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@PHDTHESIS{Tan:878387,
      author       = {Tan, Xihe},
      title        = {{D}evelopment of {E}lectromagnetic {I}nduction
                      {M}easurement and {I}nversion {M}ethods for {S}oil
                      {E}lectrical {C}onductivity {I}nvestigations},
      volume       = {62},
      school       = {RWTH Aachen},
      type         = {Dissertation},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2020-02823},
      isbn         = {978-3-95806-490-4},
      series       = {Schriften des Forschungszentrums Jülich. Reihe Information
                      / Information},
      pages        = {ix, 124 S.},
      year         = {2020},
      note         = {RWTH Aachen, Diss., 2020},
      abstract     = {Electromagnetic induction (EMI) is a promising contact-free
                      technique for non-invasive nearsurface geophysical
                      investigations. Frequency-domain rigid-boom EMI systems with
                      fixed distances between transmitter (Tx) and receivers (Rx)
                      have been increasingly used for characterizing the upper
                      meters (up to depths of approximately 1.5 times the maximum
                      coil separation) of the subsurface. Such EMI systems enable
                      the estimation of subsurface electrical conductivity
                      distributions by inverting the apparent electrical
                      conductivity (ECa) values measured from multiple different
                      Tx-Rx configurations. However, calibration issues due to the
                      thermal effects of the internal electronics as well as
                      external electromagnetic influences hinder a reliable
                      quantitative EMI data analysis. For a custom-made EMI
                      system, a transfer function analyzer (TFA) circuit is
                      developed to monitor thermal drift effects of the electrical
                      parameters of the receiver circuit. In addition, ambient
                      temperature sensors (ATS) were included into the setup.
                      Here, three correction methods were compared based on data
                      from ATS, TFA, and a combination of both TFA and ATS. The
                      presented work tested these three methods in three different
                      experimental studies where the transmitter unit temperature
                      is kept constant while the receiver unit is heated and
                      cooled (1) manually, (2) by cloudy ambient conditions and
                      (3) by partly sunny weather conditions. The results
                      demonstrate that the TFA in the receiver circuit provides
                      suitable data for correcting the phase drift originated
                      within the receiver coil but not for correcting the drift
                      caused by electrical components in the read-out circuit. The
                      latter drifts need to be corrected using ATS data.
                      Consequently, the combination of TFA and ATS data returned
                      the best correction results achieving a worst-case accuracy
                      of 2.3mS/m compared to 10.2mS/m (ATS-only) and 24.9mS/m
                      (TFA-only). The experimental results indicate that the drift
                      of the transmitter unit is not negligible and needs to be
                      corrected by a similar TFA circuit that should be
                      investigated in future studies. In addition to the thermal
                      effects, the external electromagnetic influences also shift
                      the measured ECa data which are caused by the presence of
                      the operator, cables or metallic objects included in the
                      field setup. The presented work introduces a novel
                      multi-elevation [...]},
      cin          = {ZEA-2},
      cid          = {I:(DE-Juel1)ZEA-2-20090406},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
      urn          = {urn:nbn:de:0001-2020102027},
      url          = {https://juser.fz-juelich.de/record/878387},
}