Précédent|Prochain

Radiation performance simulation and analysis of the signal-to-noise ratio for GF-4 geostationary satellite: In the case of the coastal water in Hong Kong

  • role： First author第一作者
  • Affiliation：

    International Institute for Earth System Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

  • Email：mg1527104@smail.nju.edu.cn
  • Introduction：朱小波，1992年生，男，硕士研究生，研究方向为高光谱遥感。E-mail：mg1527104@smail.nju.edu.cn
Xiaobo ZHU12,  
  • role： Corresponding author通信作者
  • Affiliation：

    International Institute for Earth System Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

  • Email：tianqj@nju.edu.cn
  • Introduction：田庆久，1964年生，男，教授，研究方向为高光谱遥感和遥感信息定量化。E-mail：tianqj@nju.edu.cn
Qingjiu TIAN12*,  
  • Affiliation：

    International Institute for Earth System Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

Kaijian XU12,  
  • Affiliation：

    College of Resource and Environment, Linyi University, Linyi 276000, China

Chunguang LYU3,  
  • Affiliation：

    National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China

Ling WANG4

résumé

With the launch and preliminary application of the GF-4 geostationary satellite, the advantages of having both high spatial and temporal resolution enable it to have its own feature in the same type of satellites, and China has attached more importance to the research on geostationary satellite images. To evaluate the on-orbit detection capability of GF-4, thorough assessment is essential to grasp the available time of the image data on the same day and reasonably arrange the boot time to improve satellite use efficiency and prolong its life span. This objective can be accomplished by realistic radiation simulation of the imagery data and signal-to-noise ratio (SNR) study with typical objects represented by dark pixels (such as water). Based on the given spectral capabilities, geometrical, and atmospheric parameters, and in combination with land surface properties (Hong Kong coastal water), the GF-4 sensor hyperspectral remote sensing in standard atmospheric conditions, including Pan wave band and blue, green, red, and NIR-four wave bands, are simulated using the radiative transmission model MODTRAN. On this basis, the interference of atmospheric path radiance is removed to calculate the effective SNR. The data of four typical time nodes in spring equinox, summer solstice, autumn equinox, and winter solstice are selected for analysis. In this way, realistically simulated hyperspectral top-of-atmosphere apparent radiance, ground effective radiance, and path radiance are obtained. The information helps identify the effective time for the satellite to obtain high-quality water images in the observation of the same day, especially analyzing the sensitivity of the critical weak signal during the dawn–dusk period. This work fills the gaps in the data quality assessment and has a positive significance to the scientific and rational use of GF-4. Results show that the highest apparent radiance values of summer solstice and winter solstice are successive at 59.26 and 56.20 W/(m2·sr·μm), respectively, all in the blue band; and the highest ground effective radiance values of summer solstice and winter solstice are 17.52 and 12.13 W/(m2·sr·μm), respectively, also in the blue band. The highest effective SNR values of the summer solstice and winter solstice are 41.0 and 38.2 dB, respectively. The simulation results of blue band are the worst, but those of NIR, green, and Pan bands are good. To ensure the image quality, the water effective SNR of 35 dB is set as a threshold value to determine the boot time. The time of image acquisition is 7:49–17:01 in summer solstice and 9:28–15:07 in winter solstice.

mots-clés

GF-4;MODTRAN;radiance;effective SNR;path radiance;Hong Kong coastal water

References

  1. 1.
    Abreu L W and Anderson G P. 1996. The MODTRAN 2/3 Report and LOWTRAN 7 Model. Contract F19628-91-C.0132. Hanscom AFB, MA: Phillips Laboratory
  2. 2.
    Chen Y H, Zhou J K, Chen X H, Zhou W and Shen W M. 2009. Calculation of SNR of a satellite CCD camera based on MODTRAN. Infrared and Laser Engineering, 38(5): 910–914 (
  3. 3.
    Gordon H R, Brown J W, Brown O B, Evans R H and Smith R C. 1988. A semianalytic radiance model of ocean color. Journal of Geophysical Research: Atmospheres, 93(D9): 10909–10924
  4. 4.
    Kirk J T O. 1994. Light and Photosynthesis in Aquatic Ecosystems. Cambridge: Cambridge University Press
  5. 5.
    Liu Z Z, Chen B Y, Chan S T, Cao Y C, Gao Y, Zhang K F and Nichol J. 2015. Analysis and modelling of water vapour and temperature changes in Hong Kong using a 40‐year radiosonde record: 1973—2012. International Journal of Climatology, 35(3): 462–474
  6. 6.
    Lodhi M A and Rundquist D C. 2001. A spectral analysis of bottom-induced variation in the colour of Sand Hills lakes, Nebraska, USA. International Journal of Remote Sensing, 22(9): 1665–1682
  7. 7.
    Lü C G, Wang W H, Yang W B, Tian Q J, Lu S and Chen Y. 2015. Radiance simulation of BUV hyperspectral sensor on multi angle observation, and improvement to initial total ozone estimating model of TOMS V8 total ozone algorithm. Spectroscopy and Spectral Analysis, 35(11): 2979–2984 (
  8. 8.
    Lyu C G, Tian J, Yang W B, Tian Q J, Lin Y H, Liu Z M and Zhang H M. 2016. Solar-blind ultraviolet upwelling radiance diurnal variation led by observation geometry factors on geostationary attitude sensor limb viewing. Terrestrial, Atmospheric and Oceanic Sciences Journal, 27(6): 943–953
  9. 9.
    McClatchey R A, Bolle H J and Kondratyev K Y 1984. A Preliminary Cloudless Standard Atmosphere for Radiation Computation. WCP-112. Boulder, Colorado, USA: World Climate Program
  10. 10.
    Otterman J and Fraser R S. 1979. Adjacency effects on imaging by surface reflection and atmospheric scattering: cross radiance to zenith. Applied Optics, 18(16): 2852–2860
  11. 11.
    Qiu R, Wu J, Yang C P, Wang X D and Liu M. 2006. Solar radiation transfer in clear atmosphere at 0.45~0.95 μm. Journal of Atmospheric and Environmental Optics, 1(1): 21–26 (
  12. 12.
    Song P F, Wang S T and Wang X Y. 2009. Impact of atmospheric radiance on efficient imaging signal-to-noise ratio in twilight environment. Spacecraft Recovery and Remote Sensing, 30(2): 30–36 (
  13. 13.
    Sutherland R A, Montoya J R and Thompson J C. 2002. Atmospheric effects on visible and infrared scene clutter characerization. Proceedings of SPIE 4718, Targets and Backgrounds VIII: Characterization and Representation. Bellingham, WA: SPIE: 235–245
  14. 14.
    Verhoef W and Bach H. 2003. Simulation of hyperspectral and directional radiance images using coupled biophysical and atmospheric radiative transfer models. Remote Sensing of Environment, 87(1): 23–41
  15. 15.
    Wan Z, Ren J W, Li X S, Zhao G J and Ren J Y. 2008. Analysis of signal-to-noise ratio for remote sensing TDI CCD camera based on radiative transfer model. Infrared and Laser Engineering, 37(3): 497–500, 555 (
  16. 16.
    Wang J T and Yang J Y. 2008. Adaptive object tracking based on SNR maximizing. Journal of Image and Graphics, 13(1): 89–94 (
  17. 17.
    Wang N, Yang J Z, Chen S B, Zhou G Q, Yu Y F and Xiang T T. 2015. Simulation to channel on-board spectra of ASTER based on MODTRAN. Earth Science——Journal of China University of Geosciences, 40(8): 1427–1431 (
  18. 18.
    Wu B Y, Li W and Chen H B. 1998. Practical Algorithm for Atmospheric Radiation Transmission. Beijing: China Meteorological Press.
  19. 19.
    Xu X Z, Li Z T and Xue L J. 2004. Analysis and processing of CCD noise. Infrared and Laser Engineering, 33(4): 343–346, 357 (
  20. 20.
    Yang B X. 2005. Study on the SNR of TDICCD camera. Spacecraft Recovery and Remote Sensing, 26(2): 22–24 (
  21. 21.
    Yang G J, Liu Q H, Liu Q, Xiao Q, Gu X F and Huang W J. 2009. Mid-infrared atmosphere radiation transfer analytic model and remote sensing images simulation. Spectroscopy and Spectral Analysis, 29(3): 629–633 (
  22. 22.
    Yang M H, Zhao Y C, Liu T J, Zhang B, Zhao C J and Tong Q X. 2003. Study on a method to repair low-ratio S/N band of imaging spectrometer data based on the trend-face of DN value. Journal of Image and Graphics, 8(11): 1299–1303 (
  23. 23.
    Zhang H, Yuan J H and Liu E H. 2006. CCD noise effects on position accuracy of star sensor. Infrared and Laser Engineering, 35(5): 629–633, 642 (

Lire l'article complet

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website