Abstract
Leaf chlorophyll content plays a vital role in plant photosynthesis. The PROSPECT model has been widely used for retrieving leaf chlorophyll content from remote sensing data over various plant species. However, despite wide variations in leaf surface reflectance across different plant species and environmental conditions, leaf surface reflectance is assumed to be the same for different leaves in the PROSPECT model. This work extends the PROSPECT model by taking into account the variation of leaf surface reflection. In the modified model named PROSPECT-Rsurf, an additional surface layer with a variable refractive index is bounded on the N elementary layers. Leaf surface reflectance (Rs) is characterized by the difference between the refractive indices of leaf surface and interior layers. The specific absorption coefficients of the leaf total chlorophyll and carotenoids were recalibrated using a cross-calibration method and the refractive indices of leaf surface and interior layers were obtained during model inversion. Chlorophyll content (Cab) retrieval and spectral reconstruction in the visible spectral region (VIS, 400–750 nm) were greatly improved using PROSPECT-Rsurf, especially for leaves covered by heavy wax or hard cuticles that lead to high surface reflectance. The root mean square error (RMSE) of chlorophyll estimates decreased from 11.1 µg/cm2 to 8.9 µg/cm2 and the Pearson’s correlation coefficient (r) increased from 0.81 to 0.88 (p < 0.01) for broadleaf samples in validation, compared to PROSPECT-5. For needle leaves, r increased from 0.71 to 0.89 (p < 0.01), but systematic overestimation of Cab was found due to the edge effects of needles. After incorporating the edge effects in PROSPECT-Rsurf, the overestimation of Cab was alleviated and its estimation was improved for needle leaves. This study explores the influence of leaf surface reflectance on Cab estimation at the leaf level. By coupling PROSPECT-Rsurf with canopy models, the influence of leaf surface reflectance on canopy reflectance and therefore canopy chlorophyll content retrieval can be investigated across different spatial and temporal scales.
Highlights
Leaf chlorophyll plays a critical role in plant photosynthesis and the conversion of CO2 into stored carbohydrate
We demonstrated that incorporating variable leaf surface layer reflectance in the PROSPECT-Rurf model is effective in improving the leaf chlorophyll content retrieval as well as spectral simulation, especially for leaves with high surface reflectance
The root mean square error (RMSE) of Cab estimates decreased from 11.1 μg/cm2 to 8.9 μg/cm2 and the Pearson’s correlation coefficient (r) increased from 0.81 to 0.88 (p < 0.01) for broadleaf samples in validation datasets, compared to PROSPECT-5
Summary
Leaf chlorophyll plays a critical role in plant photosynthesis and the conversion of CO2 into stored carbohydrate. As light directly reflected from leaf epidermis does not interact with interior materials, it contains little information on the leaf biochemistry and should be excluded from the remotely sensed leaf reflectance. Leaf surface reflectance varies greatly with plant species, leaf development and environmental conditions [6,7,8]. It is controlled by epidermal characteristics such as the morphology and density of epicuticular waxes or trichomes [4,9], which can greatly enhance the leaf reflectance in the VIS [10,11]. Leaf specular reflectance from a surface is usually considered as wavelength-independent [13], as the leaf cuticle usually contains no pigments [7]
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