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Abstract
Laser-induced fluorescence (LIF) technology has been widely applied to monitor vegetation growth status and biochemical concentrations. Thus, it is important to accurately acquire the fluorescence information for the quantitative monitoring of vegetation growth status. In this study, firstly, the incidence angle’s effect on chlorophyll fluorescence intensity was analyzed by using the FluorMODleaf model. Then, comprehensive experimental data on the angle dependence of the fluorescence intensity to vegetation leaf surface were collected. Numerical and experimental results showed that proposed corrected cosine expression could be used to describe the relationship between the incidence angle and the fluorescence intensity in the LIF-Lidar. Lastly, fluorescence signals at 685 and 740 nm extracted at different incident angles of excitation lights were fitted with the corrected cosine expression. The coefficient of determination (R2) of the fitting results reached a maximum value of 0.93 for Salix babylonica.
© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Laser induced fluorescence (LIF) technology has been applied in various scientific fields [1–4] such as chemistry, biology, and medicine. It has also attracted considerable attention in the field of remote sensing, particularly after Cecchi et al. [5] proposed the LIF light detection and ranging (lidar). LIF technology enables the sensitive identification and quantitative detection of vegetation cover. It can be used for the accurate detection of the global carbon sink, carbon cycle, vegetation status and chlorophyll concentration [6–8]. It has been widely applied in monitoring of vegetation status and productivity [9,10]. Moreover, LIF has been used to detect the changing status of blue-green algae in lake Sunwa [11]; to determine water quality parameters [12]; and to diagnose the status of outdoor cultural heritage and archaeology [13,14]. Saito et al. developed fluorescence lidar and used to monitor pollens floating in the atmosphere and used to observe the global environmental systems by connecting the livingsphere and natural system [15,16]. Sugimoto et al. also built a lidar with 32-channel to detect fluorescence signal of aerosols and indicated the feasibility of developing a compact Raman-Mie-fluorescence lidar for aerosol monitoring [17]. In addition, Kalaji et al. analyzed some questions about the instruments, methods and applications of Chlorophyll a fluorescence [18,19]. Thus, LIF-Lidar is an efficient tool for monitoring the status of vegetation in the application of remote sensing. However, geometric characteristics of target will introduce several system uncertainties, which consequently restrict the practical application of LIF-Lidar system. Several studies have been conducted on the effects of geometric characteristics of targets on lidar [20,21]. However, the study about the interaction of excitation light with the optical properties of targets (i.e., in the context of LIF, the effect of the incidence angle on fluorescence intensity based on LIF-Lidar) is still sparsely [9].
LIF-Lidar is used to monitor vegetation by collecting the fluorescence spectrum. In this setup, the light paths of the detector coincide with that of the incident light. Numerous optics and physics studies have shown that geometric factors considerably affect the measurements of fluorescence information [22]. Thus, in remote sensing, eliminating the effect of the geometric features of targets on the intensity information from LIF-Lidar is necessary.
At present, the effect of the incidence angle on the reflected spectral intensity in lidar has been experimentally and computationally addressed in several investigations [20,21]. For LIF technology, Saito et al. [9] set the receiving optical fiber set at 90° to the leaf surfaces to analyze the effect of the incidence angle of excitation light on the fluorescence intensity. Meroni et al. [23] assumed that fluorescence intensity can be described by a cosine expression, which in turn is utilized to extract solar-induced fluorescence signals from reflectance spectra. However, none of these works has investigated the effects of incidence angles on the fluorescence intensity in LIF-Lidar systems. Moreover, systematic experimental data on the effects of incidence angles on chlorophyll fluorescence intensity of different vegetation species are still sparse. Thus, the effect of the incidence angle on the chlorophyll fluorescence intensity should be investigated to advance LIF-Lidar.
Therefore, the main objective of this study is to discuss the effect of the incidence angle on fluorescence intensity based on the LIF-Lidar system. The FluorMODleaf model is used to numerically analyze the effect of the incidence angle on the laser-induced chlorophyll fluorescence intensity. Then, a comprehensive experiment is conducted to identify the angle dependence of the LIF intensity of vegetation. Thereafter, a corrected cosine expression is proposed for the quantitative analysis of the correlation between fluorescence intensity and the incidence angle.
2. Materials and experiment
2.1 Theory
Previous investigations [6,24,25] have shown that the fluorescence intensity of leaves can be described using the FluorMODleaf model which is based on the PROSPECT model [25,26]. In this model, a leaf is represented as a plate. According to the study of Pedrós [26], the emission fluorescence intensity with the changing of incidence angles can be calculated by following expression:
Where and are the upward and downward fluorescence signals of the leaf, respectively; is the fluorescence source; is transmissivity between media i and j; the subscripts s and m are the excitation and emission wavelength, respectively; is the reflectivity between i and j; and and is the transmission of the leaf for incidence and fluorescence light, respectively. is the differential of . ; is the incidence angle. The detailed description of FluorMODleaf model can be found in [26]. Thus, the leaf fluorescence intensity, which varies with incidence angle, can be calculated. The input parameters in the Eq. (1) included: N (leaf structure parameter), Cab (chlorophyll a + b concentration), Cw (equivalent water thickness), Cm (dry matter content), Sto (PSII: PSI stoichiometry), and (fluorescence quantum efficiency or quantum yield). According to [26], the input parameters set as: N = 1.5, Cab = 30ug/cm2. Cw = 0.025cm, Cm = 0.01g/cm2, Sto = 2, and = 0.04 in this research.2.2 Materials
In order to improve the universality of the application, the dicot and monocot species should be included in these samples. Then, six types of vegetation (including Magnolia denudata (Dicot), Scindapsus aureus (Monocot), Firmiana platanifolia (Dicot), Elaeocarpus decipiens Hemsl (Dicot), Salix babylonica (Dicot), Bambusoideae (Monocot)) were selected according to the characteristics of the growing area of the vegetation. The area is located at Jianghan Plain of China where the latitude range of 29°26′ N to 31°22′ N, and the longitude range of 111°45′ E to115°05′ E, which is a subtropical zone. Fresh healthy and half-year-old leaves were randomly collected. The leaves were destructively sampled by stochastically cutting six leaves with three replicates. These leaves were sealed in plastic sacks, stored in an ice chest, and immediately transported to the laboratory for fluorescence spectra measurements [27].
2.3 Experimental system
Figure 1 presents the schematic of the system used to measure the effect of the incidence angle on fluorescence intensity. The system is composed of three main parts: an excitation source, an optical receiver system, and a signal acquisition assembly. The excitation light source was an Nd: YAG laser with a wavelength of 355 nm, repetition frequency of 20 Hz, output power of 1.5 mJ, and width per pulse of 5 ns. The excitation light passed through the optical system and irradiated on the foliar sample without causing damage to them. Fluorescence signals were collected by a fiber optics cable with a diameter of 200 µm. The distance between the fiber optics and the target was 1.2 m. Fluorescence excitations were transmitted into the fiber optics and focused through a 0.05 mm slit prior to collection by a spectrometer. Fluorescence signals varying with wavelengths was detected by an intensified charge-coupled device. Data were stored on a personal computer. An additional long-pass filter with an edge of 360 nm was placed in front of fiber optics to prevent the reflected light from the laser entering fiber optics.
Fig. 1 Schematic of the LIF system for the measurement of fluorescence at different incidence angles. ICCD: intensified change-coupled device; PC: personal computer; OS: optical system; BE: 5 times the beam expander at 355nm.
The sample was placed on a rotator. A precision goniometer was used to change the incidence angle from normal (0°) to 85°. The optical axis of the excitation light source and rotation axis of the rotator were placed on the same plane to eliminate the movement effect of the rotation platform on the measured position. The excitation light was perpendicular incidence onto the rotation axis at the initial position of the swivel table. The direction of receiving fiber optics tries to coincide with the path of the excitation light source to ensure that the incidence angle was closed to the detection direction and the angle between the laser beam and fluorescence path is less than 1° which can be ignored when analyzed the effect on incidence angle on fluorescence intensity. The system used in the present is similar to that used by a previous paper [28]. In this study, fluorescence spectra were collected over the wavelength range of 360-800 nm with a sampling interval of 0.5 nm. The incidence angle ranged from 0° to 85° with a sampling interval of 5°. The variation in the fluorescence spectra of six different plant species over different incidence angles is presented in Fig. 2.
Fig. 2 Variations in relative fluorescence intensity with incidence angles plotted over 360-800 nm under 355 nm excitation laser. (a) Magnolia denudata; (b) Scindapsus aureus; (c) Firmiana platanifolia; (d) Elaeocarpus decipiens Hemsl; (e) Salix babylonica; (f) Bambusoideae.
2.4 Statistical parameters
The coefficient of determination (R2), root mean square error (RMSE), and sum of squared error (SSE) were utilized to assess the performance of the proposed cosine expression for fitting the measured data. Low RMSE and SSE and high R2 represent a good performance of model [29].
3. Results and discussion
Figure 2 shows the effect of the incidence angle on the chlorophyll fluorescence intensity of six different plant species. All fluorescence spectra were normalized to 1 at 460 nm. These fluorescence spectra of the six plant species exhibited two main red fluorescence peaks at 685 nm and 740 nm attributed to center pigment (CPI) of Photosystem II and antennae chlorophyll (CPa) of Photosystem I, respectively [30]. The blue fluorescence maximum at 460nm attributed to the compounds on the vacuole and cell wall of the leaf epidermis and leaf veins include ferulic acid, other phenylpropanoids as well as the products of the plant secondary metabolism [31,32]. The fluorescence intensity at peak wavelength of 685 nm and 740 nm are strongly related to the photosynthesis and productivity of vegetation [33–35]. The fluorescence spectra of all six plants changing with incidence angle exhibited the same variation trend at 685nm and 740nm. Changing in the fluorescence intensity in relation to the incidence angle were not obvious when incidence angle was less than about 45° at 685nm and 740nm. However, fluorescence intensities dramatically decreased with increasing incidence angle (i.e., about ≥45°). Although the actual mechanism that underlies this response is difficult to determine in the present work, a possible interpretation may be that the excited fluorescence signals are reabsorbed by chlorophyll on its way towards the leaf surface. The reason is that the presence of densely packed palisade cells in the upper leaf side increases the reabsorption by chlorophyll a of the red fluorescence induced from this side [36,37]. Moreover, the transmissivity of the excitation light decreased as incidence angles increased in accordance with the FluorMODleaf model. The laboratory measurements obtained in the present study are consistent with those reported by Saito et al. [9]. Thus, the effects of incidence angle on fluorescence intensity should be considered in quantitative analysis (i.e., monitoring of crop nutrition stress and assessment of corps yields).
Fluorescence is that the fluorophore ray part or all of its absorbed energy. Fluorescence emission, which varied with incidence angle, can be calculated on the basis of the FluorMODleaf model at Eq. (1). To compare the fluorescence intensities of different samples [21], the fluorescence intensities at peak wavelengths of 685 nm and 740 nm with varying incidence angles were normalized to 1 at 0°. The variation in the fluorescence intensities of six different plant species with incidence angle are presented in Fig. 3. The relationship between fluorescence intensity and incidence angle was close to the calculated results provided by the FluorMODleaf model when the incidence angle ranges from about 0° to 45°. The variation trend of fluorescence intensity as the incidence angle exceeded about 45° is rapid decrease. One possible interpretation is that the intensities of excitation light decreases with the increase in incidence angles due to the optical path of fluorescence is positive correlation with reciprocal of cosine [9]. In addition, the optical path of fluorescence little change until about 45°, which resulted in the fluorescence intensity is virtually flat until about 45°. In addition, the calculated values based on model are greater than the measured fluorescence values. The reason may be that hemispherical measurements were considered for the FluorMODleaf model, and the LIF-Lidar just take into account the single direction for each measurement.
Fig. 3 Effect of incidence angle on the fluorescence intensity. The fluorescence intensities of all plant species at different incidence angles with peak wavelengths of 685 and 740 nm were normalized to 1 at 0° to enable comparison between experimentally obtained fluorescence intensities and FluorMODleaf model results. (a): Fluorescence intensity at 685nm; (b): Fluorescence intensity at 740nm.
Thus, fluorescence intensity can be described as an expression of the excitation light incidence angle. In reference to Meroni et al. [23] and Kukko et al. [20], a corrected cosine expression was proposed to enable the analysis of the correlation between fluorescence intensity and the incidence angle. The variation in fluorescence intensity with incidence angle () can be written as:
Where a and b represent parameters related to the chlorophyll concentration. Equation (2) was then used to fit non-normalized experimental data which extracted from Fig. 2 [21]. The corrected cosine expression exhibited good performance in fitting the experimental fluorescence data of various samples at the fluorescence characteristics peaks 685 and 740 nm. As can be seen Fig. 4. In addition, the details of the fitting and statistics parameters of the six different plant species at 685 and 740 nm are listed in Table 1 and Table 2, respectively.
Fig. 4 The corrected cosine expression in Eq. (2) (solid lines) fitted to the experimental fluorescence data for different plant species at fluorescence characteristics peaks: (a) 685 nm; and (b) 740 nm.
Table 1. Parameters a, b and R2 of the model for targets at 685 nm
Table 2. Parameters a, b and R2 of the model for targets at 740 nm
Figure 4 as well as Table 1 and Table 2 reveal that Eq. (2) well describes the variation in fluorescence intensity with the variation in the incidence angle of excitation light. For the fitted spectrum of Salix babylonica, R2 reached a maximum value of 0.93 at 740 nm, and RMSE lower than 0.07. The different plant species exhibited different correlation levels by using corrected cosine expression. Takahashi et al. and Cerovic et al. [32,38] analyzed the distribution of scattered light and chlorophyll fluorescence in intact rice leaves, and point that the fluorescence concentration as well as the internal structure of leaf will influence on the fluorescence signals. And, the fluorescence maximum of different wavelengths is different in the depth of the inside of leaf. What’s more, the presence of densely packed palisade cells in the upper leaf side increases the reabsorption by chlorophyll a of the red fluorescence induced from this side [37]. In addition, the optical path of fluorescence is positive correlation with incidence angles. Thus, the process of reabsorption will be stronger with the increasing of incidence angle. The other fitting results also provided evidence for the good performance of the corrected cosine equation; specifically, all R2 values exceeded 0.83. These results demonstrated that Eq. (2) can facilitate correcting the effects of incidence angles on fluorescence intensities in the quantitative detection of vegetation through LIF-Lidar system. In our future works, more plant species should be added to improve the robustness of the model and to obtain a solid conclusion. In addition, we plan to extend the research on LIF-Lidar systems from the leaf to the canopy, which require sophisticated approaches.
4. Conclusion
The FluorMODleaf model and the experiment set were used to systematically investigate the effects of incidence angles on fluorescence intensities at the leaf scale based on LIF-Lidar. The numerical and experimental results suggest that the variation in fluorescence intensity with the incidence angle can be described as a corrected cosine expression. Fitting results with the proposed expression provided a maximum R2 value of 0.93 for Salix babylonica. Thus, the result can provide a reference for the study of fluorescence intensity calibration in LIF-Lidar systems. However, model parameters should be explored using more fluorescence intensity data with different vegetation varieties to improve the application of LIF-Lidars. The alternative fitting options may also need to be explored in the next work. In addition, future works will also be performed to extend the results of the present study to the canopy scale.
Funding
This research was funded by the National Key R&D Program of China (Grant No. 2018YFB0504500), the National Natural Science Foundation of China (Grant No. 41801268), the Natural Science Foundation of Hubei Province (Grant No. 2018CFB272), the Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University (Grant No. 17R05).
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