EFFECTS OF VEGETATION DIRECTIONAL REFLECTANCE ON SUN-INDUCED FLUORESCENCE RETRIEVAL IN THE OXYGEN ABSORPTION BANDS

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1 EFFECTS OF VEGETATION DIRECTIONA REFECTANCE ON SUN-INDUCED FUORESCENCE RETRIEVA IN THE OXYGEN ABSORPTION BANDS A Fournier (1), Y. Goulas (2), F. Daumard (3), A.Ounis (2), S.Champagne (4), I.Moya (2) (1) ARVAIS Institut du Végétal, 45 voie romaine Ouzouer-le-Marché (France), a.fournier@arvalisinstitutduvegetal.fr (2) CNRS- ab. Met. Dynamique, École Polytechnique, Palaiseau (France), goulas@lmd.polytechnique.fr, ounis@lmd.polytechnique.fr, moya@lmd.polytechnique.fr (3) INRA- AgroParisTech, UMR Env. Grande Cultures, Route de la Ferme F Thiverval-Grignon (France), fabrice.daumard@grignon.inra.fr (4) MEAS-IT, 23 Rie de la petite Fontaine Vauhallan, champagne@meas-it.fr ABSTRACT Remote sensing of sun induced fluorescence (SIF) in absorption bands is based on the analysis of the changes in atmospheric absorption features between reflected and incident sunlight. Indeed, chlorophyll fluorescence increase the reflected light in the same amount insight and outside the absorption features, thus reducing the apparent depth of bands. However, incoming light is a mixture of direct and radiation. Diffuse light experienced a longer optical path, and have a greater absorption band depth than direct light. Furthermore incoming light is often estimated globally by measuring radiance from a reference board. As the vegetation reflectance response may be different for incoming direct and radiation, it may results in a variation of the absorption features estimated in the vegetation radiance that would impact fluorescence retrieval using conventional algorithms. These directional reflectance effects coupled to the angular distribution of incoming irradiance have been already mentioned in the literature as a possible source of artefacts in remote sensing of SIF using oxygen bands (Guanter et al. 2010). But until now, no experimental nor theoretical analyses of these effects on fluorescence retrieval have been reported. In this study, we report first experimental evidence of such a bias by comparing reflected and incoming sunlight under different illumination regimes over a senescent wheat crop containing no chlorophyll. Canopy structure was modulated by ears cutting and rows removing in order to evaluate the link between architecture, density and the measured bias. It was found that the bias dynamically evolved with daytime and illumination conditions. A maximum appears when and direct incident radiations are balanced. We propose an analytical scheme to account for directional reflectance effects in fluorescence retrieval algorithms (FD, 3FD, SFM) by considering different vegetation reflectance responses for direct and radiations. A numerical model based on SAI and MODTRAN was developed to estimate these responses for different canopy architectures and illumination patterns. The simulated bias was in the same order of magnitude than the observed one, supporting the evidence of vegetation directional effects on fluorescence retrieval using commonly used algorithms. Application of this numerical model to green canopies for operational bias correction is discussed. Finally, a classification of experimental cases where directional effects can be neglected is proposed. 1. A SUSPECTED EFFECT 1.1. Historical intuition and operational observation Knowing the interest of steady state fluorescence variations relatively to illumination intensity as an index of stress status of a leaf (among others Cerovic, 1996, Flexas, 2000, Ounis, 2001) several authors had follow the steady state fluorescence over canopies during cloud shadowing using absorption band in-filling. When this approach was applied into Oxygen absorption bands some trends appears to be hardly attributable to pure physiological response. When simultaneous measurement where performs, the solar H bans shows none of the effects affecting O 2 terrestrials bands. Those observations have trigged an intuition into the community of an expectable effect especially visible during sun/shade illumination transitions. This intuition was support by early numerical simulations (see FluoMODleaf report Miller et al., 1999) Assessing the irradiance Operational retrieval of reflectance is based on hypothesis about the local irradiance of the target. Those hypotheses often include an assumption of isotropy of irradiance at ground level.

2 5th INTERNATIONA WORKSHOP ON REMOTE SENSING OF VEGETATION FUORESCENCE, APRI 2014, PARIS (FRANCE) 2 In the case of remote sensing of SIF, natural irradiance at ground level is one step more complex when we have to consider its anisotropy in the spectral vicinity of telluric absorption band. Depth is the ratio of irradiance intensity at maximum absorption band over the spectral continuum. The angular distribution of this ratio shows a pronounced angular and temporal variability. The driving illumination conditions are expected to be daytime, clouds cover and also atmospheric composition are key factors to understand such interception effects. As formulated by Plascyk in 1975, the reflectance is estimated in order to be separate from fluorescence in the radiance. And the reflectance estimated under such anisotropic light should be biased, inducing a complementary bias on the fluorescence. We propose to set up a dedicated experiment for evidence of this specific bias on a natural canopy. 2. A dedicated experiment for a specific bias 2.1. Fluosensor The field part of this study was conduct in 2009 on the GFlex instrumented site. The passive fluosensor based on three spectrometers thermally regulated and managed by a computer, is installed in the top of a crane (Daumard et al, 2010). It allows a continuous acquisition over all the life cycle of an agronomical controlled crop over circular target spot of 2 meters diameter Non fluorescent crop In order to ensure null or neglectable fluorescence and a 3D structure as representative as possible of the structure of a natural canopy, we perform acquisitions during the very advance senescent stage of wheat (Triticum turgidum). Expect for leaf shape modification and loss of few basal leaves, the senescent crop structure is similar to mature canopy especially a good verticality of ears and no lodging Crop geometry modification Because BRDF is known to depend on canopy structure, we modified two square areas of 4 by 4 meters. The first area was modified by removing all ears. This canopy is compounds by stem and vestigial leaves which increase significatively its erectophily. We call this target the easr removed wheat. The second area was modified by removing on row out of two which decrease its density. We call this target the sparse wheat In parallel two others surface were monitored: - A 8 by 4 meters horizontal board of frosted PVC which is used as an irradiance probe at ground level to correct the 50 meters vertical absorptions effects. - And a square area of bare soil free of any vegetation Monitoring of irradiance The illumination configuration was monitored through a dedicated set up build to access to the PAR intensity and to narrow resolution spectra of two component of irradiance: - Irradiance coming from all the superior hemisphere, designated as total irradiance in the following, - And irradiance coming from the superior hemisphere minus the sun direction angles Adapted metrics The simplest variable describing the intensity of absorption is depth (D) of a band. It is defined as the ratio of continuum radiation ( ) divided by radiation at maximum of absorption ( ). If calculated on radiance, this variable has to be corrected from reflectance slope of the target. Due to absorption this variable is higher than one. D (1) Experimental Depth (D exp ) is defined as the ratio of depth of the radiance from a target (D target ) divided by the depth on local irradiance. This irradiance depth is deduced from the radiance of a characterized plane reference (D reference ). This operational depth is representative of band in filling and should be lower than one. Dt arg et Dexp D (2) reference In a first order approach, this experimental depth should be equal to one in the absence of fluorescence. The distance of D exp to one is positively related to fluorescence contribution to radiance (Frc). Fluorescence Frc (3) This relation between Experimental depth and fluorescence is affected by the instantaneous value of irradiance depth. 1 Dexp Frc (4) D ( 1) exp D reference

3 5th INTERNATIONA WORKSHOP ON REMOTE SENSING OF VEGETATION FUORESCENCE, APRI 2014, PARIS (FRANCE) 3 3. RESUTS UNDER CEAR SKY Four non fluorescence targets presenting different geometrical structure were follow on three consecutive days around solar noun. Tab.1 summarise the experimental depth and the deduced equivalent fluorescence fluxes calculated with eq. 3 knowing a reference depth of 5 and the total radiant flux harvest by the sensor. Target Experimental Depth Fluorescence bias (mw.m -2.sr -1.nm -1 ) Bare Soil Senescent wheat Sparse senescent wheat Ears removed senescent wheat Table 1. experimental depth and equivalent bias of fluorescence overestimation on four non fluorescent targets around solar noon. For comparison purpose : the wheat canopy has emit 1.5 to 2 mw.m -2.sr -1.nm -1 when it was green. Those values can be compared to the fluorescence flux observed on the same wheat canopy before senescence which has typical values at solar noon under clear sky of 1.5 to 2 mw.m -2.sr -1.nm -1. The depletion of experimental depth is maximum on ears removed canopy which indicate a principal sensitivity to erectophily. The magnitude of deduced bias is equal between intact canopy and the sparse canopy, indicating a reduced impact of canopy density. A non-null effect can be observed on bare soil, questioning its use as a reference surface for irradiance probing. 4. SIMPE MODEISATION AND SIMUATION A simple formulation of an expectable bias related to a differentiate interception of illumination component and its numerical simulation is aimed to check consistency of such hypothesis in front of observation Bias expression In order to formulate an expectable fluorescence bias induced by complex reflectance directional distribution of targets illuminate by a complex distribution of irradiance, we can start with a two component formulation of the classical FD equation 5 rad R F (5) irad 1 Where rad and irrad are the light flux from the target and the light flux incoming to the target. R being the reflectance factor associated to the acquisition geometry and F the fluorescence. The two term equation as: rad diff diff dir ( R R dir ) F (6) irad irad 2 We write on equation 7 the bias resulting by using direct as sum of and instead of a irad irad irad composition affected by the specific reflectance factors R and R direct. In this equation the and direct depth are define as: diff D (8) And dir D (9) direct direct This equation is the product of a reflectance term and an illumination term. We can infer from the reflectance term that the effect will be proportional to de difference between the reflectance factor associated to sun direction (R dir ) and the reflectance factor associated to the rest of the superior hemisphere (R diff ). Depending on sun elevation, a diurnal pattern is expectable for this term and annulation points could be found. On perfect lambertian reference the effect should be null. Observation seems to support such interpretation. Indeed the ears removed wheat is the more erectophill and a more pronounced geometry is often associates with stronger BRDF anisotropy. The numerator of illumination indicate that if the intensity of one of the two terms of illumination is neglectable, the effect is minimal and a maximum effect should be attain for intermediary illumination condition when and direct illumination are on the same order of intensities. dir diff diff dir dir diff I I ( D D ) F 1 F ( R R ) 2 diff diff dir dir dir diff I ( D 1) D I ( D (8) 1) D

4 5th INTERNATIONA WORKSHOP ON REMOTE SENSING OF VEGETATION FUORESCENCE, APRI 2014, PARIS (FRANCE) Simulation The reflectance term was numerically simulated with a Mathematica implementation of SAI code. Figure 2 present diurnal evolution of and direct reflectance factor from 8 to 20:00 local time (UTC+2) calculated with the reflectance acquired manually on leafs and stem of senescent wheat. day along with the bias expressed in term of experimental depth for this same day. Figure 4: comparison of measured and simulated experimental depth around noon on a sunny day. Simulation appears to fits well the intensity of an expected effect at solar noon. But the temporal trend is not coherent with observed evolutions. Figure 2: diurnal evolution of direct a reflectance factor simulated with SAI using senescent leaves spectra as elements spectra. The illumination term was simulated using MODTRAN 4. The figure 3 present diurnal evolution of fraction and the depth of a direct radiation for the spectral bands and resolution of the Instrument used for acquisition on senescent wheat. This tool can also be extended to evaluate an expectable bias at solar noon over the same canopy when it was green and fluorescent. Using green element reflectance into SAI and applying MODTRAN simulation for the right dates, we found a steady additional contribution of 30% of sensed fluorescence flux into O 2 A band. This value significatively higher than deduced from tab.1 can be explain by the limitation of SAI to represent accurately the BRDF of a strongly erectophill wheat crop. Figure 3: Diurnal evolution of direct and Irradiance depth and fraction simulated with MODTRAN4. First manipulation of this tool is to reproduce conditions of acquisition over senescent wheat. Figure 4 presents temporal evolution around solar noon of measured experimental depth over senescent wheat for a clear sky Figure 5: example of a diurnal simulation of expectable bias for different geometrical parameter of the canopy. Standard case: AI = 2, spheroidal distribution of leaf area angle.

5 5th INTERNATIONA WORKSHOP ON REMOTE SENSING OF VEGETATION FUORESCENCE, APRI 2014, PARIS (FRANCE) 5 Such a tool can also be used to evaluate driving variable of the effect as canopy structure through eaf Area Index or leaf angle distribution (fig 5) or geometry of acquisition (fig. 6). ACKNOWEDGMENTS Authors are grateful to their colleague of INRA- Avignon for experimental support and fruitful discussions. This work has been conduct on the framework of a PhD grants funded by AIRBUS D&S (formerly ASTRIUM). Crane platform and fluorescence campaign were conduct with the support of CNES- PNTS. REFERENCES Figure 6: example of a simulation of expectable bias for different angle of sight at different hours. Standard case: AI = 2, spheroidal distribution of leaf area angle, sight-sun azimuthal angle is ESSENTIA ESSONS TO REMEMBER 5.1. Evidence and bounding of a methodological bias By setting up an experiment dedicated to fine sensing of fluorescent zero over non fluorescent structured canopies, we provide evidence of a bias specific to infilling measurements into absorption band generated in the earth atmosphere. The effect show stable, positive and limited additional values for clear sky conditions boundable to 30% in worth cases. The effect is notably higher for illumination intermediary state and can be positive and negative Modelled and simulated We propose a formulation of the expectable bias based on the hypothesis of two illumination terms: and direct. A numerical simulation relying on SAI and MODTRAN 4 provide a good accordance to acquisition with the same intensity effect at solar noon under clear sky conditions. Such tools can be extend to infer the operational bias over green canopy or to investigate acquisition configuration minimising its intensity Operational correction affordable This simple model can be improved by adding environmental illumination terms which is known to be a significative component of ground level targets. The formulation of such bias can also be extended to a spectrally dependent formulation in order to be operationally corrected into existing fluorescence retrieval algorithm. Numerical simulation with MODTRAN models are bounds to considers, direct and environmental illumination. A spectro-angular numerical simulator of illumination would be the key tool for a complete analysis of the natural occurrence of such bias. [1] Cerovic, Z.G., Goulas, Y., Gorbunov, M., Briantais, J.-M., Camenen,., Moya, I., 1996, Fluoresensing of water stress in plants : diurnal changes of the mean lifetime and yield of chlorophyll fluorescence, measured simultaneously and at a distance with a t-ida and a modified PAM fluorimeter, in maize, sugar beet and kalanchöe. Remote sensing of environment 58: [2] Daumard F., Champagne, S., Fournier, A., Goulas, Y., Ounis, A., Hanocq, J.F., Moya, I., 2010, A field platform for long-term measurement of canopy fluorescence. IEEE transaction on geoscience and remote sensing, 48 (9): [3] Flexas, J., Briantais, J.M., Cerovic, Z. Medrano, H., Moya, I., 2000, Steady-state and maximum chlorophyll response to water stress in grapevine leaves: A new remote sensing system. Remote Sensing of Environment, 73: [4] Miller, J., Berger, M., Goulas, Y., Jacquemoud, S., ouis, J., Mohammed, G., Moise, N., Moreno, J., Moya, I., Pedrόs, R., Verhoef, W., Zarco-Tejada, P., 2005, Development of a vegetation fluorescence canopy model. ESTEC publication. FluorMOD final report. [5] Ounis, A., Evain, S., Flexas, J., Tosti, S., Moya, I., 2001, Adaptation of a PAM-fluorometer for remote sensing of chlorophyll fluorescence. Photosynthesis Research, 68: [6] Plascyk, J.A., 1975, The MKII Fraunhofer line discriminator (FD-II) for airborne and orbital remote sensing of solar simulated luminescence. Optical Engineering, 14: