Search

The year-to-year variability of the blooming phenology of cherry trees is important as a proxy climate indicator and strongly affects cultural ecosystem services. Observation of blooming phenology at multiple points requires a simple and flexible approach. We examined changes in the canopy gap fraction extracted from binarized upward images taken periodically beneath a Cerasus × yedoensis ‘Somei-yoshino’ tree. The gap fraction decreased rapidly after the start of bloom, reached a minimum value at full bloom, and began to increase again, but then decreased rapidly during leaf flush. These changes reflect the phenology of blooming and leaf flush after flower drop of ‘Somei-yoshino’. These characteristics allow detection of the year-to-year variability of the bloom and leaf-flush phenology of cherry and other deciduous tree species that show the same patterns. [ABSTRACT FROM AUTHOR]

Key message: In a comparison of six methods of estimating foliage clumping, logarithmic methods were found to be the most suitable for validating remote sensing-based clumping maps. Abstract: The clumping index is a measure describing the spatial aggregation of foliage elements and has an important effect on radiation transfer in canopies. Quantifying the clumping index from field-based measurements has shown to be complicated, as values presented in literature vary substantially between methods. The goal of this work was to improve on previous comparison of beyond-shoot clumping quantification methods over Järvselja RAMI test sites by including additional methods as well as emphasizing the temporal variability of the clumping index by including two phenologically contrasting moments in the growing season. We show that while apparent clumping, digital cover photography-based methods and clumping from gap size distribution coincide well, they result in the maximum clumping value that should be considered in any case, whereas logarithmically based methods might provide more accurate estimates of clumping. The results are of great importance for the correct assessment of foliage clumping from space, as well as for current attempts to assess clumping using airborne and terrestrial laser scanning. [ABSTRACT FROM AUTHOR]

Key message : A hypergeometric model is proposed explicitly instead of two previous stochastic models (the Poisson model and Neyman-A model) to describe the topological relationship of trees and the influence of the exclusion distance on gap fraction and clumping index of forest plantation canopies. Abstract: Gap fraction (GF) and clumping index (CI) play key roles in plant light interception, and therefore they have strong impacts on plant growth and canopy radiative transfer processes. Trees are usually assumed to be randomly distributed in natural forests in many previous studies. However, few studies have shown how trees are distributed in forest plantations and how these distribution patterns affect GF and CI in these forests. In this paper, a simple and general distance factor defined as relative allowable shortest distance between centers of two adjacent crowns divided by the mean diameter of the crowns (RASD) is proposed to describe quantitatively the degree of mutual exclusion among trees in forest plantations of various tree distribution patterns. A hypergeometric model is proposed instead of two previous stochastic tree distribution models (the Poisson model and Neyman-A model) to describe the topological relationship of trees and the influences of the exclusion distance on the GF and CI of the forest plantation canopies. The results show that: (1) the hypergeometric model is more suitable than the Poisson model and Neyman-A model for describing the topological relationship of trees in forest plantations; (2) the exclusion distance has strong impacts on GF and CI: there are significant differences between the results of the hypergeometric model and the Poisson model. Larger RASD causes lower GF and larger CI. The simulations are verified by field measurements in four forest plantation stands. Similarly, impacts of RASD on GF and CI are also found for other two crown shapes (prolate and oblate ellipsoids). [ABSTRACT FROM AUTHOR]

Predicting the temporal and spatial variability of radiation intensity under wide-spaced tree stands is required for many applied issues in savannah-like ecosystems, orchards, agroforestry and urban forestry systems. Numerous authors have advocated the use of simple light interception models that approximate the crown shape with ellipsoids. They have suggested taking into account leaf clumping to improve the efficiency of these simple models, but this was never assessed. We tested this hypothesis together with the impact of including predictions of light interception by woody parts (trunks, branches). We calibrated and evaluated the model using cross-validation across eight walnut trees with field measurements of radiation intensity and spatial heterogeneity using hemispherical photographs. Leafless trees were efficiently modelled using Wood Area Density (WAD, mm) for branches and an opaque cone for the trunk. We introduced a clumping parameter (μ) but this proved inefficient, clumping being highly variable amongst trees. This results from the limitations of representing the crown as an ellipsoid, a procedure too coarse to be improved by using a clumping parameter. The model proved efficient to predict the light pattern around an average tree, but was not fit for simulating the variability of individual trees. We finally discuss practical recommendations for modelling light competition in integrated agroforestry models simply. [ABSTRACT FROM AUTHOR]

The effectiveness of using leveled digital camera for measuring leaf inclination angles was investigated in this study as an inexpensive and convenient alternative to existing approaches. The new method is validated with manual leaf angle measurements for various broadleaf tree species common to hemi-boreal region of Estonia and the tropical forests of Hawai'i Islands. The acquired leaf angle distributions suggest that planophile case might be more appropriate than the commonly assumed spherical as the general approximation of leaf orientation while modeling the radiation transmission through the canopies of (hemi)-boreal broadleaf stands. However, direct leaf inclination measurements should be obtained whenever possible, as there will always exist a large variety of leaf orientation, both among different species and in the space-time domain within a single species. The camera method tested in this study provides a new robust and affordable tool to obtain this information. [ABSTRACT FROM AUTHOR]

A method that applies the terrestrial laser scanning to estimate leaf areas of individual trees in a mature conifer forest is presented. It is based on the theory of conventional optical LAI determinations, but refined for the inclusion of 3D depth information from the laser scanner. For each objective tree, we first used a single scan to measure local gap fractions beyond determined crown depths and combined this scan with other scans to delineate the geometrical dimensions of the crown. Then, through integrating the information from both aspects, the local leaf area density and the corresponding volume were derived. Finally, the total leaf area was obtained as the scalar product of these two variables. As most procedures were implemented on segmented 2D range images, the method possesses high efficiency. Additionally, through using gap fraction beyond determined crown depths, it solved the zero gap fraction problem encountered in segmented hemispherical photograph analysis. The method was tested on 11 trees in a 39 years old Norway spruce ( Picea abies [L.] Karst.) stand located in southern Bavaria, Germany. Through correlation of the results with the estimates obtained with allometric equations, the accuracy was validated. The influence of the crown depth, for measuring gap fraction, and the segment size on estimation were also analyzed. [ABSTRACT FROM AUTHOR]

Light Detection and Ranging (LiDAR) systems can be used to estimate both vertical and horizontal forest structure. Woody components, the leaves of trees and the understory can be described with high precision, using geo-registered 3D-points. Based on this concept, the Effective Plant Area Indices (PAI) for areas of Korean Pine ( Pinus koraiensis), Japanese Larch ( Larix leptolepis) and Oak ( Quercus spp.) were estimated by calculating the ratio of intercepted and incident LIDAR laser rays for the canopies of the three forest types. Initially, the canopy gap fraction ( G) was generated by extracting the LiDAR data reflected from the canopy surface, or inner canopy area, using k-means statistics. The LiDAR-derived PAI was then estimated by using G with the Beer-Lambert law. A comparison of the LiDAR-derived and field-derived PAI revealed the coefficients of determination for Korean Pine, Japanese Larch and Oak to be 0.82, 0.64 and 0.59, respectively. These differences between field-based and LIDAR-based PAI for the different forest types were attributed to the amount of leaves and branches in the forest stands. The absence of leaves, in the case of both Larch and Oak, meant that the LiDAR pulses were only reflected from branches. The probability that the LiDAR pulses are reflected from bare branches is low as compared to the reflection from branches with a high leaf density. This is because the size of the branch is smaller than the resolution across and along the 1 meter LIDAR laser track. Therefore, a better predictive accuracy would be expected for the model if the study would be repeated in late spring when the shoots and leaves of the deciduous trees begin to appear. [ABSTRACT FROM AUTHOR]

Background: Hemispherical photography (HP) is a popular method to estimate canopy structure and understorey light environment, which analyses photographs acquired with wide view-angle lens (i.e. fisheye lens). To increase HP accuracy, the approaches of most previous studies were to increase the preciseness of exposure and thresholding of photographs, while ours quantified effects of canopy properties (gap fraction and length of sky-canopy border (SCB)) and errors of exposure and thresholding on the accuracy of HP.Results: Through analysing photographs of real and model canopies, it was showed that HP inaccuracy resulted from the mismatch between exposure and thresholding rather than exposure or thresholding errors alone. HP inaccuracy was a function of the SCB length and the extent of exposure and thresholding errors, but independent of gap fraction.Discussion: In photographs, SCBs are recorded as grey pixels which greyness is in between that of sky and canopy pixels. When there are exposure and thresholding errors, grey pixels are those prone to be misclassified in image analysis. Longer (vegetation with taller canopies) and wider (lower image sharpness) SCBs in photographs can both result in a higher amount of grey pixels and ultimately higher HP inaccuracy for a given extent of exposure and threshold errors.Conclusions: Using lenses with view angle narrower rather than that of fisheye lens can shorten the SCB length in photographs and in turn reduce HP estimation inaccuracy for canopy structure and understorey light environment. Since short SCBs and low levels of exposure and thresholding errors can both result in low HP inaccuracy, to identify the true performance of new exposure and thresholding methods for HP, photographs recording canopies with long SCBs and acquired with fisheye lenses should be used. Because HP inaccuracy in a function of the amount of grey pixels resulting from SCBs, the amount of these pixels in photographs can be used as a universal parameter to quantify canopy properties influential to HP estimation and in turn make cross-study comparisons feasible. [ABSTRACT FROM AUTHOR]