Izvestiya, Atmospheric and Oceanic Physics

, Volume 53, Issue 9, pp 991–995 | Cite as

Polarization Signature of Radar Backscattering Spatial Variations

  • A. V. Dmitriev
  • T. N. Chimitdorzhiev
  • P. N. Dagurov
Physical Bases and Methods of Studying the Earth from Space

Abstract

A new type of polarization signatures for the radar imaging of the Earth’s cover is proposed. These signatures allow determining the degree of spatial variations of the backscattering coefficient based on the fractal approach. The azimuthal dependence of the radar backscattering spatial variations is discovered when analyzing backscattering on a pine forest.

Keywords

radar imaging polarization signature fractal dimension spatial variations 

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References

  1. Bondur, V.G. and Chimitdorzhiev, T.N., Texture analysis of radar images of vegetation, Izv. Vyssh. Uchebn. Zaved., Geod. Aerofotos’emka, 2008a, no. 5, pp. 9–14.Google Scholar
  2. Bondur, V.G. and Chimitdorzhiev, T.N., Remote sensing of vegetation by optical–microwave methods, Izv. Vyssh. Uchebn. Zaved., Geod. Aerofotos’emka, 2008b, no. 6, pp. 64–73.Google Scholar
  3. Chimitdorzhiev, T.N., Arkhincheev, V.E., Dmitriev, A.V., and Tsydypov, B.Z., Fractal analysis of radar polarimetric data for the classification of Earth covers, Issled. Zemli Kosmosa, 2007a, no. 4, pp. 27–33.Google Scholar
  4. Chimitdorzhiev, T.N., Arkhincheev, V.E., and Dmitriev, A.V., Polarimetric estimate for spatial fluctuations of radar images for recovering the structure of forest canopy, Issled. Zemli Kosmosa, 2007b, no. 5, pp. 80–82.Google Scholar
  5. Cloude, S.R. and Pottier, E., A review of target decomposition theorems in radar polarimetry, IEEE Trans. Geosci. Remote Sens., 1996, vol. 34, no. 2, pp. 498–518. doi 10.1109/36.485127CrossRefGoogle Scholar
  6. Freeman, A. and Durden, S.L., A three-component model for polarimetric SAR imagery, IEEE Trans. Geosci. Remote Sens., 1998, vol. 36, no. 3, pp. 963–973. doi 10.1109/36.673687CrossRefGoogle Scholar
  7. Jafari, M., Maghsoudi, Y., and Zoej, M., A new method for land cover characterization and classification of polarimetric SAR data using polarimetric signatures, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 2015, no. 99, pp. 1–13. doi 10.1109/JSTARS.2014.2387374Google Scholar
  8. Myint, S.W., Fractal approaches in texture analysis and classification of remotely sensed data: Comparisons with spatial autocorrelation techniques and simple descriptive statistics, Int. J. Remote Sens., 2003, vol. 24, no. 9, pp. 1925–1947.CrossRefGoogle Scholar
  9. Neumann, M., Ferro-Famil, L., and Reigber, A., Estimation of forest structure, ground and canopy layer characteristics from multi-baseline polarimetric interferometric SAR data, IEEE Trans. Geosci. Remote Sens., 2010, vol. 48, no. 3, pp. 1086–1104. doi 10.1109/TGRS.2009.2031101Google Scholar
  10. Strzelczyk, J. and Porzycka-Strzelczyk, S., Identification of coherent scatterers in SAR images based on the analysis of polarimetric signatures, IEEE Geosci. Remote Sens. Lett., 2014, vol. 11, no. 4, pp. 783–787. doi 10.1109/LGRS.2013.2279005CrossRefGoogle Scholar
  11. Tustison, N. and Gee, J., Stochastic fractal dimension image. http://hdl.handle.net/1926/1525.Google Scholar
  12. Van Zyl, J.J., Zebker, H.A., and Elachi, C., Imaging radar polarization signatures: Theory and observation, Radio Sci., 1987, vol. 22, no. 4, pp. 529–543. doi 10.1029/RS022i004p00529CrossRefGoogle Scholar
  13. Yamaguchi, Y., Moriyama, T., Ishido, M., and Yamada, H., Four-component scattering model for polarimetric SAR image decomposition, IEEE Trans. Geosci. Remote Sens., 2005, vol. 43, no. 8, pp. 1699–1706. doi 10.1109/TGRS.2005.852084CrossRefGoogle Scholar
  14. Zakharova, L.N., Exploitation of interferometric coherence generated from fully polarimetric SAR data for the classification of Earth covers, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2008, no. 5, vol. 1, pp. 96–101.Google Scholar

Copyright information

© Pleiades Publishing, Ltd. 2017

Authors and Affiliations

  • A. V. Dmitriev
    • 1
  • T. N. Chimitdorzhiev
    • 1
  • P. N. Dagurov
    • 1
  1. 1.Institute of Physical Material Science, Siberian BranchRussian Academy of SciencesUlan-UdeRussia

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