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@INPROCEEDINGS{Krieger:872665,
      author       = {Krieger, Vera and Matveeva, Maria and Rascher, Uwe},
      collaboration = {Cogliati and Damm, Alexander},
      othercontributors = {Rademske, Patrick},
      title        = {{S}ystematic {A}ssessment {O}f {A}irborne {S}un-{I}nduced
                      {F}luorescence {M}aps {B}y {T}he {A}pplication {O}f
                      {Q}uality {C}riteria},
      school       = {Rheinische Friedrich-Wilhelms-Universität Bonn},
      reportid     = {FZJ-2020-00156},
      year         = {2019},
      abstract     = {When plants absorb light, not all energy is converted by
                      photosynthesis, but excess energy is released as heat or
                      emitted as sun-induced chlorophyll fluorescence (F). This
                      signal, related to the photosynthetic efficiency of plants,
                      has been intensively studied and measured from ground,
                      airborne and satellite. However, retrieving sun-induced
                      fluorescence (F) from remote sensing data is challenging
                      because accurate modeling of atmospheric influences is
                      required.. The advent of the airborne imaging spectrometer
                      HyPlant made possible to produce F maps in high-spatial
                      resolution (1-3 meters), which is a valuable tool to better
                      understand F at relevant ecosystem scale. Currently, two
                      different algorithms are used routinely to retrieve red and
                      far-red F from HyPlant. Both methods are based on the O 2
                      absorption bands, but while iFLD method employs a
                      semi-empirical atmospheric correction (i.e., bare-soils),
                      the SFM makes use of a physically-based atmospheric modeling
                      (MODTRAN5 code). A common method of testing the reliability
                      of a remotely sensed F product (in this study airborne F
                      maps) is the comparison with “ground truth” data where
                      the atmosphere can be neglected. In this work we tested
                      another possibility of assessing the quality of the airborne
                      F maps, which does not require ground reference
                      measurements. For this purpose we have developed so-called
                      ’quality criteria’, which should help to find errors and
                      artefacts that have arisen during F retrieval. This method
                      was used to test the quality of the airborne F maps of 2016
                      campaign. By applying the quality criteria, clear
                      differences in the performance of two retrievals were found.
                      Although it was shown that both retrievals performed well in
                      F 760 retrieval, even at places with changes from vegetated
                      to non-vegetated sites on pixel scale, iFLD was more robust
                      for retrieving correct absolute values for F 760 and F 687 ,
                      while SFM performed less accurate in this term, over- and
                      underestimating F values. Furthermore, previously reported
                      problems with image pre-processing (deconvolution for
                      correcting PSF) of SFM became clear here. This was causing
                      strong artefacts in F 687 retrievals from SFM. However, SFM
                      proved to be the more suitable method for identifying small
                      differences on pixel scale. Moreover, this algorithm did not
                      show systematic variations over entire flight lines as
                      observed by the use of iFLD. The physically-based approach
                      of atmospheric correction used with SFM thus provided more
                      interference-free F maps than the semi-empirical correction
                      using non-fluorescent surfaces as in iFLD retrieval. Testing
                      F retrievals on vegetation under different illumination
                      conditions showed the necessity to calculate F yield for
                      quantification of photosynthesis rates. The application of
                      the proposed quality features proved to be a valuable tool
                      for assessing the performance of F retrieval on airborne
                      maps. Therefore we propose to use the quality criteria even
                      when sufficient ground references are available, because
                      even if the quality criteria do not replace ground-truth
                      data, they provide important additional information about
                      the quality of the F product of the respective retrieval
                      method.},
      month         = {Feb},
      date          = {2019-02-06},
      organization  = {EARSel SIG Imaging Spectroscopy
                       Workshop, Brno (Czech), 6 Feb 2019 - 8
                       Feb 2019},
      subtyp        = {Other},
      cin          = {IBG-2},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {582 - Plant Science (POF3-582)},
      pid          = {G:(DE-HGF)POF3-582},
      typ          = {PUB:(DE-HGF)6},
      url          = {https://juser.fz-juelich.de/record/872665},
}