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@ARTICLE{Moghadas:11776,
      author       = {Moghadas, D. and André, F. and Slob, E.C. and Vereecken,
                      H. and Lambot, S.},
      title        = {{J}oint full-waveform analysis of off-ground zero-offset
                      ground penetrating radar and electromagnetic induction
                      synthetic data for estimating soil electrical properties},
      journal      = {Geophysical journal international},
      volume       = {182},
      issn         = {0956-540X},
      address      = {Oxford . Wiley-Blackwell},
      publisher    = {Wiley-Blackwell - STM},
      reportid     = {PreJuSER-11776},
      pages        = {1267 - 1278},
      year         = {2010},
      note         = {This research was supported by the Forschungszentrum Julich
                      (Germany), Universite catholique de Louvain and FNRS
                      (Belgium) in the framework of the DIGISOIL project, financed
                      by the European Commission under the 7th Framework Programme
                      for Research and Technological Development, Area
                      'Environment', Activity 6.3 'Environmental Technologies'.},
      abstract     = {A joint analysis of full-waveform information content in
                      ground penetrating radar (GPR) and electromagnetic induction
                      (EMI) synthetic data was investigated to reconstruct the
                      electrical properties of multilayered media. The GPR and EMI
                      systems operate in zero-offset, off-ground mode and are
                      designed using vector network analyser technology. The
                      inverse problem is formulated in the least-squares sense. We
                      compared four approaches for GPR and EMI data fusion. The
                      two first techniques consisted of defining a single
                      objective function, applying different weighting methods. As
                      a first approach, we weighted the EMI and GPR data using the
                      inverse of the data variance. The ideal point method was
                      also employed as a second weighting scenario. The third
                      approach is the naive Bayesian method and the fourth
                      technique corresponds to GPR–EMI and EMI–GPR sequential
                      inversions. Synthetic GPR and EMI data were generated for
                      the particular case of a two-layered medium. Analysis of the
                      objective function response surfaces from the two first
                      approaches demonstrated the benefit of combining the two
                      sources of information. However, due to the variations of
                      the GPR and EMI model sensitivities with respect to the
                      medium electrical properties, the formulation of an optimal
                      objective function based on the weighting methods is not
                      straightforward. While the Bayesian method relies on
                      assumptions with respect to the statistical distribution of
                      the parameters, it may constitute a relevant alternative for
                      GPR and EMI data fusion. Sequential inversions of different
                      configurations for a two layered medium show that in the
                      case of high conductivity or permittivity for the first
                      layer, the inversion scheme can not fully retrieve the soil
                      hydrogeophysical parameters. But in the case of low
                      permittivity and conductivity for the first layer, GPR–EMI
                      inversion provides proper estimation of values compared to
                      the EMI–GPR inversion.},
      cin          = {ICG-4 / JARA-ENERGY},
      ddc          = {550},
      cid          = {I:(DE-Juel1)VDB793 / $I:(DE-82)080011_20140620$},
      pnm          = {Terrestrische Umwelt},
      pid          = {G:(DE-Juel1)FUEK407},
      shelfmark    = {Geochemistry $\&$ Geophysics},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000280997700012},
      doi          = {10.1111/j.1365-246X.2010.04706.x},
      url          = {https://juser.fz-juelich.de/record/11776},
}