Fluorescence sensing techniques for vegetation assessment

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 (O2) 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.