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@ARTICLE{Chakhvashvili:906543,
      author       = {Chakhvashvili, Erekle and Siegmann, Bastian and Muller,
                      Onno and Verrelst, Jochem and Bendig, Juliane and Kraska,
                      Thorsten and Rascher, Uwe},
      title        = {{R}etrieval of {C}rop {V}ariables from {P}roximal
                      {M}ultispectral {UAV} {I}mage {D}ata {U}sing {PROSAIL} in
                      {M}aize {C}anopy},
      journal      = {Remote sensing},
      volume       = {14},
      number       = {5},
      issn         = {2072-4292},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2022-01507},
      pages        = {1247 -},
      year         = {2022},
      abstract     = {Mapping crop variables at different growth stages is
                      crucial to inform farmers and plant breeders about the crop
                      status. For mapping purposes, inversion of canopy radiative
                      transfer models (RTMs) is a viable alternative to parametric
                      and non-parametric regression models, which often lack
                      transferability in time and space. Due to the physical
                      nature of RTMs, inversion outputs can be delivered in sound
                      physical units that reflect the underlying processes in the
                      canopy. In this study, we explored the capabilities of the
                      coupled leaf–canopy RTM PROSAIL applied to high-spatial
                      resolution (0.015 m) multispectral unmanned aerial vehicle
                      (UAV) data to retrieve the leaf chlorophyll content (LCC),
                      leaf area index (LAI) and canopy chlorophyll content (CCC)
                      of sweet and silage maize throughout one growing season. Two
                      different retrieval methods were tested: (i) applying the
                      RTM inversion scheme to mean reflectance data derived from
                      single breeding plots (mean reflectance approach) and (ii)
                      applying the same inversion scheme to an orthomosaic to
                      separately retrieve the target variables for each pixel of
                      the breeding plots (pixel-based approach). For LCC
                      retrieval, soil and shaded pixels were removed by applying
                      simple vegetation index thresholding. Retrieval of LCC from
                      UAV data yielded promising results compared to ground
                      measurements (sweet maize RMSE = 4.92 μg/cm2, silage maize
                      RMSE = 3.74 μg/cm2) when using the mean reflectance
                      approach. LAI retrieval was more challenging due to the
                      blending of sunlit and shaded pixels present in the UAV
                      data, but worked well at the early developmental stages
                      (sweet maize RMSE = 0.70m2/m2, silage RMSE = 0.61m2/m2
                      across all dates). CCC retrieval significantly benefited
                      from the pixel-based approach compared to the mean
                      reflectance approach (RMSEs decreased from 45.6 to 33.1
                      μg/m2). We argue that high-resolution UAV imagery is well
                      suited for LCC retrieval, as shadows and background soil can
                      be precisely removed, leaving only green plant pixels for
                      the analysis. As for retrieving LAI,it proved to be
                      challenging for two distinct varieties of maize that were
                      characterized by contrasting canopy geometry.},
      cin          = {IBG-2},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {2171 - Biological and environmental resources for
                      sustainable use (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2171},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000773836200001},
      doi          = {10.3390/rs14051247},
      url          = {https://juser.fz-juelich.de/record/906543},
}