RUI: Predicting Photosynthetic Fluxes from Spectral Reflectance of Leaves and Canopies

这项研究将验证光合作用 效率和能力可以从“生理”预测， 反射率指数”来自光谱反射率的 植被 这一假说假设树叶和树冠 遵循光能分布的生理生态“规律” 从而导致PAR分布与 光合通量 实验研究采用并行 光谱反射率、叶片气体交换和 万年青植物的荧光会产生一种机制 理解光合调节与 和光谱反射率。 这些实验将被用来推导 结合“生理反射率”的叶片水平模型 将光谱反射率与光合通量联系起来的“指数”。 叶片和冠层反射率的实验比较将 提供用于预测光合效率的算法， 冠层光谱反射能力。 %%% 这项工作使一位年轻而非常有前途的生态系统科学家 在本科院校利用少数民族学生。 虽然最了解生理功能的人 叶和冠层水平，结论可能有益于未来的研究 涉及遥感的植被-大气相互作用 景观水平。

This research will test the hypothesis that photosynthetic efficiency and capacity can be predicted from "physiological reflectance indices" derived from spectral reflectance of vegetation. This hypothesis assumes that leaves and canopies follow ecophysiological "rules" of light energy distribution resulting in consistent relationships between PAR distribution and photosynthetic fluxes. Experimental studies employing concurrent measurements of spectral reflectance, leaf gas exchange and fluorescence on evergreen species will develop a mechanistic understanding of relationships between photosynthetic regulation and spectral reflectance. These experiments will be used to derive a leaf-level model incorporating "physiological reflectance indices" linking spectral reflectance to photosynthetic fluxes. Experimental comparisons of leaf and canopy reflectance will provide algorithms for predicting photosynthetic efficiency and capacity from canopy spectral reflectance. %%% This work enables a young and very promising ecosystem scientist utilizing minority students at an undergraduate institution. Although the most understanding of physiological function at the leaf and canopy levels, the conclusions may benefit future studies of vegetation-atmosphere interactions involving remote sensing at the landscape level.