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@ARTICLE{Yang:1045821,
      author       = {Yang, Peiqi and Liu, Zhigang and Han, Dalei and Zhang,
                      Runfei and Siegmann, Bastian and Liu, Jing and Zhao, Huarong
                      and Rascher, Uwe and Chen, Jing M. and van der Tol,
                      Christiaan},
      title        = {{M}itigating the black-soil problem in the
                      reflectance-to-fluorescence ({R}2{F}) relationship: {A}
                      soil-adjusted reflectance-based approach for downscaling
                      {SIF}},
      journal      = {Remote sensing of environment},
      volume       = {330},
      issn         = {0034-4257},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2025-03620},
      pages        = {114998 -},
      year         = {2025},
      note         = {Bitte Post-print ergänzen},
      abstract     = {Solar-induced chlorophyll fluorescence (SIF) is an
                      effective probe for photosynthesis, but this remote
                      sensingsignal is affected by multiple factors, including
                      radiation intensity, canopy structure, sun-observer
                      geometry, andleaf physiological status. The complex
                      interplay among these factors causes substantial
                      discrepancies among topof-canopy (TOC) SIF, leaf-level
                      average SIF and actual photosynthetic activity. Downscaling
                      TOC SIF to the leafleveland decoupling structural and
                      physiological information remain major challenges in the use
                      of SIF signalsfor remote sensing of photosynthesis. To
                      address these challenges, the R2F
                      (reflectance-to-fluorescence) theorywas developed, grounded
                      in the similarity in radiative transfer processes governing
                      SIF and reflectance. Thistheory establishes a physical
                      relationship between near-infrared reflectance (Rnir) and
                      the far-red SIF scatteringcoefficient (σF). On this basis,
                      SIF signals can be scaled from the canopy to the leaf level
                      by normalizing σF,estimated from reflectance as σF =
                      Rnir/i0, where i0 denotes canopy interceptance. However, the
                      original R2Fformulation assumes a non-reflective soil. This
                      simplification breaks down in sparse canopies, where soil
                      contributionsare non-negligible—an issue referred to as
                      the “black-soil problem”. Soil enhances both Rnir and
                      σF,distorting their intrinsic relationship. In this study,
                      we show that soil effects manifest through two
                      mainmechanisms: (1) direct soil reflection, which
                      significantly increases Rnir but has minimal impact on σF,
                      and (2)soil–vegetation multiple scattering, which affects
                      both Rnir and σF but tends to have compensatory
                      effects.Consequently, the dominant source of bias in the
                      original R2F relationship is direct soil reflection that
                      contributesto Rnir—a mechanism that had not been
                      explicitly isolated in previous studies. This finding allows
                      us tonarrow down the “black-soil problem” in the R2F
                      framework to the specific impact of soil single scattering
                      onRnir. To mitigate this bias, we propose a soil-adjusted
                      R2F (saR2F) method, which estimates the direct
                      soilcontribution of Rnir using TOC red and blue reflectance.
                      Correcting Rnir for the direct soil reflection results in
                      arobust relationship between σF and soil-adjusted Rnir
                      (saRnir), notably σF = saRnir/i0.We evaluated the saR2F
                      relationship using one field and two simulated datasets. In
                      the field study, saR2Fimproved the estimation of σF from
                      TOC reflectance, with R2 increasing ranging from 0.21 to
                      0.31 compared to the original R2F. In the two simulations,
                      saR2F consistently outperformed the original R2F, especially
                      under sparse canopy conditions. We also compared saR2F with
                      NDVI-based (NIRv) and FCVI-based R2F approaches. In the
                      available field observations collected under specific
                      conditions (i.e., varying viewing azimuth angles), the three
                      approaches showed similar performance and were better than
                      the original R2F in explaining the viewing- angle dependence
                      of σF. However, across the broader range of simulated
                      scenarios and for estimating the exact σF, saR2F
                      demonstrated better stability than NIRv and FCVI-based R2F
                      methods. The NIRv-based and FCVI-based R2F methods yielded
                      relatively low RMSE (0.092 and 0.075, respectively) but weak
                      explanatory power, with R2 values below 0.41 for canopies
                      with LAI <3. In contrast, saR2F achieved a much stronger
                      relationship (R2 =0.80) and a low RMSE of 0.044.
                      Furthermore, compared to the NIRv or FCVI-based approaches
                      for R2F corrections, saR2F offers a more physically
                      plausible and interpretable solution that can be applied to
                      angular correction and total SIF estimation. The effective
                      mitigation of the black-soil problem facilitates
                      interpretation of raw SIF observations and enhances the
                      monitoring of photosynthetic activity using SIF.},
      cin          = {IBG-2},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {1121 - Digitalization and Systems Technology for
                      Flexibility Solutions (POF4-112) / 2171 - Biological and
                      environmental resources for sustainable use (POF4-217)},
      pid          = {G:(DE-HGF)POF4-1121 / G:(DE-HGF)POF4-2171},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001566835400001},
      doi          = {10.1016/j.rse.2025.114998},
      url          = {https://juser.fz-juelich.de/record/1045821},
}