% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{vonBueren:276576,
      author       = {von Bueren, S. K. and Burkart, A. and Hueni, A. and
                      Rascher, U. and Tuohy, M. P. and Yule, I. J.},
      title        = {{D}eploying four optical {UAV}-based sensors over
                      grassland: challenges and limitations},
      journal      = {Biogeosciences},
      volume       = {12},
      number       = {1},
      issn         = {1726-4189},
      address      = {Katlenburg-Lindau [u.a.]},
      publisher    = {Copernicus},
      reportid     = {FZJ-2015-06941},
      pages        = {163 - 175},
      year         = {2015},
      abstract     = {Unmanned aerial vehicles (UAVs) equipped with lightweight
                      spectral sensors facilitate non-destructive, near-real-time
                      vegetation analysis. In order to guarantee robust scientific
                      analysis, data acquisition protocols and processing
                      methodologies need to be developed and new sensors must be
                      compared with state-of-the-art instruments. Four different
                      types of optical UAV-based sensors (RGB camera, converted
                      near-infrared camera, six-band multispectral camera and high
                      spectral resolution spectrometer) were deployed and compared
                      in order to evaluate their applicability for vegetation
                      monitoring with a focus on precision agricultural
                      applications. Data were collected in New Zealand over
                      ryegrass pastures of various conditions and compared to
                      ground spectral measurements. The UAV STS spectrometer and
                      the multispectral camera MCA6 (Multiple Camera Array) were
                      found to deliver spectral data that can match the spectral
                      measurements of an ASD at ground level when compared over
                      all waypoints (UAV STS: R2=0.98; MCA6: R2=0.92). Variability
                      was highest in the near-infrared bands for both sensors
                      while the band multispectral camera also overestimated the
                      green peak reflectance. Reflectance factors derived from the
                      RGB (R2=0.63) and converted near-infrared (R2=0.65) cameras
                      resulted in lower accordance with reference measurements.
                      The UAV spectrometer system is capable of providing
                      narrow-band information for crop and pasture management. The
                      six-band multispectral camera has the potential to be
                      deployed to target specific broad wavebands if shortcomings
                      in radiometric limitations can be addressed. Large-scale
                      imaging of pasture variability can be achieved by either
                      using a true colour or a modified near-infrared camera. Data
                      quality from UAV-based sensors can only be assured, if field
                      protocols are followed and environmental conditions allow
                      for stable platform behaviour and illumination.},
      cin          = {IBG-2},
      ddc          = {570},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {582 - Plant Science (POF3-582)},
      pid          = {G:(DE-HGF)POF3-582},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000347960800010},
      doi          = {10.5194/bg-12-163-2015},
      url          = {https://juser.fz-juelich.de/record/276576},
}