Science in China Series F: Information Sciences

, Volume 53, Issue 1, pp 168–181 | Cite as

Analysis of microwave brightness temperature of lunar surface and inversion of regolith layer thickness: Primary results of Chang-E 1 multi-channel radiometer observation

Research Papers

Abstract

In China’s first lunar exploration project, Chang-E 1 (CE-1), a multi-channel microwave radiometer was aboard the satellite, with the purpose of measuring microwave brightness temperature from lunar surface and surveying the global distribution of lunar regolith layer thickness. In this paper, the primary 621 tracks of swath data measured by Chang-E 1 microwave radiometer from November 2007 to February 2008 are collected and analyzed. Using nearest neighbor interpolation based on the sun incidence angle in observations, global distributions of microwave brightness temperature from lunar surface at lunar daytime and nighttime are constructed. Using the three-layer model (the top dust-soil, regolith and underlying rock media) for microwave thermal emission of lunar surface, the measurements of brightness temperature and dependence upon latitude, frequency and FeO+TiO2 content, etc. are discussed. On the basis of the ground measurements at Apollo landing sites, the observed brightness temperature at these locations are validated and calibrated by numerical three-layer modeling. Using the empirical dependence of physical temperature upon the latitude verified by the measurements at Apollo landing sites, the global distribution of regolith layer thickness is then inverted from the brightness temperature data of CE-1 at 3 GHz channel. Those inversions at Apollo landing sites are compared with the Apollo in situ measurements. Finally, the statistical property of regolith thickness distribution is analyzed and discussed.

Keywords

Chang-E 1 multi-channel brightness temperature Apollo landing site physical temperature inversion of regolith layer thickness 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    McKay D, Heiken G, Basu A, et al. The lunar regolith. In: Heiken G H, Vaniman D T, French B M, eds. Lunar Source-Book: A User’s Guide to the Moon. New York: Cambridge University Press, 1991. 285–356Google Scholar
  2. 2.
    Shkuratov Y G, Bondarenko N V. Regolith layer thickness mapping of the Moon by radar and optical data. Icarus, 2001, 149: 329–338CrossRefGoogle Scholar
  3. 3.
    Fa W, Jin Y Q. Simulation of brightness temperature from lunar surface and inversion of regolith layer thickness. J Geophys Res, 2007a, 112: E05003, doi: 10.1029/2006JE002751CrossRefGoogle Scholar
  4. 4.
    Fa W, Jin Y Q. Quantitative estimation of helium-3 spatial distribution in the lunar regolith layer. Icarus, 2007b, 190: 15–23CrossRefGoogle Scholar
  5. 5.
    Nakamura Y, Dorman J, Duennebier F, et al. Shallow lunar structure determined from the passive seismic experiment. Moon, 1975, 13: 3–15CrossRefGoogle Scholar
  6. 6.
    Strangway D, Pearce G, Olhoeft G. Magnetic and dielectric properties of lunar samples, In: Vinogradov A P, ed. Kosmochimiya Luny i Planet (in Russian). Nauka, Moscow, 1975. 712–728Google Scholar
  7. 7.
    Quaide W L, Oberbeck V R. Thickness determinations of the lunar surface layer from lunar impact craters. J Geophys Res, 1968, 73: 5247–5270CrossRefGoogle Scholar
  8. 8.
    Shoemaker E M, Baston R M, Holt H E, et al. Observations of the lunar regolith and the Earth from the television camera on Surveyor 7. J Geophys Res, 1969, 74: 6081–6119CrossRefGoogle Scholar
  9. 9.
    Jiang J S. Microwave Moon (in Chinese). Sci China Ser D-Earth Sci, 2009, 39: 1028Google Scholar
  10. 10.
    Jin Y Q, Yan F, Liang Z. Simulation of brightness temperature from the Lunar surface using multi-channels microwave radiometers. Chinese J Radio Sci, 18: 477–486Google Scholar
  11. 11.
    Keihm S J, Gary B L. Comparison of theoretical and observed λ3.55 cm wavelength brightness temperature maps of the full moon. Proc Lunar Sci Conf, 1979, 10: 2311–2319Google Scholar
  12. 12.
    Lucey P G, Blewett D T, Jolliff B L. Lunar iron and titanium abundance algorithms based on final processing of Clementine ultraviolet-visible images. J Geophys Res, 2000, 105: 20297–20305CrossRefGoogle Scholar
  13. 13.
    Zhang H, Zhang X, Yang J. The analysis of affections to the cold space calibration source of Chang-E 1 payload microwave detector. Adv Space Res, 2008, 42: 350–357CrossRefGoogle Scholar
  14. 14.
    Heiken G H, Vaniman D T, French B M. Lunar Source-Book: A User’s Guide to the Moon. New York: Cambridge University Press, 1991Google Scholar
  15. 15.
    Shkuratov Y G, Kaydash V G, Bondarenko N V. Iron and titanium abundance and maturity degree distribution on the lunar nearside. Icarus, 1999, 137: 235–246CrossRefGoogle Scholar
  16. 16.
    Hagfor T. Backscattering from an undulating surface with application to radar returns from the Moon. J Geophys Res, 1964, 97: 13319–13346Google Scholar
  17. 17.
    Lawrence D J, Feldman W C, Elphic R C, et al. Iron abundances on the lunar surface as measured by the Lunar prospector gamma-ray and neutron spectrometers. J Geophys Res, 2002, 107: 5130, doi: 10.1029/2001JE001530.CrossRefGoogle Scholar
  18. 18.
    Shkuratov Y G, Kaydash V G, Stankevich D G, et al. Derivation of elemental abundance maps at intermediate resolution from optical interpolation of lunar prospector gamma-ray spectrometer data. Planetary Space Sci, 2005, 53: 1287–1301CrossRefGoogle Scholar
  19. 19.
    Vasavada A R, Paige D A, Wood S E. Near-surface temperature on Mercury and the Moon and the stability of polar ice deposits. Icarus, 1999, 141: 179–193CrossRefGoogle Scholar
  20. 20.
    Lawson S L, Jakosky B M, Park H S, et al. Brightness temperatures of the lunar surface: Calibration and global analysis of the Clementine long-wave infrared camera data. J Geophys Res, 2000, 105: 4273–4290CrossRefGoogle Scholar

Copyright information

© Science in China Press and Springer Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Key Laboratory of Wave Scattering and Remote Sensing Information (MoE)Fudan UniversityShanghaiChina

Personalised recommendations