% 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{Krmer:902157,
      author       = {Krämer, Julie and Siegmann, Bastian and Kraska, Thorsten
                      and Muller, Onno and Rascher, Uwe},
      title        = {{T}he potential of spatial aggregation to extract remotely
                      sensed sun-induced fluorescence ({SIF}) of small-sized
                      experimental plots for applications in crop phenotyping},
      journal      = {International journal of applied earth observation and
                      geoinformation},
      volume       = {104},
      issn         = {0303-2434},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2021-04066},
      pages        = {102565 -},
      year         = {2021},
      abstract     = {Airborne measurements of sun-induced chlorophyll
                      fluorescence (SIF) are a promising tool for monitoring
                      plantfunctioning on different scales. However, currently
                      operational airborne imaging spectrometers for SIF
                      measurementsstill have limited spatial resolution and
                      pointing accuracy. This is challenging in terms of the
                      practicaluse of SIF maps for crop breeding and plant
                      phenotyping. We developed and tested two spatial
                      aggregationapproaches to make airborne SIF data usable in
                      experimental settings with a high number of small
                      experimentalplots. The two aggregation approaches generating
                      representative SIF values for experimental plots
                      demonstratedthe potential to be used in crop phenotyping.
                      The first aggregation approach (Approach A) aggregates
                      pixelvalues directly on SIF maps, whereas the second
                      approach (Approach B) aggregates at-sensor radiance before
                      SIFretrieval. The statistical analysis showed that
                      Approaches A and B led to significantly different SIF
                      products forsingle experimental plots (p < 0.001). To
                      evaluate the usability of the two approaches, aggregated SIF
                      productswere fitted against ground-based reference
                      measurements. We found that Approach B provided a better
                      representationof ground truth SIF760 (R2 = 0.61, p < 0.001)
                      than Approach A (R2 = 0.55, p < 0.001) when combinedwith
                      weighted averaging and robust outlier detection.
                      Furthermore, our results suggest that a slight decrease
                      inthe spatial resolution of the image data improves accuracy
                      of aggregation.},
      cin          = {IBG-2},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2173},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000711067500002},
      doi          = {10.1016/j.jag.2021.102565},
      url          = {https://juser.fz-juelich.de/record/902157},
}