Leaf Inclination Angle Distribution Research Articles

BcBZR1 Regulates Leaf Inclination Angle in Non-Heading Chinese Cabbage (Brassica campestris ssp. chinensis Makino)

Brassinosteroids (BRs) play critical roles in plant growth by promoting cell elongation and division, leading to increased leaf inclination angles. BRASSINAZOLE RESISTANT 1 (BZR1) and BRI1-EMS-SUPPRESSOR 1 (BES1) act as transcription factors in the brassinosteroid signaling pathway and are involved in several physiological activities regulated by BRs. In this study, we identified and cloned BcBZR1 from the heitacai non-heading Chinese cabbage (NHCC) cultivar. The sequence analysis showed that the coding sequence length of BcBZR1 is 996 bp, encoding 331 amino acid residues. Subcellular localization assays showed that BcBZR1 is localized in the nucleus and cytoplasm and that BcBZR1 protein is transported to the nucleus after receiving BR signals. Compared with Col-0, the leaf inclination angle was smaller in BcBZR1-OX. The EBR treatment experiment indicated that BRs regulate the differential expression of paclobutrazol resistance1 (PRE1) and ILI1 binding bHLH1 (IBH1) in the adaxial and abaxial cells of the petiole through BZR1, thus regulating the leaf inclination angle. The bimolecular fluorescence complementation (BiFC) assay indicated that BcBZR1 interacts with C-repeat Binding Factor2 (BcCBF2) and CBF3. Taken together, our findings not only validate the function of BcBZR1 in leaf inclination angle distribution in non-heading Chinese cabbage, but also contribute to the mechanism of leaf inclination angle regulation in this species under cold stress.

Accurate solution of the SAIL model by leaf inclination angle calculation based on laser point clouds

ABSTRACT The canopy radiative transfer model enables quantitative inversion of vegetation biophysical parameters by rapidly simulating spectral information. However, structural input parameters, such as the leaf inclination angle distribution (LAD), are often set to empirical values in classic models, leading to simulation errors. Laser point cloud technology has developed rapidly in recent years, and the 3D structure of vegetation can be detailed using laser sensors and processing software, providing the necessary conditions for accurate solutions of radiative transfer models of the canopy. However, the mechanisms for improving existing models of canopy radiative transfer by introducing laser point clouds have not yet been theoretically analyzed in detail. In this study, a precise solution was proposed by incorporating the accurate LAD obtained from laser point clouds into the intermediate function of the traditional Scattering by Arbitrarily Inclined Leaves (SAIL) model, which is a widely used multiangle radiative transfer model. The calculation of the leaf inclination angle and the derivation of the improved model were detailed in this paper. Experiments from different observation angles and bands compared the similarity between the actual measured spectra and the simulated spectra for both the traditional SAIL model and the proposed model with accurate structural parameters. The overall similarity of the proposed model with respect to the conventional SAIL model was improved, indicating that introducing laser point clouds improved the simulation accuracy. The proposed model achieved more significant improvements in the blue 450 nm and red 670 nm bands. Moreover, the similarity improvements differed between different angles. Finally, we analyzed the sensitivity of the structural parameters of the SAIL model and the proposed model using local and global sensitivity analysis methods.

Canopy structural changes explain reductions in canopy-level solar induced chlorophyll fluorescence in Prunus yedoensis seedlings under a drought stress condition

Drought events have a major impact on vegetation structure and function. Recently, solar-induced chlorophyll fluorescence (SIF) has been widely used to understand the photosynthesis rates of vegetation under drought stress conditions. However, it is still unclear whether the reduction in SIF shown under drought stress conditions is regulated by physiological or structural factors. To understand the underlying reduction mechanism of SIF under drought stress, we conducted an experiment under a drought condition using one-year-old Prunus yedoensis seedlings. We compared the experiment trees with control trees that were not exposed to drought stress. We collected spectral and gas exchange data to monitor physiological changes and scanned the trees with a terrestrial laser scanner to monitor the structural changes. The discrete anisotropic radiative transfer (DART) and Fluspect models were used to simulate canopy-level SIF. We found that drought stress caused leaf-level steady-state fluorescence yield to increase, while maximum photosynthetic rate, stomatal conductance, and the quantum yield of Photosystem II decreased significantly. Regarding the canopy structural changes, the leaf inclination angle distribution of the experiment trees gradually turned toward erectophile over time (55.2 ± 9.3° to 74.7 ± 6.0°; mean ± standard deviation), whereas that of the control trees remained relatively constant (52.9 ± 8.8°). Furthermore, reduction of crown cover of the experiment trees was 3-fold (77.4 ± 9.8%) compared with the control trees (26.0 ± 16.2%). The simulated nadir-view canopy-level SIF of the experiment trees was reduced 2.8-fold compared to the control trees. These findings, obtained specifically from Prunus yedoensis seedlings, indicate that canopy-level SIF reduced due to the canopy structural changes, although leaf-level fluorescence yield increased. Therefore, canopy structural changes should be considered when attempting to understand SIF reduction in drought conditions.

Potential of Satellite Spectral Resolution Vegetation Indices for Estimation of Canopy Chlorophyll Content of Field Crops: Mitigating Effects of Leaf Angle Distribution

Accurate estimation of canopy chlorophyll content (CCC) is critically important for agricultural production management. However, vegetation indices derived from canopy reflectance are influenced by canopy structure, which limits their application across species and seasonality. For horizontally homogenous canopies such as field crops, LAI and leaf inclination angle distribution or leaf mean tilt angle (MTA) are two biophysical characteristics determining canopy structure. Since CCC is relevant to LAI, MTA is the only structural parameter affecting the correlation between CCC and vegetation indices. To date, there are few vegetation indices designed to minimize MTA effects for CCC estimation. Herein, in this study, CCC-sensitive and MTA-insensitive satellite broadband vegetation indices are developed for crop canopy chlorophyll content estimation. The most efficient broadband vegetation indices for four satellite sensors (Sentinel-2, RapidEye, WorldView-2 and GaoFen-6) with red edge channels were identified (in the context of various vegetation index types) using simulated satellite broadband reflectance based on field measurements and validated with PROSAIL model simulations. The results indicate that developed vegetation indices present strong correlations with CCC and weak correlations with MTA, with overall R2 of 0.76–0.80 and 0.84–0.95 for CCC and R2 of 0.00 and 0.00–0.04 in the field measured data and model simulations, respectively. The best vegetation indices identified in this study are the soil-adjusted index type index SAI (B6, B7) for Sentinel-2, Verrelts’s three-band spectral index type index BSI-V (NIR1, Red, Red Edge) for WorldView-2, Tian’s three-band spectral index type index BSI-T (Red Edge, Green, NIR) for RapidEye and difference index type index DI (B6, B4) for GaoFen-6. The identified indices can potentially be used for crop CCC estimation across species and seasonality. However, real satellite datasets and more crop species need to be tested in further studies.

STMRT: A simple tree canopy radiative transfer model for outdoor mean radiant temperature

Tree canopy shading can significantly decrease the outdoor mean radiant temperature (MRT). However, canopy radiative transfer is quite complex, making it challenging to evaluate the MRT under a tree canopy. In this study, a simple tree canopy radiative transfer model (STMRT) was developed to determine the MRT under a tree canopy. In STMRT, the direct and diffuse solar radiation transfers are calculated based on the leaf inclination angle distribution, and the longwave radiation emitted from a canopy is evaluated based on the simplification that the canopy surface temperature is the same as the surrounding air temperature. The STMRT's accuracy was evaluated by measurement and compared to that of 4SAIL. The results demonstrate that the MRT differences (ΔMRT) in STMRT are typically less than 2.3 °C; in Shanghai, China, ΔMRT caused by the differences in direct solar radiation transmissivity between STMRT and 4SAIL are less than 2.0 °C, unless the leaf area index is less than 2 and the solar zenith angle is greater than 70°. According to STMRT, it is found that ΔMRT generated by the leaf inclination angle variances across various tree species can reach 9.5 °C; ΔMRT caused by a uniform distribution simplification for leaf inclination angle can reach 5.7 °C. STMRT will help plan the outdoor thermal environment by evaluating the MRT under tree canopies.

On the leaf inclination angle distribution as a plant trait for the most abundant broadleaf tree species in Europe

Leaf angle distribution influences forest canopy processes like radiation balance, photosynthesis, and evapotranspiration. Indeed, a strong sensitivity to variability in the leaf angle distribution is reported for many models. Difficulties in conducting leaf angle distribution measurements limit data availability and explanations of its species-specific phenology and variation across environmental gradients. This leads to the situation that leaf angle distribution is often the most poorly constrained model parameter. Here, we report a spatial survey of leaf angle distributions and their seasonal and vertical changes for five most abundant forest broadleaf tree species in Europe according to the spatially representative Level I ICP Forests monitoring network. Although we found evidence that leaf angle distribution might be considered a species-specific trait for all studied species except Betula pendula, we advocate the use of leaf angle distributions obtained from actual leaf inclination measurements whenever possible. Data on leaf angle distributions for 50 widespread forest broadleaf tree species in Europe is also reported.

The Role of Spatial Averaging Scale in Leaf‐To‐Canopy Scaling of Non‐Linear Processes in Homogeneous Canopies

AbstractIn formulating canopy biophysical models of non‐linear processes like photosynthesis and stomatal conductance, it is necessary to average inputs over some representative spatial scale (sub‐leaf, leaf, sub‐crown, crown, whole‐canopy, etc.). The consequences of the choice of averaging scale is often unclear due to the inability of experiments to robustly quantify fluxes across the full range of relevant length scales. This study quantified errors in canopy‐level flux simulations due to input radiative flux averaging scale choice using a detailed leaf‐resolving biophysical model that represents three‐dimensional canopy geometry at the sub‐leaf level. Simulations were performed for an array of homogeneous canopies differing in leaf area index (LAI), canopy height, leaf inclination angle distribution, leaf size, leaf shape, and the size of leaf sub‐sections relative to total leaf size. Canopy fluxes based on a sub‐leaf averaging scale were compared with fluxes derived from averaging over single leaves, averaging sunlit and shaded portions of leaf area separately (i.e., two‐leaf model), and averaging multiple vertical layers and leaf angle classes separately (i.e., multi‐layer model). Canopy‐level fluxes were found to be influenced by the chosen averaging scale and other variables tested, especially LAI. Averaging approaches inherent in the two‐leaf and multi‐layer models currently used in most canopy models resulted in low or moderate over‐estimates of canopy‐level fluxes under many conditions tested. Surprisingly, averaging over entire leaves (i.e., leaf‐resolving model) had the potential to create the largest errors. This result underscored the need to sub‐divide leaves in leaf‐resolving models.

Influence of the canopy structure of a birch forest on the visibility of the fires below

The work is aimed at studying the visibility of a flame through the canopy of a birch forest, depending on the structure of the latter, and providing support for decision-making on the choice of the optimal sensing geometry for solving the problem of detecting fires in birch forests when video shooting from low altitudes. For the site located in the Priozersk district of the Leningrad region, using photographic technology, data were obtained on the frequency distribution of birch leaf inclination angles (for a hybrid of two species). The information is compared with the results of the work of other researchers. On the basis of the collected data, three-dimensional models of the canopy of various structures were constructed, suitable for simulating the radiation transfer. A set of experiments has been carried out to estimate the values of the fraction of beam penetration for light emitted by the combustion center in the direction of the sensor at different viewing angles. For individual ratios of crown sizes and distances between them, the least informative ranges of viewing angles, which should be avoided when monitoring fires, have been determined. It has been confirmed that the visibility of the flame depends on the shape and closeness of the crowns, which determine the length of the radiation path in the vegetation layer, and, to a lesser extent, on the prevailing orientation of the leaves.

Quantitative Evaluation of Leaf Inclination Angle Distribution on Leaf Area Index Retrieval of Coniferous Canopies

Both leaf inclination angle distribution (LAD) and leaf area index (LAI) dominate optical remote sensing signals. The G-function, which is a function of LAD and remote sensing geometry, is often set to 0.5 in the LAI retrieval of coniferous canopies even though this assumption is only valid for spherical LAD. Large uncertainties are thus introduced. However, because numerous tiny leaves grow on conifers, it is nearly impossible to quantitatively evaluate such uncertainties in LAI retrieval. In this study, we proposed a method to characterize the possible change of G-function of coniferous canopies as well as its effect on LAI retrieval. Specifically, a Multi-Directional Imager (MDI) was developed to capture stereo images of the branches, and the needles were reconstructed. The accuracy of the inclination angles calculated from the reconstructed needles was high. Moreover, we analyzed whether a spherical distribution is a valid assumption for coniferous canopies by calculating the possible range of the G-function from the measured LADs of branches of Larch and Spruce and the true G-functions of other species from some existing inventory data and three-dimensional (3D) tree models. Results show that the constant G assumption introduces large errors in LAI retrieval, which could be as large as 53% in the zenithal viewing direction used by spaceborne LiDAR. As a result, accurate LAD estimation is recommended. In the absence of such data, our results show that a viewing zenith angle between 45 and 65 degrees is a good choice, at which the errors of LAI retrieval caused by the spherical assumption will be less than 10% for coniferous canopies.

Leaf inclination angle and foliage clumping in an evergreen broadleaf

How leaves are presented affects interaction of atmospheric CO2, energy (light), and plant physiology. Plant productivity is primarily determined by the amount of leaf area, leaf orientation and distribution in space. Not much attention has been paid to possible changes in leaf orientation and distribution with elevated CO2, but its effect on plant growth could alter the proportions of sunlit and shaded leaf areas and feedback on carbohydrate available for further growth. We report on first measurements of leaf inclination angle distribution and foliage clumping in a native evergreen Eucalyptus woodland in ambient CO2 and under +150 ppm elevated CO2. We found that a spherical leaf angle distribution was not an appropriate supposition for present species (Eucalyptus tereticornis Sm.) at this site. Our measurements of leaf inclination angles from imagery indicated an erectophile, highly skewed unimodal leaf inclination angle distribution function. We conclude that despite the measured steeper angles under elevated CO2 concentrations, the leaf angle change is not significant and falls within the expected natural variability and uncertainties connected with the measurement method. The lack of a clear response of leaf orientation and foliage clumping to elevated CO2 concentration indicates that the previously produced datasets of leaf inclination angles and foliage clumping maps with Earth observation data may be suitable while modelling carbon and water cycles under climate change.

Estimating Needle and Shoot Inclination Angle Distributions and Projection Functions in Five Larix principis-rupprechtii Plots via Leveled Digital Camera Photography

The leaf inclination angle distribution function is a key determinant that influences radiation penetration through forest canopies. In this study, the needle and shoot inclination angle distributions of five contrasting Larix principis-rupprechtii plots were obtained via the frequently used leveled digital camera photography method. We also developed a quasi-automatic method to derive the needle inclination angles based on photographs obtained using the leveled digital camera photography method and further verified using manual measurements. Then, the variations of shoot and needle inclination angle distributions due to height levels, plots, and observation years were investigated. The results showed that the developed quasi-automatic method is effective in deriving needle inclination angles. The shoot and needle inclination angle distributions at the whole-canopy scale tended to be planophile and exhibited minor variations with plots and observation years. The small variations in the needle inclination angle distributions with height level in the five plots might be caused by contrasting light conditions at different height levels. The whole-canopy and height level needle projection functions also tended to be planophile, and minor needle projection function variations with plots and observation years were observed. We attempted to derive the shoot projection functions of the five plots by using a simple and applicable method and further evaluated the performance of the new method.

Modeling Microwave Emission of Corn Crop Considering Leaf Shape and Orientation Under the Physical Optics Approximation

The objective of this article is a systematic investigation of the sensitivity of C- and X-band emissions to leaf shape and orientation for various growth stages of corn. To simulate these effects, we used the model developed at Tor Vergata University (TOV model), which is based on a matrix doubling algorithm considering multiple scattering. Corn leaves have specific properties of shape, curvature, and orientation. We have compared different approaches, including segmented elliptical disk oriented following leaf curvature, unique elliptical disk per leaf, and segmented circular disk with size determined by the shorter leaf dimension and following the leaf curvature. Moreover, widespread leaf inclination angle distribution functions combined with in situ measurements of leaf inclination angle are adopted. The scatterers' phase matrix calculations are based on the physical optics approximation. Simulations are conducted with the ground-measured soil and vegetation properties as inputs and evaluated against the corresponding ground-based, multifrequency radiometer observations carried out in four different years over Chinese sites. The investigations show that in most cases the segmented circular disk assumption shows the best correspondence to the measurements over intermediate growth stages when the vegetation heights lie between 50 and 200 cm, and the unique elliptical disk model achieves the best correspondence for the later growth stages when the vegetation heights are larger than 200 cm with prefer-erectophile distribution of leaf orientation. The use of in situ leaf inclination angle measurements can improve the model accuracy by up to 25 K for tall vegetation heights compared with random distribution assumption.

Dynamic Simulation on Canopy Light Distribution and Dry Matter Accumulation of Natural Colored Cotton in Alar Reclamation Area of Xinjiang

Based on Ross’s theory of optical radiation transmission and full consideration of influences of vertical distribution of canopy leaf area and leaf inclination angle distribution of colored cotton on the light distribution, the Gaussian 5-point distance was used to divide the canopy into 5 layers on basis of the leaf area index. The leaf inclination angle on each layer was divided into 6 equal parts by 15°. The types of radiation in canopy, spatial distribution of light radiation, as well as diurnal variation with solar hour angles were quantified in detail. After comprehensively considering influences of temperature, physiological age and other factors on photosynthesis and respiration, the canopy light distribution, photosynthetic production and dry matter accumulation of colored cotton were simulated with strong mechanistic and physiological & ecological significance. The colored cotton samples sown on April 16, 2019 were used to verify the model. The RMSEs of simulated and measured canopy PAR values at Beijing time 10:00, 12:00, 14:00 and 16:00 on July 30 were 58.2, 64.1, 43.4 and 39.7 µmol•m-2•s-1, respectively. The RMSE of simulated and observed values of the dry matter accumulation above ground was 412.6 kgDM•hm-2, reflecting the good predictability of the model.

Light absorption, light use efficiency and productivity of 16 contrasted genotypes of several Eucalyptus species along a 6-year rotation in Brazil

Stemwood productivity in forest ecosystems depends on the amount of light absorbed by the trees (APAR) and on the Light Use Efficiency (LUE), i.e. the amount of stemwood produced per amount of absorbed light. In fertilized Eucalyptus plantations of Brazil, growth is expected to be strongly limited by light absorption in the first years after planting, when trees can benefit from high soil water stocks, recharged after clearcutting the previous stand. Other limiting factors, such as water or nutrient shortage are thought to increase in importance after canopy closure, and changes in allocation patterns are expected, affecting the LUE.Studying changes in APAR and LUE along a complete rotation is paramount for gaining insight into the mechanisms that drive the inter- and intra-genotype variabilities of productivity and stemwood biomass at the time of harvest. Here, we present a 6-year survey of productivity, APAR and LUE of 16 Eucalyptus genotypes of several species used in commercial plantations and planted in 10 randomized replications in the São Paulo Region, Brazil. APAR was estimated using the MAESTRA tridimensional model parameterized at tree scale for each tree in each plot (a total of 16,000 trees) using local measurements of leaf and canopy properties. Stand growth was estimated based on allometric relationships established through successive destructive biomass measurements at the study site.Allometric relationships predicting biomass of tree components, leaf surface, crown dimension and leaf inclination angle distribution throughout the rotation for the 16 productive genotypes are shown. Results at stand scale showed that (1) LUE increased with stand age for all genotypes, from 0.15 at age 1 yr to 1.70 g MJ−1 at age 6 yrs on average; (2) light absorption was a major limiting factor over the first year of growth (R2 between APAR and stand biomass ranging from 0.5 to 0.95), explaining most of the inter- and intra-genotype growth variability; (3) at rotation scale, the variability of final stemwood biomass among genotypes was in general attributable to other factors than average APAR; (4) differences in stemwood productions among genotypes remained large throughout the rotation; (5) LUEs over the second half of the rotation, rather than initial growth or APAR, was the major driver of stemwood biomass at the time of harvest.

Estimation of Leaf Inclination Angle in Three-Dimensional Plant Images Obtained from Lidar

The leaf inclination angle is a fundamental variable for determining the plant profile. In this study, the leaf inclination angle was estimated automatically from voxel-based three-dimensional (3D) images obtained from lidar (light detection and ranging). The distribution of the leaf inclination angle within a tree was then calculated. The 3D images were first converted into voxel coordinates. Then, a plane was fitted to some voxels surrounding the point (voxel) of interest. The inclination angle and azimuth angle were obtained from the normal. The measured leaf inclination angle and its actual value were correlated and indicated a high correlation (R2 = 0.95). The absolute error of the leaf inclination angle estimation was 2.5°. Furthermore, the leaf inclination angle can be estimated even when the distance between the lidar and leaves is about 20 m. This suggests that the inclination angle estimation of leaves in a top part is reliable. Then, the leaf inclination angle distribution within a tree was calculated. The difference in the leaf inclination angle distribution between different parts within a tree was observed, and a detailed tree structural analysis was conducted. We found that this method enables accurate and efficient leaf inclination angle distribution.

Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest

Leaf inclination angle and leaf angle distribution (LAD) are important plant structural traits, influencing the flux of radiation, carbon and water. Although leaf angle distribution may vary spatially and temporally, its variation is often neglected in ecological models, due to difficulty in quantification.In this study, terrestrial LiDAR (TLS) was used to quantify the LAD variation in natural European beech (Fagus Sylvatica) forests. After extracting leaf points and reconstructing leaf surface, leaf inclination angle was calculated automatically. The mapping accuracy when discriminating between leaves and woody material was very high across all beech stands (overall accuracy = 87.59%). The calculation accuracy of leaf angles was evaluated using simulated point cloud and proved accurate generally (R2 = 0.88, p < 0.001; RMSE = 8.37°; nRMSE = 0.16). Then the mean (θmean), mode (θmode), and skewness of LAD were calculated to quantify LAD variation.Moderate variation of LAD was found in different successional status stands (θmean∈ [36.91°, 46.14°], θmode∈ [17°, 43°], skewness ∈ [0.07, 0.48]). Rather than the previously assumed spherical distribution or reported planophile distribution, here we find that LAD tended towards a uniform distribution in young and medium stands, and a planophile distribution in mature stands. A strong negative correlation was also found between plot θmean and plot median canopy height, making it possible to estimate plot specific LAD from canopy height data.Larger variation of LAD was found on different canopy layers (θmean∈ [33.64°, 52.97°], θmode∈ [14°, 64°], skewness ∈ [−0.30, 0.71]). Beech leaves grow more vertically in the top layer, while more obliquely or horizontally in the middle and bottom layer.LAD variation quantified by TLS can be used to improve leaf area index mapping and canopy photosynthesis modelling.

Morphological acclimation to agronomic manipulation in leaf dispersion and orientation to promote “Ideotype” breeding: Evidence from 3D visual modeling of “super” rice (Oryza sativa L.)

Food security is confronted by major threats from crop yield stagnation and global climate change. The benefits of phenotypic plasticity across environments for given crop genotypes are thought to be imperative for high-yielding cropping systems. Given that 3D modeling is increasingly recognized for dissecting crop phenotypic plasticity, it requires an assessment of the potential benefits of architectural adaptation of super rice to different agronomic practices. In this study, we focused on a comprehensive evaluation of the phenotypic plasticity of super rice on the aspects of 3D architectural “reoptimization,” photosynthetic productivity, nitrogen economy, and grain yield. A super rice phenotype in superhigh-yielding practice (SH) displays a “reoptimized” morphogenesis in the leaf vertical dispersion and orientation in comparison to that in Farmer's practice (FP). Specifically, a super rice phenotype in SH is provided with a high cumulative rate and peaks of leaf area, increasing the distribution of high leaf inclination angles in comparison to that in FP, particularly in the upper parts of the canopy. These “reoptimizations” sustained profits in light environment within a canopy, leaf area duration, photosynthetic light harvest, and light utilization efficiency and were coordinated with improving nitrogen uptake and assimilation. The current literature indicates that the agronomic plasticity of super rice in architectural “reoptimization” is a promising perspective for high yield formation. Our results suggest that more emphasis should be placed upon agronomic adaptation strategies for super rice across diverse genotypes and environments to further improve crop establishment and photosynthetic productivity.

Retrieving 2-D Leaf Angle Distributions for Deciduous Trees From Terrestrial Laser Scanner Data

Terrestrial laser scanning is a promising tool for estimating leaf angle (including leaf inclination and azimuthal angles) distribution (LAD). However, previous studies focus on the retrieval of leaf inclination angle distribution, very few studies have considered the distribution of leaf azimuthal angle due to the restriction of measurement techniques. In this paper, we developed a new method to obtain more accurate leaf inclination and azimuthal angle estimations based on leaf point cloud segmentation and filtration and then fit LAD functions using two-parameter Beta-distribution model. In addition, we constructed a new projection coefficient model with two parameters $G(\theta $ , $\varphi$ ) using Nilson’s algorithm based on the accurate retrieval of LAD. To assess the influence of leaf numbers on leaf inclination and azimuthal angle estimations, we modeled 160 individual leaves and 10 trees with different leaf numbers. In addition, to validate the final results, we also sampled three magnolia trees with different leaf numbers and manually measured leaf inclination and azimuthal angles of all their leaves using an angle measurement device. All results showed that the method proposed in this paper can provide accurate leaf inclination and azimuthal angles (leaf inclination angle: $R^{2} = 0.98$ , RMSE = 24° and leaf azimuthal angle: $R^{2} = 0.99$ , RMSE = 3.44°). The simulated LAD and $G(\theta $ , $\varphi$ ) estimations based on these leaf inclination and azimuthal angles were strongly correlated with those obtained from ground truth measurements ( $P >0.05$ ).

Sensitivity of Common Vegetation Indices to the Canopy Structure of Field Crops

Leaf inclination angle distribution is an important canopy structure characteristic which directly impacts the fraction of the intercepted solar radiation. Together with the leaf area index (LAI) it determines the structure and fractional cover of a homogeneous crop canopy. Unfortunately, this key canopy parameter has usually been ignored when applying common multispectral vegetation indices to the mapping of LAI, although its impact is known from model simulations. Therefore, we measured leaf angles and determined their distribution (quantified using the leaf mean tilt angle, MTA) for six crop species with different structures growing on 162 plots with a broad range of LAI (1.1–5.0) and leaf chlorophyll content (26–94 μg cm−2). Next, we calculated six vegetation indices widely used for LAI monitoring—the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the two band enhanced vegetation index (EVI2), the modified triangular vegetation index (MTVI2), the optimized soil adjusted vegetation index (OSAVI) and the wide dynamic range vegetation index (WDRVI)—from airborne imaging spectroscopy data. We calculated the Spearman’s correlation coefficient R s , a non-parametric statistic chosen because of the non-normal distribution of canopy parameters. All studied indices depended on the LAI ( 0.50 ≤ R s ≤ 0.71 ) , but the dependence on the MTA was of similar magnitude ( − 0.83 ≤ R s ≤ − 0.53 ) with EVI, EVI2, OSAVI and MTVI2 depending more strongly on MTA than on LAI. All studied indices were good proxies ( 0.78 ≤ R s ≤ 0.88 ) for vegetation fractional cover (Fcover) which, for homogeneous crop canopies, is a nonlinear function of LAI and MTA. EVI2 and MTVI2 were the most strongly correlated with Fcover, although the difference to the other studied indices was small. This first study involving a large range of crop structures confirms the results from canopy reflectance simulations and emphasizes the necessity of leaf angle information for the successful mapping of LAI with Earth observation data.

Variations of leaf inclination angle distribution with height over the growing season and light exposure for eight broadleaf tree species

Leaf inclination angles are of critical importance in determining the transmission of radiation by vegetation canopies. In this short communication we address the seasonal and vertical changes in leaf inclination angles for eight deciduous broadleaf tree species common to temperate and hemiboreal ecoclimatic regions. The greatest changes in leaf inclination angles are observed in spring at the top of the canopy. Tree species with more vertical leaf inclination angles are more sensitive to light exposure than tree species with more horizontal inclination angles. We also test the sensitivity to user subjectivity of the leveled digital camera method for measuring leaf inclination angles and show that the method provides comparable results irrespective of the user.