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Leaf area index (LAI) is a key parameter of vegetation structure in the fields of agriculture, forestry, and ecology. Optical indirect methods based on the Beer-Lambert law are widely adopted in numerous fields given their high efficiency and feasibility for LAI estimation. These methods have undergone considerable progress in the past decades, thereby making them operational in ground-based LAI measurement and even in airborne estimation. However, several challenges remain, given the requirement of increasing accuracy and new applications. Clumping effect correction attained significant progress for continuous canopies with non-randomly disturbed leaves while non-continuous canopies are rarely studied. Convenient and operational measurement of leaf angle distribution and woody components is lacked. Accurate and comprehensive validations are still very difficult due to the limitations of direct measurement. The introduction of active laser scanning technology is a driving force for addressing several challenges, but its three-dimensional information has not been fully explored and utilized. In order to update the general knowledge and identify the possible error source, this study comprehensively reviews the temporal development, theoretical framework, and issues of indirect LAI measurement, followed by current methods, instruments, and platforms. Latest methods and instruments are introduced and compared to traditional ones. Current challenges, recent advances, and future perspectives are discussed to provide recommendations for further research.

Satellite data are continuously used to monitor albedo and fraction of absorbed photosynthetically active radiation (FAPAR), which are key components in determining the energy balance and productivity of forests. However, due to the mismatch between spatial resolution of the satellite data and forest stand size, coarse resolution satellite products cannot capture the fine-scale variations in forest structure. Therefore, forest radiation budget models are important tools in quantifying albedo and FAPAR at stand scale. However, due to the lack of suitable input data, simulations are often restricted to summer conditions only and the seasonal patterns are not considered. We modeled the time series of albedo and FAPAR for an entire growing season for 20 forest plots in the boreal zone in Finland (61°50′ N, 24°17′ E) using an exceptional ground reference data set. Canopy gap fractions and the spectra of forest floor were monitored in the plots throughout the growing season. Data on the seasonality of spectra of tree foliage were also available. The modeled albedo and FAPAR were upscaled and compared against albedo and FAPAR derived from MODIS satellite data. We showed that forest radiation budget models capable of adequately taking into account foliage clumping and its effects on multiple scattering are the most appropriate for simulating albedo of boreal coniferous forests. Our results also indicated negative albedo-productivity relations in boreal coniferous forests. In addition, we demonstrated that not only the overall level, but also the seasonal patterns of albedo and FAPAR differ between tree species. Therefore, the use of only peak growing season albedo or FAPAR values when estimating climate impacts of forest management can be misleading.

Leaf area index (LAI) is an important parameter controlling many biological and physiological processes associated with vegetation on the Earth's surface, such as photosynthesis, respiration, transpiration, carbon and nutrient cycle and rainfall interception. LAI can be measured indirectly by sunfleck ceptometers in an easy and non-destructive way but this practical methodology tends to underestimated when measured by these instruments. Trying to correct this underestimation, some previous studies heave proposed the multiplication of the observed LAI value by a constant correction factor. The assumption of this work is LAI obtained from the allometric equations are not so problematic and can be used as a reference LAI to develop a new methodology to correct the ceptometer one. This new methodology indicates that the bias (the difference between the ceptometer and the reference LAI) is estimated as a function of the basal area per unit ground area and that bias is summed to the measured value. This study has proved that while the measured Pinus LAI needs a correction, there is no need for that correction for the Eucalyptus LAI. However, even for this last specie the proposed methodology gives closer estimations to the real LAI values. RESUMO O índice de área foliar (IAF) é um parâmetro importante que controla muitos processos biológicos e fisiológicos associados à vegetação, entre as quais a fotossíntese, a respiração, a transpiração e o ciclo do carbono. O IAF pode ser medido indiretamente, de uma maneira fácil e não destrutiva, como pelo uso de ceptometros sunfleck. Contudo, esta metodologia, apesar de prática, tende a subestimar o IAF em grande parte devido à forma como as folhas se organizam nas copas, em especial o agrupamento das acículas em coníferas. Na tentativa de corrigir esta deficiência, propõe-se a multiplicação do valor de IAF medido por um fator de correção constante. Em contrapartida, assume-se que o IAF obtido a partir das equações alométricas não é tão problemático e pode ser usado como uma referência para estimar o IAF e desenvolver uma nova metodologia para corrigir as médias obtidas pelo ceptometro. Esta nova metodologia assume que o erro (a diferença entre o IAF do ceptometro e o IAF de referência) é estimado como uma função da área basal por hectare. O erro obtido deve então ser somado ao IAF do ceptometro, para se obter um valor corrigido. Este estudo mostrou ainda que, embora o IAF da Pinus necessite da aplicação desta correção, não há necessidade de aplicar no casa do IAF para a Eucalyptus. No entanto, mesmo para esta última espécie a metodologia proposta dá estimativas mais próximas dos valores reais de IAF.

Background and Aims Proper characterization of the clumped structure of forests is needed for calculation of the absorbed radiation and photosynthetic production by a canopy. This study examined the dependency of crown-level clumping on tree size and growth conditions in Scots pine (Pinus sylvestris), and determined the ability of statistical canopy radiation models to quantify the degree of self-shading within crowns as a result of the clumping effect. Methods Twelve 3-D Scots pine trees were generated using an application of the LIGNUM model, and the crown-level clumping as quantified by the crown silhouette to total needle area ratio (STARcrown) was calculated. The results were compared with those produced by the stochastic approach of modelling tree crowns as geometric shapes filled with a random medium. Key Results Crown clumping was independent of tree height, needle area and growth conditions. The results supported the capability of the stochastic approach in characterizing clumping in crowns given that the outer shell of the tree crown is well represented. Conclusions Variation in the whole-stand clumping index is induced by differences in the spatial pattern of trees as a function of, for example, stand age rather than by changes in the degree of self-shading within individual crowns as they grow bigger.

Airborne lidar point clouds of vegetation capture the 3-D distribution of its scattering elements, including leaves, branches, and ground features. Assessing the contribution from vegetation to the lidar point clouds requires an understanding of the physical interactions between the emitted laser pulses and their targets. Most of the current methods to estimate the gap probability ( P gap ) or leaf area index (LAI) from small-footprint airborne laser scan (ALS) point clouds rely on either point-number-based (PNB) or intensity-based (IB) approaches, with additional empirical correlations with field measurements. However, site-specific parameterizations can limit the application of certain methods to other landscapes. The universality evaluation of these methods requires a physically based radiative transfer model that accounts for various lidar instrument specifications and environmental conditions. We conducted an extensive study to compare these approaches for various 3-D forest scenes using a point-cloud simulator developed for the latest version of the discrete anisotropic radiative transfer (DART) model. We investigated a range of variables for possible lidar point intensity, including radiometric quantities derived from Gaussian Decomposition (GD), such as the peak amplitude, standard deviation, integral of Gaussian profiles, and reflectance. The results disclosed that the PNB methods fail to capture the exact P gap as footprint size increases. By contrast, we verified that physical methods using lidar point intensity defined by either the distance-weighted integral of Gaussian profiles or reflectance can estimate P gap and LAI with higher accuracy and reliability. Additionally, the removal of certain additional empirical correlation coefficients is feasible. Routine use of small-footprint point-cloud radiometric measures to estimate P gap and the LAI potentially confirms a departure from previous empirical studies, but this depends on additional parameters from lidar instrument vendors.

The angular profiles of canopy gap fraction curves are influenced by canopy structure, and are commonly expected to vary with stand- and crown-level variables such as tree pattern, crown shape and leaf orientation. In this study, measurements of canopy structure, gap fractions and effective LAI in 986 plots of Scots pine, Norway spruce and Silver birch stands in Finland were used to assess how similar the angular canopy gap fraction profiles are for common boreal tree species. The profiles were characterized with help of the shape function ψ ( θ ), defined as the normalized value of the canopy light extinction coefficient at zenith angle ( θ ). Variation in ψ ( θ ) would be induced not only by a non-spherical leaf orientation, but also by differences in the directional clumping indices, such as could result from species-specific differences in crown shape. Our results showed that there is wide variation in the shape of ψ in the individual plots of the three different species. The species-specific mean curves ψ ( θ ), however, showed relatively small variation with θ , except for a sudden drop at large zenith angles, and the shape of the curves was similar for the different tree species. Results indicate that differences in crown shape of the study species do not significantly affect the angular profiles of canopy gap fraction.

International audience; Sun-shade models proved to be simple, fast and reliable tools for estimating the fraction of absorbed PAR (fAPAR) and the photosynthesis of low and simple canopies (e.g. wheat). Applications on tall canopies, or non-ideal canopies (e.g. row-planting, azimuthal heterogeneity, clumping, non-spherical leaf angle distribution, large proportion of non-green elements) were limited so far. We attempted to apply the Sun-shade model proposed by de Pury and Farquhar [de Pury, D.G.G., Farquhar, G.D., 1997. Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models. Plant Cell Environ. 20, 537–557] at the scale of the non-ideal canopy of adult coconut palms. The gap fractions of the whole cover, fraction of intercepted PAR (fIPAR), clumping index and leaf orientation derived from LAI-2000 (PCA) were closely matching the simulations of a reference 3D architectural model (3DM) used for cross-validation. Moreover, 3DM supplied a relationship for down-scaling the gap-fractions from the whole cover to green elements of the canopy. The derived Sun-shade simulations of fAPAR by green leaves agreed within 5% with 3DM, on a half-hourly time-step and for 1 year, confirming combined PCA and Sun-shade methods as a fast and reliable tool, even for tall or complex canopies. fIPAR and plant area index (PAI) were compared with the coconut literature and an empirical model was proposed for estimating fIPAR from age and planting density. The coefficient of extinction, K, was adjusted to 0.33 for the regular range of planting density.

Inverting radiative transfer (R-T) models against remote sensing observations to retrieve key biogeophysical parameters such as leaf area index (LAI) is a common approach. Even if new inversion techniques allow the use of three-dimensional (3D) models for that purpose, onedimensional (1D) models are still widely used because of their ease of implementation and computational efficiency. Nevertheless, they assume a random distribution of foliage elements whereas most canopies show a clumped organization. Due to that crude simplification in the representation of the canopy structure, sizeable discrepancies can occur between 1D simulations and real canopy reflectance, which may further lead to false LAI values. The present investigation aims to appraise to which extent the incorporation of a clumping index (noted l) into 1D R-T model could improve the simulations of Bidirectional Reflectance Distribution Function (BRDF). Canopy BRDF is simulated here for three growth stages of a maize crop with the Discrete Anisotropic Radiative Transfer (DART) model in the visible and near infrared spectral bands, for two contrasted soil types (dark and bright) and different levels of heterogeneity to represent the canopy structure. 3D numerical scenes are based on in-situ structural measurements and associated BRDF simulations are thus considered as references. 1D scenarios assume either that leaves are randomly distributed (l = 1) or clumped (l < 1). If BRDF simulations seem globally reliable under the assumption of a random distribution in near infrared, it can also lead to relative errors on the total BRDF up to 30% in the red spectral band. It comes out that the use of a clumping index in a 1D reflectance model generally improves BRDF simulations in the red considering a bright soil, which seems relatively independent of LAI. In the near infrared, best results are usually obtained with homogeneous canopies, except with the dark soil. Clearly, influent factors are mainly the LAI and the spectral contrast between soil and leaves.

* Simple models of light interception are useful to identify the key structural parameters involved in light capture. We developed such models for isolated trees and tested them with virtual experiments. Light interception was decomposed into the projection of the crown envelope and the crown porosity. The latter was related to tree structure parameters. * Virtual experiments were conducted with three-dimensional (3-D) digitized apple trees grown in Lebanon and Switzerland, with different cultivars and training. The digitized trees allowed actual values of canopy structure (total leaf area, crown volume, foliage inclination angle, variance of leaf area density) and light interception properties (projected leaf area, silhouette to total area ratio, porosity, dispersion parameters) to be computed, and relationships between structure and interception variables to be derived. * The projected envelope area was related to crown volume with a power function of exponent 2/3. Crown porosity was a negative exponential function of mean optical density, that is, the ratio between total leaf area and the projected envelope area. The leaf dispersion parameter was a negative linear function of the relative variance of leaf area density in the crown volume. * The resulting models were expressed as two single equations. After calibration, model outputs were very close to values computed from the 3-D digitized databases.