ReviewRemote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications
Introduction
Monitoring plant status and function from space is of major interest for precision farming, forest management and assessment of the terrestrial carbon budget. Current strategies in optical remote sensing (RS) mainly rely on reflectance data offered by several Earth observing systems which provide estimates of plant status related to structural or biochemical properties such as leaf area index (LAI) or chlorophyll (Chl) content (e.g. Baret et al., 2007). These data can be used to model the potential photosynthetic rates of plant ecosystems. However, plant photosynthesis is an actively regulated process and the efficiency of this biophysical/biochemical reaction is highly variable, in that it adjusts to prevailing environmental conditions by altering or rearranging the pigments within the leaves without any detectable changes in reflectance.
An alternative to this strategy is offered by solar-induced Chl fluorescence (F) which is emitted by the photosynthetic machinery itself and which can provide an early and more direct approach for diagnosis of the actual functional status of vegetation, for example in detecting sub-optimal conditions before significant reductions in Chl content or LAI have occurred. In fact, the emission of light as F is in competition with photochemical conversion and therefore F may allow a more accurate carbon assimilation estimate and earlier stress detection than is possible from reflectance data alone (Entcheva Campbell et al., 2008).
Even though the first attempts to quantify F passively (i.e. without an artificial excitation source) on terrestrial vegetation date back to the 1970s, the challenging issue of the remote measurement of F is still in a developmental stage. Spaceborne observation of F was the concept defining the scientific Fluorescence Explorer (FLEX) satellite mission, submitted to the European Space Agency (ESA) Earth Explorer program call in 2005. Preparatory pre-phase A studies were performed from 2006 to 2008 (www.esa.int/esaLP/LPfuturemis.html, www.esa.int/esaLP/SEMQACHYX3F_LPfuturemis_0.html). Prompted by FLEX, research intensified greatly and resulted in a rapid improvement of F-sensing capabilities during this period. The aim of this manuscript is to provide a comprehensive review of the current methods and devices used to estimate F over terrestrial vegetation together with their applications at different observation scales, from ground to airborne and spaceborne measurements.
Chlorophyll fluorescence can be considered a direct probe of the functional status of photosynthetic machinery because of its relationship with photosynthesis. Typically, part of the energy absorbed by Chl is expelled from the light reactions of photosynthesis and is dissipated as fluorescence (re-emission of light at a longer wavelength than for excitation). Together with the other dissipative pathway, non-photochemical quenching (NPQ or non-photochemical protection), F competes with photosynthesis for the use of the absorbed light. This close relationship enabled plant physiologists to use field- or laboratory-based actively-induced fluorescence measurements as a diagnostic tool to assess the vitality of the photosynthetic apparatus (for a comprehensive overview see Papageorgiou & Govindjee, 2004, for a recent review see Baker, 2008).
Chlorophyll of the pigment–protein complexes exhibits a F emission spectrum in the red and near-infrared regions, characterized by two peaks at approximately 690 and 740 nm (Fig. 1A).
Although fluorescence, photosynthesis and non-photochemical protection are closely connected, the translation of fluorescence data to photosynthesis is not trivial. In fact, while under low light unstressed conditions (no non-photochemical protection mechanisms activated) a negative correlation exists between fluorescence and photochemistry, most studies have observed that in the presence of plant stress and high light conditions, fluorescence declines with photosynthesis (i.e., positive correlation) as a result of protective mechanisms (e.g., deactivation of the antenna, activation of the xanthophyll cycle and non-photochemical protection) which take place in the leaf to prevent damage caused by harmful radicals formed in such stress conditions (Van der Tol et al., 2009).
Plant fluorescence under solar illumination (F) adds a weak signal to reflected solar radiation. If both fluorescence emission and surface reflectance are assumed to follow Lambert's law, the radiance upwelling from vegetation (L) at ground level is therefore composed of two coupled contributions, one reflected (r E / π) and the other emitted (F):where λ is wavelength, r is reflectance (free of the emission component), and E is total irradiance incident on the target. Even though F contributes to the signal detected by a remote sensor, its magnitude is small (1–5% of the reflected radiation in the near-infrared) thus making the decoupling of the two contributions difficult. Zarco-Tejada et al. (2000a) first recognized the effect of F on r and demonstrated that it is possible to detect the F signal using r measurements. In fact, the reflectance factor usually computed by the RS community as the ratio between upwelling and incident fluxes is indeed polluted by the F contribution:
This quantity, referred here as apparent reflectance, r⁎, differs from the pure reflectance (r) as indicated by the right hand side of Eq. (2) and as shown in Fig. 1B.
Progress in understanding the effect of F in remotely-sensed data have also been made through the development and integration of leaf and canopy F models based on physical methods (Maier, 2000, Olioso et al., 1992, Rosema et al., 1998, Zarco-Tejada et al., 2000a). The FluorMOD canopy F model (Miller et al., 2005) builds on these earlier efforts and provides simulations of incident and reflected radiance and of emitted F by linking three radiative transfer models: MODTRAN-4 for the atmosphere (Berk et al., 1989), FluorMODleaf (Pedrós et al., 2005) for the leaf (based on the PROSPECT model, Jacquemoud & Baret, 1990), and SAIL for the canopy optical properties (Verhoef, 1984, Verhoef, 2005). For a user-friendly interface to the FluorMOD model, the reader is referred to the FluorMODgui tool (Zarco-Tejada et al., 2006) available on line at http://www.ias.csic.es/fluormod.
Section snippets
Rationale for passive estimation of F
The F signal is comparably stronger and can be detected passively in narrow dark lines of the solar and atmospheric spectrum in which irradiance is strongly reduced (the so-called Fraunhofer lines). In the visible and near-infrared, the solar spectrum at ground level exhibits three main “Fraunhofer” features which have been exploited for F estimation: Hα due to hydrogen (H) absorption in the solar atmosphere (centered at 656.4 nm) and two telluric oxygen (O2) absorption bands in the Earth
Review of methods used for estimating F
Methods used to quantify F are divided into two major categories: radiance-based and reflectance-based approaches. The former makes use of radiance measurements (in physical units or instrument counts) and exploits the Fraunhofer line to decouple F from the reflected flux. The latter operates with spectral reflectance and does not necessarily require correspondence to a Fraunhofer line. While the radiance-based approach is able to estimate F, either in physical or auxiliary units, the
Review of devices and applications
In this section we present the development of F-sensing capabilities from pioneer works of the 1970s to the current state of the art. Studies conducted at ground, aircraft and satellite levels are listed (Table 3) together with relevant information concerning retrieval method, device used and practical application of the study.
The majority of the research has been performed at ground level, thus exploiting the easier availability of ground-based instruments. The practical goal of most of the
Range of variation of F under natural daylight conditions
In order to provide an overview of the results of experiments aimed at F estimation, we present a comparison of F estimates on different vegetation types, at different observation levels and using different techniques and devices. This comparison was possible for those studies providing F in absolute units (less than half of the total number of studies reviewed). The ranges of F variation in the O2-A and O2-B bands extrapolated from papers providing estimates in physical units are reported in
Summary and outlook
Measuring vegetation fluorescence remotely is an appealing prospect but also a challenging one. In this manuscript we review progress towards this goal and we make a first attempt at classifying the different retrieval approaches in some major groups. A rule of thumb to address the best method for estimating F cannot be given here for two reasons. First, an assessment of the estimation error of the various methods is missing. This lack of validation is due to the fact that F cannot be measured
Acknowledgments
This work has been made possible by the funding support of the ESA-project FLEX Performance analysis and requirements consolidation study, through ESTEC contract no. 21264/07/NL/FF. The authors would like to thank the four anonymous reviewers of this manuscript for their valuable comments which have helped us to improve the completeness and overall quality of the paper.
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