth targets. National Remote Sensing Bulletin, 27(10): 2270-2282
  57. 57.
    Wang L, Hu X Q, Zheng Z J and Chen L. 2018. Radiometric calibration tracking detection for FY-3A/MERSI by joint use of snow targets in south and north poles. Acta Optica Sinica, 38(2): 0212003
  58. 58.
    Wang W H, Cao C Y, Shao X, Blonski S, Choi T, Uprety S, Zhang B and Bai Y. 2022. Evaluation of 10-year NOAA/NASA Suomi NPP and NOAA-20 VIIRS Reflective Solar Band (RSB) Sensor Data Records (SDR) over deep convective clouds. Remote Sensing, 14(15): 3566
  59. 59.
    Wang Y, Hu X Q, Chen L, Huang Y, Li Z F, Wang S R, Zhang P, Wu R H, Zhang L and Wang W. 2020. Comparison of the lunar models using the hyper-spectral imager observations in Lijiang, China. Remote Sensing, 12(11): 1878
  60. 60.
    Wang Y, Huang Y, Wang S R, Li Z F, Zhang Z H, Hu X Q and Zhang P. 2017. Ground-based observation system development for the moon hyper-spectral imaging. Publications of the Astronomical Society of the Pacific, 129: 055002
  61. 61.
    Wielicki B A, Young D F, Mlynczak M G, Thome K J, Leroy S, Corliss J, Anderson J G, Ao C O, Bantges R, Best F, Bowman K, Brindley H, Butler J J, Collins W, Dykema J A, Doelling D R, Feldman D R, Fox N, Huang X, Holz R, Huang Y, Jin Z, Jennings D, Johnson D G, Jucks K, Kato S, Kirk-Davidoff D B, Knuteson R, Kopp G, Kratz D P, Liu X, Lukashin C, Mannucci A J, Phojanamongkolkij N, Pilewskie P, Ramaswamy V, Revercomb H, Rice J, Roberts Y, Roithmayr C M, Rose F, Sandford S, Shirley E L, Smith W L, Soden B, Speth P W, Sun W, Taylor P C, Tobin D and Xiong X. 2013. Achieving climate change absolute accuracy in orbit. Bulletin of the American Meteorological Society, 94(10): 1519-1539
  62. 62.
    Wilson T, Wu A S, Shrestha A, Geng X, Wang Z P, Moeller C, Frey R and Xiong X X. 2017. Development and implementation of an electronic crosstalk correction for bands 27-30 in terra MODIS collection 6. Remote Sensing, 9(6): 569
  63. 63.
    Wu A S, Xiong X X and Cao C Y. 2009. Using BRDF derived from MODIS observations over Dome C to characterize calibration stability and consistency of POS sensors//Proceedings Volume 7456, Atmospheric and Environmental Remote Sensing Data Processing and Utilization V: Readiness for GEOSS III. San Diego: SPIE: 37-48
  64. 64.
    Wu R H, Zhang P, Xu N, Hu X Q, Chen L, Zhang L and Yang Z D. 2020. FY-3D MERSI on-orbit radiometric calibration from the lunar view. Sensors, 20(17): 4690
  65. 65.
    Wu R H, Zhang P, Yang Z D, Hu X Q, Ding L and Chen L. 2016. Monitor radiance calibration of the remote sensing instrument with reflected lunar irradiance. Journal of Remote Sensing, 20(2): 278-289
  66. 66.
    Wu R H, Zhang P, Zheng X B, Hu X Q, Xu N, Zhang L and Qiao Y L. 2019. Data collection and irradiance conversion of lunar obsevation for MERSI. Optics and Precision Engineering, 27(8): 1819-1827
  67. 67.
    Xian D, Zhang P, Gao L, Sun R J, Zhang H Z and Jia X. 2021. Fengyun meteorological satellite products for earth system science applications. Advances in Atmospheric Sciences, 38(8): 1267-1284
  68. 68.
    Xiao D, Xu N, Hu X Q, Wu R H, Niu X H, Wang X H and He Y Q. 2020. On-orbit detection and correction of crosstalk effect of FY-3D MERSI-Ⅱ signals. Acta Optica Sinica, 40(10): 1011001
  69. 69.
    Xiong X, Che N, Pan C, Xie X, Sun J, Barnes W L and Guenther B. 2006. Results and lessons from MODIS reflective solar bands calibration: pre-launch to on-orbit//Proceedings Volume 6296, Earth Observing Systems XI. San Diego: SPIE: 52-62
  70. 70.
    Xiong X X and Barnes W. 2006. MODIS calibration and characterization//Qu J J, Gao W, Kafatos M, Murphy R E and Salomonson V V, eds. Earth Science Satellite Remote Sensing. Berlin: Springer: 77-97
  71. 71.
    Xu H L, Hu X Q, Xu N and Min M. 2015. Discrimination and correction for solar contamination on mid-infrared band of FY-3C/VIRR. Optics and Precision Engineering, 23(7): 1874-1879
  72. 72.
    Xu H L, Hu X Q, Xu N, Zhang L Y and Qi C L. 2023. Construction and validation of FY-3C/VIRR infrared window channel refinement re-calibration model. National Remote Sensing Bulletin, 27(10): 2307-2317
  73. 73.
    Xu N, Wu R H, Hu X Q, Chen L, Wang L and Sun L. 2015. Integrated method for on-obit wide dynamic vicarious calibration of FY-3C MERSI reflective solar bands. Acta Optica Sinica, 35(12): 1228001
  74. 74.
    Zhang B, Hu X Q, Zhou W W, Wang L, Chen L and Zhang P. 2023. Radiometric response evaluation of FY-3D/MERSI-Ⅱ reflective solar bands based on deep convective cloud. Acta Optica Sinica, 43(18): 1828003
  75. 75.
    Zhang L, Zhang P, Hu X Q, Chen L, Min M, Xu N and Wu R H. 2019a. Radiometric cross-calibration for multiple sensors with the moon as an intermediate reference. Journal of Meteorological Research, 33(5): 925-933
  76. 76.
    Zhang P, Lu N M, Li C R, Ding L, Zheng X B, Zhang X J, Hu X Q, Ye X, Ma L L, Xu N, Chen L and Schmetz J. 2020. Development of the Chinese space-based radiometric benchmark mission LIBRA. Remote Sensing, 12(14): 2179
  77. 77.
    Zhang P, Lu Q F, Hu X Q, Gu S Y, Yang L, Min M, Chen L, Xu N, Sun L, Bai W G, Ma G and Xian D. 2019b. Latest progress of the Chinese meteorological satellite program and core data processing technologies. Advances in Atmospheric Sciences, 36(9): 1027-1045
  78. 78.
    Zhang Y P, Hu X Q, Yin D K and Gu M J. 2020. Onboard polarization calibration technique of multi-angle polarization imager based on sun glint from ocean. Acta Optica Sinica, 40(15): 1528002
  79. 79.
    Zhao J Y, He Y Q, Hu X Q, Jin W Q, Zhang L J and Zhang D. 2021. Simulation of external stray light for FY-3C VIRR combined with satellite orbit attitude model. Remote Sensing, 13(24): 5037
  80. 80.
    Zhao Y H, Wang H, Li Y F, Li Y and Zhang X Q. 2021. Research on high-precision radiation calibration technology of long-wave infrared space optical remote sensor. National Remote Sensing Bulletin, 25(8): 1646-1654
  81. 81.
    Zhou W W, Hu X Q and Yang L K. 2023. Modeling of BRDF characteristics of deep convective cloud based on Himawari-8 satellite imager. Acta Optica Sinica, 43(12): 1228007
  82. 82.
    Zhu J B, Hu X Q, Yang L K, Xu H L, Xu N and Zhang P. 2021. Study on the correction of sunlight pollution in mid-infrared image of FY-3C/VIRR. National Remote Sensing Bulletin, 25(3): 803-815

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