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@ARTICLE{Bandopadhyay:893418,
      author       = {Bandopadhyay, Subhajit and Rastogi, Anshu and Cogliati,
                      Sergio and Rascher, Uwe and Gąbka, Maciej and Juszczak,
                      Radosław},
      title        = {{C}an {V}egetation {I}ndices {S}erve as {P}roxies for
                      {P}otential {S}un-{I}nduced {F}luorescence ({SIF})? {A}
                      {F}uzzy {S}imulation {A}pproach on {A}irborne {I}maging
                      {S}pectroscopy {D}ata},
      journal      = {Remote sensing},
      volume       = {13},
      number       = {13},
      issn         = {2072-4292},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2021-02742},
      pages        = {2545 -},
      year         = {2021},
      abstract     = {In this study, we are testing a proxy for red and far-red
                      Sun-induced fluorescence (SIF) using an integrated fuzzy
                      logic modelling approach, termed as SIFfuzzy and
                      SIFfuzzy-APAR. The SIF emitted from the core of the
                      photosynthesis and observed at the top-of-canopy is
                      regulated by three major controlling factors: (1) light
                      interception and absorption by canopy plant cover; (2)
                      escape fraction of SIF photons (fesc); (3) light use
                      efficiency and non-photochemical quenching (NPQ) processes.
                      In our study, we proposed and validated a fuzzy logic
                      modelling approach that uses different combinations of
                      spectral vegetation indices (SVIs) reflecting such
                      controlling factors to approximate the potential SIF signals
                      at 760 nm and 687 nm. The HyPlant derived and field
                      validated SVIs (i.e., SR, NDVI, EVI, NDVIre, PRI) have been
                      processed through the membership transformation in the first
                      stage, and in the next stage the membership transformed maps
                      have been processed through the Fuzzy Gamma simulation to
                      calculate the SIFfuzzy. To test whether the inclusion of
                      absorbed photosynthetic active radiation (APAR) increases
                      the accuracy of the model, the SIFfuzzy was multiplied by
                      APAR (SIFfuzzy-APAR). The agreement between the modelled
                      SIFfuzzy and actual SIF airborne retrievals expressed by R2
                      ranged from 0.38 to 0.69 for SIF760 and from 0.85 to 0.92
                      for SIF687. The inclusion of APAR improved the R2 value
                      between SIFfuzzy-APAR and actual SIF. This study showed, for
                      the first time, that a diverse set of SVIs considered as
                      proxies of different vegetation traits, such as biochemical,
                      structural, and functional, can be successfully combined to
                      work as a first-order proxy of SIF. The previous studies
                      mainly included the far-red SIF whereas, in this study, we
                      have also focused on red SIF along with far-red SIF. The
                      analysis carried out at 1 m spatial resolution permits to
                      better infer SIF behaviour at an ecosystem-relevant scale},
      cin          = {IBG-2},
      ddc          = {620},
      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:000671000900001},
      doi          = {10.3390/rs13132545},
      url          = {https://juser.fz-juelich.de/record/893418},
}