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On-orbit radiometric calibration and Validation of GF-7 satellite based on RadCalNet Baotou site

  • role： First author第一作者
  • Affiliation：

    Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China

  • Email：tanghz@pku.edu.cn
  • Introduction：唐洪钊，研究方向为遥感辐射定标。E-mail：tanghz@pku.edu.cn
TANG Hongzhao1,  
  • Affiliation：

    Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China

TANG Xinming1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China

  • Email：xiejf@lasac.cn
  • Introduction：谢俊峰，研究方向为卫星在轨检验与应用。E-mail：xiejf@lasac.cn
XIE Junfeng1*,  
  • Affiliation：

    China University of Mining and Technology (Beijing), Beijing 100083, China

CHEN Wei2,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

Qian Yonggang3

resumen

The aim of this study is to obtain a reliable, high-precision radiometric calibration coefficient for the GF-7 satellite sensor. In this study, we describe the methods and results of a reflectance-based vicarious calibration campaign that was conducted in September 2020 at RadCalNet Baotou Site located in Inner Mongolia, China. A series of gray-scale permanent artificial targets and infrastructure have been built in the Baotou site to provide effective support for the GF-7 satellite sensor’s on-orbit calibration. The reflectance-based vicarious calibration approach relies on the synchronous measurement of surface spectral reflectance and atmospheric parameters. In this campaign, synchronous measurements of surface and atmospheric conditions (including aerosol optical depth, amount of water vapor, and aerosol inversion products) at the Baotou site at the time of the GF-7 satellite’s overhead pass are obtained with an SVC HR-1024i spectroradiometer and a Cimel CE318 sun photometer. The bidirectional reflectance distribution function (BRDF) of the surface is measured with a multi-angle instrument with an SVC spectroradiometer. The synchronous measurement of surface spectral reflectance is modified by the surface BRDF model, and the atmospheric parameters are coupled with the exoatmospheric solar irradiance spectrum. The relative spectral response of the sensor is adopted as an input for a radiative transfer model to compute the at-sensor spectral radiance. The relationship between the at-sensor radiance and the digital number (DN) recorded in the GF-7 satellite image is identified. Results show a good linear relationship between DN and the apparent radiances of each band. The uncertainty of the GF-7 sensor radiometric calibration in the RadCalNet Baotou site is 4.33%, which is less than 5%. A detailed discussion of the validation analysis of the GF-7 radiometric calibration coefficient is performed using the products from the automated RadCalNet Baotou Sand site. This study can provide a site reference for the radiometric validation of Chinese satellites. In consideration of the results shown in this paper, the data from the RadCalNet Baotou site can be used as a reference to evaluate the radiometric performance of Chinese high-resolution satellites.

palabra clave

remote sensing;radiometric calibration;TOA radiance;reflectance-based approach;the Baotou site;GF-7 satellite

References

  1. 1.
    Biggar S F, Dinguirard M C, Gellman D I, Henry P J, Jackson R D, Moran M S and Slater P N. 1991. Radiometric calibration of SPOT 2 HRV: a comparison of three methods//Proceedings of SPIE 1493, Calibration of Passive Remote Observing Optical and Microwave Instrumentation. Orlando: SPIE: 155-162
  2. 2.
    Biggar S F, Slater P N and Gellman D I. 1994. Uncertainties in the in-flight calibration of sensors with reference to measured ground sites in the 0.4-1.1 μm range. Remote Sensing of Environment, 48(2): 245-252
  3. 3.
    BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML. 2008. JCGM 101:2008 Evaluation of measurement data - Supplement 1 to the “Guide to the expression of uncertainty in measurement” - Propagation of distributions using a Monte Carlo method. [s.l.]: JCGM
  4. 4.
    Bouvet M, Thome K, Berthelot B, Bialek A, Czapla-Myers J, Fox N P, Goryl P, Henry P, Ma L L, Marcq S, Meygret A, Wenny B N and Woolliams E R. 2019. RadCalNet: a radiometric calibration network for earth observing imagers operating in the visible to shortwave infrared spectral range. Remote Sensing, 11(20): 2401
  5. 5.
    Cao H Y, Liu F Q, Zhao C G and Dai J. 2021. The study of high resolution stereo mapping satellite. National Remote Sensing Bulletin, 25(7): 1400-1410
  6. 6.
    Dinguirard M and Slater P N. 1999. Calibration of space-multispectral imaging sensors: a review. Remote Sensing of Environment, 68(3): 194-205
  7. 7.
    Feingersh T, Dorigo W, Richter R and Ben-Dor E. 2005. A new model-driven correction factor for BRDF effects in HRS data//Proceedings of 4th EARSeL Workshop on Imaging Spectroscopy. Warsaw: EARSeL and Warsaw University
  8. 8.
    Gao H L, Gu X F, Yu T, Li X Y, Gong H and Li J G. 2010. The research overview on visible and near-infrared channels radiometric calibration of space-borne optical remote sensors. Remote Sensing Information, 25(4): 117-128
  9. 9.
    Han Q J, Ma L L, Liu L, Zhang X W, Fu Q Y, Pan Z Q and Wang A C. 2015. On-orbit calibration and evaluation of GF-2 satellite based on wide dynamic ground target. Acta Optica Sinica, 35(7): 0728003
  10. 10.
    Jing X, Leigh L, Teixeira Pinto C and Helder D. 2019. Evaluation of RadCalNet output data using Landsat 7, Landsat 8, sentinel 2A, and sentinel 2B sensors. Remote Sensing, 11(5): 541
  11. 11.
    Li C R, Ma L L, Gao C X, Tang L L, Wang N, Liu Y K, Zhao Y G, Dou S, Zhang D D and Li X H. 2015. Permanent target for optical payload performance and data quality assessment: spectral characterization and a case study for calibration. Journal of Applied Remote Sensing, 8(1): 083498
  12. 12.
    Li C R, Ma L L, Tang L L, Gao C X, Qian Y G, Wang N and Wang X H. 2021. A comprehensive calibration site for high resolution remote sensors dedicated to quantitative remote sensing and its applications. National Remote Sensing Bulletin, 25(1): 198-219
  13. 13.
    Liu Y K, Ma L L, Wang N, Qian Y G, Qiu S, Li C R and Tang L L. 2017. Vicarious radiometric calibration/validation of Landsat-8 operational land imager using a ground reflected radiance-based approach with Baotou site in China. Journal of Applied Remote Sensing, 11(4): 044004
  14. 14.
    Pang B, Ma L L, Liu Y K, Wang N, Zhao Y G, Han Q J, Meng F R, Li C R, Tang L L, Chen Z P and Wang G Z. 2019. Ground-based automatic radiometric calibration of land observation satellite optical sensors and cross validation analysis. Remote Sensing Technology and Application, 34(1): 146-154
  15. 15.
    Tang H Z, Xiao C C, Liang S N, Wei H Y and Gao H L. 2020. On-orbit radiometric calibration and validation of ZY-1-02D satellite. Spacecraft Engineering, 29(6): 142-147
  16. 16.
    Thome K J. 2001. Absolute radiometric calibration of Landsat 7 ETM+ using the reflectance-based method. Remote Sensing of Environment, 78(1/2): 27-38
  17. 17.
    Xu W W, Zhang L M, Yang B Y and Qiao Y L. 2012. On-orbit radiometric calibration based on gray-scale tarps. Acta Optica Sinica, 32(2): 0212007
  18. 18.
    Yeom J M, Hwang J, Jung J H, Lee K H and Lee C S. 2017. Initial radiometric characteristics of KOMPSAT-3A multispectral imagery using the 6S radiative transfer model, well-known radiometric tarps, and MFRSR measurements. Remote Sensing, 9(2): 130

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