% 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{DeGrave:891684,
      author       = {De Grave, Charlotte and Pipia, Luca and Siegmann, Bastian
                      and Morcillo-Pallarés, Pablo and Rivera-Caicedo, Juan Pablo
                      and Moreno, José and Verrelst, Jochem},
      title        = {{R}etrieving and {V}alidating {L}eaf and {C}anopy
                      {C}hlorophyll {C}ontent at {M}oderate {R}esolution: {A}
                      {M}ultiscale {A}nalysis with the {S}entinel-3 {OLCI}
                      {S}ensor},
      journal      = {Remote sensing},
      volume       = {13},
      number       = {8},
      issn         = {2072-4292},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2021-01667},
      pages        = {1419 -},
      year         = {2021},
      abstract     = {ESA’s Eighth Earth Explorer mission “FLuorescence
                      EXplorer” (FLEX) will be dedicated to the global
                      monitoring of the chlorophyll fluorescence emitted by
                      vegetation. In order to properly interpret the measured
                      fluorescence signal, essential vegetation variables need to
                      be retrieved concomitantly. FLEX will fly in tandem
                      formation with Sentinel-3 (S3), which conveys the Ocean and
                      Land Color Instrument (OLCI) that is designed to
                      characterize the atmosphere and the terrestrial vegetation
                      at a spatial resolution of 300 m. In support of FLEX’s
                      preparatory activities, this paper presents a first
                      validation exercise of OLCI vegetation products against in
                      situ data coming from the 2018 FLEXSense campaign. During
                      this campaign, leaf chlorophyll content (LCC) and leaf area
                      index (LAI) measurements were collected over croplands,
                      while HyPlant DUAL images of the area were acquired at a 3 m
                      spatial resolution. A multiscale validation strategy was
                      pursued. First, estimates of these two variables, together
                      with the combined canopy chlorophyll content (CCC = LCC ×
                      LAI), were obtained at the HyPlant spatial resolution and
                      were compared against the in situ measurements. Second, the
                      fine-scale retrieval maps from HyPlant were coarsened to the
                      S3 spatial scale as a reference to assess the quality of the
                      OLCI vegetation products. As an intermediary step,
                      vegetation products extracted from Sentinel-2 data were used
                      to compare retrievals at the in-between spatial resolution
                      of 20 m. For all spatial scales, CCC delivered the most
                      accurate estimates with the smallest prediction error
                      obtained at the 300 m resolution (R2 of 0.74 and RMSE = 26.8
                      μg cm−2). Results of a scaling analysis suggest that CCC
                      performs well at the different tested spatial resolutions
                      since it presents a linear behavior across scales. LCC, on
                      the other hand, was poorly retrieved at the 300 m scale,
                      showing overestimated values over heterogeneous pixels. The
                      introduction of a new LCC model integrating mixed
                      reflectance spectra in its training enabled to improve by
                      $16\%$ the retrieval accuracy for this variable (RMSE = 10
                      μg cm−2 for the new model versus RMSE = 11.9 μg cm−2
                      for the former model).},
      cin          = {IBG-2},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {217 - Für eine nachhaltige Bio-Ökonomie – von
                      Ressourcen zu Produkten (POF4-217)},
      pid          = {G:(DE-HGF)POF4-217},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000644673700001},
      doi          = {10.3390/rs13081419},
      url          = {https://juser.fz-juelich.de/record/891684},
}