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@ARTICLE{Burkart:830012,
      author       = {Burkart, Andreas and Hecht, Vera Lisa and Kraska, T. and
                      Rascher, Uwe},
      title        = {{P}henological analysis of unmanned aerial vehicle based
                      time series of barley imagery with high temporal resolution},
      journal      = {Precision agriculture},
      volume       = {19},
      number       = {1},
      issn         = {1385-2256},
      address      = {Dordrecht [u.a.]},
      publisher    = {Springer Science + Business Media B.V},
      reportid     = {FZJ-2017-03614},
      pages        = {134–146},
      year         = {2018},
      abstract     = {Emerging strategies and technologies in agriculture, such
                      as precision farming and phenotyping depend on detailed data
                      on all stages of crop development. Unmanned aerial vehicles
                      promise to deliver such time series as they allow very
                      frequent measurements. In this study, we analyse a field
                      trial with two barley cultivars and two contrasting sowing
                      densities in a random plot design over 2 consecutive years
                      using the aerial images of 28 flight campaigns, providing a
                      very high temporal resolution. From empirically corrected
                      RGB images, we calculated the green-red-vegetation-index
                      (GRVI) and evaluated the time-series for its potential to
                      track the seasonal development of the crop. The time series
                      shows a distinct pattern during crop development that
                      reflected the different developmental stages from
                      germination to harvest. The simultaneous comparison to
                      ground based assessment of phenological stages, allowed us
                      to relate features of the airborne time series to actual
                      events in plant growth and development. The measured GRVI
                      values range from −0.10 (bare soil) to 0.20 (fully
                      developed crop) and show a clear drop at time of ear pushing
                      and ripening. Lower sowing densities were identified by
                      smaller GRVI values during the vegetative growth phase.
                      Additionally, we could show that the time of corn filling
                      was strongly fixed and happened around 62 days after seeding
                      in both years and under both density treatments. This case
                      study provides a proof-of-concept evaluation how RGB data
                      can be utilized to provide quantitative data in crop
                      management and precision agriculture.},
      cin          = {IBG-2},
      ddc          = {630},
      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:000419944500008},
      doi          = {10.1007/s11119-017-9504-y},
      url          = {https://juser.fz-juelich.de/record/830012},
}