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Fluorescence sensing techniques for vegetation assessment

机译:用于植被评估的荧光传感技术

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摘要

Active fluorescence (F) sensing systems have long been suggested as a means to identify species composition and determine physiological status of plants. Passive F systems for large-scale remote assessment of vegetation will undoubtedly rely on solar-induced F (SIF), and this information could potentially be obtained from the Fraunhofer line depth (FLD) principle. However, understanding the relationships between the information and knowledge gained from active and passive systems remains to be addressed. Here we present an approach in which actively induced F spectral data are used to simulate and project the magnitude of SIF that can be expected from near-ground observations within selected solar Fraunhofer line regions. Comparisons among vegetative species and nitrogen (N) supply treatments were made with three F approaches: the passive FLD principle applied to telluric oxygen (O_(2)) bands from field-acquired canopy reflectance spectra, simulated SIF from actively induced laboratory emission spectra of leaves at a series of solar Fraunhofer lines ranging from 422 to 758 nm, and examination of two dual-F excitation algorithms developed from laboratory data. From these analyses we infer that SIF from whole-plant canopies can be simulated by use of laboratory data from active systems on individual leaves and that SIF has application for the large-scale assessment of vegetation.
机译:长期以来,人们一直建议使用主动荧光(F)传感系统来识别物种组成和确定植物的生理状态。用于植被的大规模远程评估的无源F系统无疑将依赖于太阳诱发的F(SIF),并且该信息可能可以从Fraunhofer线深度(FLD)原理中获得。但是,了解从主动和被动系统获得的信息与知识之间的关系仍有待解决。在这里,我们提出一种方法,其中使用主动感应的F光谱数据来模拟和预测SIF的大小,这可以从选定的太阳能Fraunhofer线区域内的近地观测获得预期。通过三种F方法对植物物种和氮(N)的供应处理进行了比较:被动FLD原理应用于现场获得的冠层反射光谱中的碲氧(O_(2))波段,主动诱导的实验室发射光谱模拟的SIF离开了一系列Fraunhofer太阳线(范围从422至758 nm),并检查了根据实验室数据开发的两种双F激发算法。从这些分析中,我们可以得出结论,可以通过使用来自单个叶子上的活动系统的实验室数据来模拟全植物冠层的SIF,并且SIF可用于大规模的植被评估。

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