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@ARTICLE{Rodionov:823906,
      author       = {Rodionov, Andrei and Pätzold, Stefan and Welp, Gerhard and
                      Pude, Ralf and Amelung, Wulf},
      title        = {{P}roximal field {V}is-{NIR} spectroscopy of soil organic
                      carbon: {A} solution to clear obstacles related to
                      vegetation and straw cover},
      journal      = {Soil $\&$ tillage research},
      volume       = {163},
      issn         = {0167-1987},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2016-06538},
      pages        = {89 - 98},
      year         = {2016},
      abstract     = {The assessment of soil organic carbon (SOC) content using
                      proximal diffuse reflectance spectroscopy in the visible and
                      near-infrared (Vis-NIRS) may be hampered if green plants
                      (photosynthetic vegetation) and straw (non-photosynthetic
                      vegetation) are present in the measuring spot. Under such
                      conditions, taking spectra of the soil surface yields
                      insufficient results and requires quantitative correction.
                      In this combined lab and field study, we investigated if,
                      and to what degree, it is possible to distinguish green
                      plants and straw from bulk soil organic matter using the
                      same Vis-NIR spectra. Without any modification of an
                      approved SOC model, SOC was overestimated by more than
                      $200\%,$ depending on the fractional coverage with green
                      leaves and straw. This error was more severe for green
                      leaves than for straw. After covering the soil surface with
                      defined proportions of green barley leaves or straw
                      concomitant changes in reflectance spectra were recorded.
                      Partial least squares regression (PLSR) with three factors
                      yielded quantitative predictions of soil coverage by green
                      leaves (R2adj = 0.98, RMSEcv of cross-validation = $5.3\%$
                      soil coverage) and straw (R2adj = 0.95, RMSEcv = $7.5\%$
                      soil coverage). Furthermore, photosynthetic and
                      non-photosynthetic vegetation indices, the Normalized
                      Difference Vegetation Index (NDVI) and the Cellulose
                      Absorption Index (CAI), were derived from the Vis-NIR
                      spectra of the soil surface. Both indices increased when
                      covering with green leaves or straw increased (R2 = 0.99
                      [NDVI] and 0.94 [CAI], respectively). The degree of SOC
                      overestimation was correlated with NDVI and CAI.
                      Second-order polynomial regressions between SOC
                      overestimation, and CAI or NDVI were fitted (R2 = 0.97 and
                      0.99, respectively). This enabled us to carry out a
                      correction step after predicting SOC using an approved SOC
                      model (R2adj = 0.84, RPD = 2.53, RMSECV = 0.73) to minimize
                      the overestimation error. Transferring this
                      two-step-approach to field conditions revealed that Vis-NIR
                      spectra still showed scattered predictions of point-specific
                      SOC contents (R2 = 0.66 and 0.58 for stop-and-go and
                      on-the-go acquisitions, respectively), however, with a slope
                      close to unity. Consequently, the disturbance by green
                      plants or straw on the soil surface during superficial
                      Vis-NIR sensing of SOC in the field can be overcome.},
      cin          = {IBG-3},
      ddc          = {630},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000381834000011},
      doi          = {10.1016/j.still.2016.05.008},
      url          = {https://juser.fz-juelich.de/record/823906},
}