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001040884 1001_ $$0P:(DE-HGF)0$$aLu, Wendi$$b0
001040884 245__ $$aCharacterizing leaf-scale fluorescence with spectral invariants
001040884 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2025
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001040884 520__ $$aSun-induced chlorophyll fluorescence (SIF) is increasingly recognized as a non-destructive probe for tracking terrestrial photosynthesis. Emerging developments in spectral invariants theory provide an innovative and efficient approach for representing SIF radiative transfer processes at the canopy scale. However, modeling leaf-scale fluorescence based on the spectral invariants properties (SIP) remains underexplored. In this study, the spectral invariants theory is employed for the first time to model the leaf-scale total, backward and forward fluorescence (leaf-SIP SIF). The leaf-SIP SIF model separates the leaf-scale radiative transfer process into two distinct components: the wavelength-dependent one associated with leaf biochemical properties, and the wavelength-independent component linked to leaf structural characteristics. The leaf structure-related effects are characterized by two spectrally invariant parameters: the photon recollision probability (p) and the scattering asymmetry parameter (q), which are parameterized using the directly measurable leaf dry matter. Evaluation against field measurements shows that the proposed leaf-SIP SIF model has a good performance, with coefficient of determination (R2) of 0.89, 0.89, 0.90 and root mean squared errors (RMSE) of 1.28, 0.69, 0.74 Wm−2μm−1sr−1, respectively for the total, backward, and forward fluorescence (660–800 nm). The leaf-SIP SIF model with a more concise formulation demonstrates comparable performance with the widely used Fluspect model. The leaf-SIP SIF model provides a simple and efficient approach for simulating leaf-scale fluorescence, with the potential to be integrated into a unified SIP-based model framework for simulating the radiative transfer processes across the soil-leaf-canopy-atmosphere continuum.
001040884 536__ $$0G:(DE-HGF)POF4-2172$$a2172 - Utilization of renewable carbon and energy sources and engineering of ecosystem functions (POF4-217)$$cPOF4-217$$fPOF IV$$x0
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001040884 7001_ $$0P:(DE-HGF)0$$aZeng, Yelu$$b1$$eCorresponding author
001040884 7001_ $$0P:(DE-HGF)0$$aVilfan, Nastassia$$b2
001040884 7001_ $$0P:(DE-HGF)0$$aHuang, Jianxi$$b3
001040884 7001_ $$aVan Wittenberghe, Shari$$b4
001040884 7001_ $$aHe, Yachang$$b5
001040884 7001_ $$aGao, Yongyuan$$b6
001040884 7001_ $$0P:(DE-Juel1)168454$$aJunker-Frohn, Laura$$b7$$eCorresponding author
001040884 7001_ $$aJohnson, Jennifer E.$$b8
001040884 7001_ $$aSu, Wei$$b9
001040884 7001_ $$aLiu, Qinhuo$$b10
001040884 7001_ $$0P:(DE-Juel1)172711$$aSiegmann, Bastian$$b11
001040884 7001_ $$0P:(DE-HGF)0$$aHao, Dalei$$b12$$eCorresponding author
001040884 773__ $$0PERI:(DE-600)1498713-2$$a10.1016/j.rse.2025.114704$$gVol. 322, p. 114704 -$$p114704$$tRemote sensing of environment$$v322$$x0034-4257$$y2025
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