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

本研究将验证从植被的光谱反射率推导出的“生理反射率指数”可以预测光合效率和能力的假设。这一假说认为，叶片和冠层遵循光能分布的生态生理“规则”，导致PAR分布与光合通量之间的关系一致。采用光谱反射率、叶片气体交换和荧光同步测量常绿物种的实验研究将对光合作用调节和光谱反射率之间的关系进行机制理解。这些实验将用于推导一个包含“生理反射指数”的叶片水平模型，该模型将光谱反射率与光合通量联系起来。叶片和冠层反射率的实验比较将提供从冠层光谱反射率预测光合效率和能力的算法。这项工作使一位年轻而非常有前途的生态系统科学家能够利用本科院校的少数民族学生。虽然在叶片和冠层水平上对植被的生理功能了解最多，但这些结论可能对未来在景观水平上进行植被-大气相互作用的遥感研究有益。

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.