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@ARTICLE{vonHebel:866110,
      author       = {von Hebel, Christian and van der Kruk, Jan and Huisman,
                      Johan Alexander and Mester, Achim and Altdorff, Daniel and
                      Endres, Anthony L. and Zimmermann, Egon and Garre, Sarah and
                      Vereecken, Harry},
      title        = {{C}alibration, {C}onversion, and {Q}uantitative
                      {M}ulti-{L}ayer {I}nversion of {M}ulti-{C}oil {R}igid-{B}oom
                      {E}lectromagnetic {I}nduction {D}ata},
      journal      = {Sensors},
      volume       = {19},
      number       = {21},
      issn         = {1424-8220},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2019-05329},
      pages        = {4753},
      year         = {2019},
      abstract     = {Multi-coil electromagnetic induction (EMI) systems induce
                      magnetic fields below and above the subsurface. The
                      resulting magnetic field is measured at multiple coils
                      increasingly separated from the transmitter in a rigid boom.
                      This field relates to the subsurface apparent electrical
                      conductivity (σa), and σa represents an average value for
                      the depth range investigated with a specific coil separation
                      and orientation. Multi-coil EMI data can be inverted to
                      obtain layered bulk electrical conductivity models. However,
                      above-ground stationary influences alter the signal and the
                      inversion results can be unreliable. This study proposes an
                      improved data processing chain, including EMI data
                      calibration, conversion, and inversion. For the calibration
                      of σa, three direct current resistivity techniques are
                      compared: Electrical resistivity tomography with
                      Dipole-Dipole and Schlumberger electrode arrays and vertical
                      electrical soundings. All three methods obtained robust
                      calibration results. The Dipole-Dipole-based calibration
                      proved stable upon testing on different soil types. To
                      further improve accuracy, we propose a non-linear exact EMI
                      conversion to convert the magnetic field to σa. The
                      complete processing workflow provides accurate and
                      quantitative EMI data and the inversions reliable estimates
                      of the intrinsic electrical conductivities. This improves
                      the ability to combine EMI with, e.g., remote sensing, and
                      the use of EMI for monitoring purposes.},
      cin          = {IBG-3 / JARA-HPC},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IBG-3-20101118 / $I:(DE-82)080012_20140620$},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255) / Better predictions with environmental
                      simulation models: optimally integrating new data sources
                      $(jicg41_20100501)$},
      pid          = {G:(DE-HGF)POF3-255 / $G:(DE-Juel1)jicg41_20100501$},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31683890},
      UT           = {WOS:000498834000150},
      doi          = {10.3390/s19214753},
      url          = {https://juser.fz-juelich.de/record/866110},
}