Crown Profiles Research Articles

Individual Tree Segmentation Based on Seed Points Detected by an Adaptive Crown Shaped Algorithm Using UAV-LiDAR Data

Unmanned aerial vehicle–light detection and ranging (UAV-LiDAR) provides a convenient and economical means of forest data acquisition that can penetrate canopy gaps to obtain abundant ground information, offering huge potential in forest inventory. Individual tree segmentation is a prerequisite to obtain individual tree details but is highly dependent on the accuracy of seed point detection. However, most of the existing methods, such as the local maximum (LM) and CHM-based methods, are strongly dependent on the window size, and, for individual tree segmentation, they can result in over-segmentation and under-segmentation, especially in natural forests. In this paper, we propose an adaptive crown shaped algorithm for individual tree segmentation without consideration of the window size. It was implemented in four plots with different forest types and topographies (i.e., planted coniferous forest with flat terrain, coniferous forest with sloping terrain, mixed forest with flat terrain and broadleaf forest with flat terrain). First, the normalized point clouds were rotated and blocked at multiple angles to extract the surface points of the forest. Then, the crown boundaries were delineated by analyzing the crown profiles to extract the treetops as seed points. Finally, a region growing method based on seed points was applied for individual tree segmentation. Our results showed that the recall, precision and F1-score of seed point detection reached 91.6%, 95.9% and 0.94, respectively, and that the accuracy rates for individual tree segmentation for the four plots were 87.7%, 80.6%, 73.2% and 70.5%, respectively. Our proposed method can effectively detect seed points via the adaptive crown shaped algorithm and reduce the impacts of elongated branches by applying distance thresholds between trees, enhancing the accuracy of seed point detection and subsequently improving the precision of individual tree segmentation. In addition, the proposed algorithm demonstrated superior performance in comparison to LM and CHM-based methods for the calculation of seed points, as well as outperforming PCS in individual tree segmentation. The proposed method demonstrates effectiveness and feasibility in dense forests and natural forests, providing an important reference for future research on seed point detection and individual tree segmentation.

Crown Profile Modeling and Prediction Based on Ensemble Learning

Improving prediction accuracy is a prominent modeling issue in relation to forest simulations, and ensemble learning is a new effective method for improving the precision of crown profile model simulations in order to overcome the disadvantages of statistical modeling. Background: Ensemble learning (a machine learning paradigm in which multiple learners are trained to achieve better performance) has strong nonlinear problem learning ability and flexibility in terms of analyzing longitudinal data, and it remains rarely explored so far in the field of crown profile modeling forest science. In this study, we explored the application of ensemble learning to the modeling and prediction of crown profiles. Methods: We evaluated the performance of ensemble learning procedures and marginal model in modeling crown profile using the crown profile database from China fir plantations in Fujian, in southern China. Results: The ensemble learning approach for the crown profile model appeared to have better performance and higher efficiency (R2 > 0.9). The crown equation model 18 showed an intermediate performance in its estimation, whereas GBDT (MAE = 0.3250, MSE = 0.2450) appeared to have the best performance and higher efficiency. Conclusions: The ensemble learning method can combine the advantages of multiple learners and has higher model accuracy, robustness and overall induction ability, and is thus an effective technique for crown profile modeling and prediction.

Study of the oil palm crown characteristics associated with Basal Stem Rot (BSR) disease using stratification method of point cloud data

Basal Stem Rot (BSR) disease caused by the Ganoderma boninense fungus is the most serious issue affecting the oil palm industry. Terrestrial laser scanning (TLS) technology is a precise, contact-free, and active remote sensing method which is widely used for determining tree morphology using the crown strata. However, its capability in BSR detection using crown strata solely has not been explored. Therefore, this study used TLS data to study the effect of crown profile due to BSR and develop a BSR detection model using crown strata. Ninety-two palms were selected at random consists of 36 healthy oil palm trees and 56 unhealthy oil palm trees infected by Ganoderma boninense. The palms were each scanned at four different positions around them, and crown strata (named as Cn; where n is the crown length in cm) were generated using crown stratification method. The numbers of laser hits in the strata were used to generate crown profiles comparing healthy and unhealthy oil palm trees, to develop prediction models and to examine the patterns of crown density in different parts. The study has accounted for the occlusion problem by carrying out a systematic multi-scan approach. Moreover, the short traveling distance (less than 12 m) needed for the laser to reach the maximum crown tips ensures greater point density. The profiles of crown strata revealed that the healthy trees have higher crown densities than unhealthy trees starting from 250 cm from the top (strata no. 5) to the bottom. Prediction models using the strata parameters C650, C700, C800, and C850 were 92.5% accurate in the classification of healthy-unhealthy trees.

Modelling the responses of crown profiles to competition in terms of different tree classes and directions in two coniferous tree species in northeastern China

Using branch data from 63 L.kaempferi and 36 L.gmelinii sampled trees in northeastern China, the responses of crown profiles with different tree classes (dominant, intermediate and suppressed trees) and aspects (north, east, south and west) to competition were studied. Crown displacement, defined as the distance between the centre of gravity of the crown and the stem base, was calculated for all the sampled trees to estimate the crown plasticity. The horizontal crown overlapping area (COAH) between sampled trees and the closest neighbouring trees was calculated to estimate the neighbour competition. A crown profile model that includes COAH as the explanatory variable was developed, and the effect of COAH on the crown profile of two tree species was analysed. The results showed that more than half of the trees had the largest crown radius and upper crown surface area on the north and east sides for L.kaempferi and on the north and south sides for L.gmelinii. The crown displacement of L.kaempferi was greater on the north and east sides, and that of L.gmelinii was greater on the south and east sides. COAH had a significant effect on the crown profile model for both species. The mean square error reduction (MSER) for the crown profile model including COAH relative to the model without COAH was 1.68% and 2.10% for L.kaempferi and L.gmelinii, respectively. The COAH had a greater impact on the crown profile of L.gmelinii than that of L.kaempferi. The inflexion point of the dominant and intermediate trees for both species was sensitive to COAH and gradually moved towards the crown base as the neighbour competition intensified, while the inflexion point of the suppressed tree showed a weak response to COAH. The crown profile in the four directions was closely related to the current radial stem growth.

Effect of strip shelterwood-cuts on the crown morphology plasticity of natural regenerated Pinus tabuliformis saplings in northeastern China.

The study analysed the effect of shelterwood-cut strips on the outermost crown profiles and crown characteristics of naturally regenerated Pinus tabuliformis saplings in northeastern China. A total of 49 regenerated saplings from shelterwood-cut strips and 30 from uncut strips were collected. Nonlinear quantile regression was used to develop the outermost crown profile model for the saplings from the shelterwood-cut and uncut strips. The quantile value suitable for describing the outermost crown profiles of the two types of strips was selected using nonparametric boundary regression. The difference in crown morphologies between the shelterwood-cut strips and uncut strips was compared. The results showed that with the same diameter at breast height, the crown radii of the uncut strip saplings were larger than those of the shelterwood-cut strip saplings within the range of 0.2–1.0 for the relative depth into the crown. The largest crown radius of the saplings from the uncut strips was larger than that of the saplings from the shelterwood-cut strips. The inflection points of the shelterwood-cut strip sapling crowns were larger than those of the uncut strip sapling crowns. The crown volume of the small uncut strip saplings was larger than that of the shelterwood-cut strip saplings, and the difference in crown volume decreased with increasing sapling size. The saplings in the early stage of the uncut strips showed a greater growth rate than those of the shelterwood-cut strips, but their growth rate slowed over the long term according to branch-length annual growth. The present study provides a reference for forest management strategy decision making in promoting natural regeneration.

Modelling the Crown Profile of Western Hemlock (Tsuga heterophylla) with a Combination of Component and Aggregate Measures of Crown Size

Research Highlights: We present statistical methods for using crown measurement data from multiple destructive sampling studies to model crown profiles in the Tree and Stand Simulator (TASS) and evaluate it using component (branch-level) and aggregate (tree-level) predictions. Combining data collected under different sampling protocols offered unique challenges. Background and Objectives: The approach to modelling crown profiles was based on Mitchell’s monograph on Douglas-fir growth and simulated dynamics. The functional form defines the potential crown size and shape and governs the rate of crown expansion. With the availability of additional data, we are able to update these functions as part of ongoing TASS development and demonstrate the formulation and fitting of new crown profile equations for stand-grown western hemlock (Tsuga heterophylla (Raf.) Sarg. Materials and Methods: Detailed measurements on 1616 branches from 153 trees were collected for TASS development over a 40-year period. Data were collected under two different sampling protocols and the methods were designed to allow the use of data from both protocols. Data collected on all branches were then introduced through the application of the ratio of length of each of the selected branches to the largest branch in the internode (RL). Results: A mixed-effects model with two random effects, which accounted for tree-level variation, provided the best fit. From that, a model that expressed one parameter as a function of another with one random effect was developed to complement the structure of the Tree and Stand Simulator (TASS). The models generally over-estimated crown size when compared to the projected crown area recorded from field measurements, and a scalar adjustment factor of 0.89 was applied that minimised mean-squared error of the differences. The new model is fit from direct measures of crown radius and predicts narrower crown shapes than previous functions used in TASS.

Apple orchard inventory with a LiDAR equipped unmanned aerial system

Knowledge about the number of trees in an orchard and their geometric parameters is beneficial in precise farming and together with other information may be used to predict the yield. These parameters can be obtained based on time-consuming field measurements or more effectively, from very high resolution 3D data collected with Unmanned Aerial Vehicles (UAV). Numerous UAV experiments have been conducted in agricultural areas; however, most of studies are limited to the use of a passive optical sensor (camera). This study demonstrates an experiment on the novel remote sensing approach of determining selected geometric parameters of trees in an apple orchard, based on a high-density point cloud obtained from a Velodyne HDL-32E laser scanner mounted on a small UAV platform Leica Aibot X6 V2. Reference data of selected geometric parameters of trees was obtained from orthophotomap and with geodetic surveying methods. Original and robust methodology is proposed for the point cloud processing, which is the inventive combination of an alpha-shape algorithm, principal component analysis and detection of local minima on crown profiles. The developed approach allowed for the correct identification of 99% of the trees in the test orchard. The root mean square error of determined crown areas was equal to 0.98 m2. The accuracy of tree top identification, tree height and crown base height determination was equal to 0.38, 0.09 and 0.09 m, respectively.

街道峡谷绿化带设置对空气流场及污染分布的影响模拟研究

PDF HTML阅读 XML下载 导出引用 引用提醒 街道峡谷绿化带设置对空气流场及污染分布的影响模拟研究 DOI: 10.5846/stxb201703080392 作者: 作者单位: 中国科学院生态环境研究中心,重庆市农业科学院生物技术研究中心,中国科学院生态环境研究中心,中国科学院生态环境研究中心 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金重点项目（41430638）；国家重点研究和发展计划项目（2016YFC0503003）；国家自然科学基金青年科学基金项目（31500381）；城市与区域生态国家重点实验室自主重点项目 Simulation study on the influence of green belt settings on air-flow and pollution distribution in street canyon Author: Affiliation: Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences,Biotechnology Research Center, Chongqing Academy of Agricultural Science,Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences,Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences Fund Project: The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:合理设置道路绿化带能够改变街道空气流场进而改善空气质量。利用风洞试验结合数值模型的方法测试了树冠形状和绿化带位置对街道峡谷的风场影响。在数值模型中，采用针对植物模型不同高度赋予不同叶面积密度（leaf area density，LAD）值的新方法近似模拟不同树冠形状的植物，通过输入污染源数据，得到风场及污染物浓度数据结果；与风洞试验结果进行对比，验证了其有效性；进而，利用数值模型分析了不同绿化带设置下街道峡谷内行人的污染暴露特征，结果表明：绿化带位置及树冠形状影响街道峡谷中的涡流结构，形成复杂的细小湍流，从而影响街道峡谷中的风环境和污染物分布。阔叶树冠和位于街道峡谷中央的绿化带位置有利于降低行人污染暴露风险。未来研究中，通过增加风洞试验布点、考虑热力作用及气象因子的影响，或许可以提供更加详细的改善街道峡谷微环境的绿化带布局，为城市大气环境管理和绿地系统建设提供科学依据。 Abstract:Reasonable greenbelt setting can change the air flow field, effectivelyoptimizing air quality. In this study, the effects of crown profiles and location of green belts in street canyon were explored by using wind tunnel and numerical model. In numerical part, an innovative method, assigning different leaf area density (LAD) values to different heights of plant models, was used to simulate the crown profiles in the numerical model, and then the pollution source data was input into the simulation system to calculate the wind field data and pollutant concentration data. After simulate calculation, the numerical model was verified by comparing data from simulation results with the the data obtained from wind tunnel experiment. At last, pollutant exposure characteristics of pedestrians in street canyons under different green belts settings were analyzed using the numerical model. The results show that the differences between green belts lacation and crown profile will affect the vortex structure in the street canyon, resulting in complex turbulence, which affects the wind environment and the pollutant distribution in the street canyon. The deciduous profile and the one central green belt are effective in reducing the pedestrians pollutant exposure. In future study, more monitoring points should be set in the wind tunnel and the influence of thermal and meteorological factors should also be embededinto simulation and wind tunnel experiment, so as to provide a more detailed configuration of the green belt in street planning to alleviate the pollution inthe microenvironment in street canyons, and provide better scientific basis for local atmospheric environment management and the design of urban green space. 参考文献 相似文献 引证文献

Modelling conifer crown profiles as nonlinear conditional quantiles: An example with planted Korean pine in northeast China

With few exceptions crown profile models for coniferous trees have conventionally been estimated within the least squares framework that is confined to describing the central trend of whorl radius along the stem. This article introduces a new approach of modelling the outer profiles of conifer tree crowns as nonlinear conditional quantiles using plantation grown Korean pine in northeast China as an example. The approach was demonstrated with two nonlinear model forms using data from detailed measurements of 83 sample trees with a total number of 1415 whorls and 5123 live branches. One model was based on a segmented polynomial function and the other was a modified variable-exponent function. For each model form, 11 nonlinear quantile curves were estimated using the branch radius data by taking 11 values of q, representing the qth quantile, from 0.5 to 0.95 with an even interval of 0.05 plus one extreme value of 0.99. Parameter estimates for a given value of q were obtained through repeated fitting by leaving one tree out each time in a simple form of jackknife model averaging. To select the best q values for delineating the outer or outmost contours of the exterior edges of tree crowns, three fix-effects (marginal) models of the same nonlinear form was fitted iteratively to the entire, about one-half and one-quarter of the whorl radius data after removing non-positive residuals at each iteration. Based on graphical evaluations and comparisons of benchmarking statistics, the 0.90th and 0.95th nonlinear quantiles were chosen for depicting the outer and outmost crown profiles of Korean pine trees for both model forms. The variable-exponent model appeared to be superior to the segmented polynomial model not only in delineating the outer crown profiles but also in estimating the largest crown radius of individual trees. In comparison to the marginal models or to the more traditional least squares regression, the new approach enables more accurate depictions of the outer or outmost crown profiles without subjective data selection and thus any loss of information. It also has the potential to profile the inner part of individual tree crowns through a family of nonlinear conditional quantial curves, therefore providing a greater insight into the crown structure than the conventional methods.

Modeling Variation in Crown Profile with Tree Status and Cardinal Directions for Planted Larix olgensis Henry Trees in Northeast China

Crown profile models were developed for north, east, south, and west crown directions of dominant trees, intermediate trees, and suppressed trees in planted stands of Larix olgensis Henry in Northeast China. A total of 139 sample trees were randomly selected, and all branches of each tree were measured. A segmented power equation, segmented polynomial equation, modified Weibull equation, and Kozak equation were selected as the candidate models. A traditional approach that did not consider the differences between tree status and crown directions was also developed. Three steps were conducted to analyze the effect of tree status (dominant, intermediate, and suppressed tree) and crown direction (north, east, south, and west) on the crown profiles using a dummy variable approach. Step 1 considered only tree status, Step 2 considered only crown direction, and Step 3 took both tree status and crown direction into account. Nonlinear mixed-effects model was used to express the effect of individual tree level on crown shape, and was also compared to the ordinary least-squares and generalized least-squares model. The results demonstrated that the modified Kozak equation showed good performance in the crown profile description. The nonlinear mixed-effects model significantly improved the model performance compared to the ordinary least-squares and generalized least-squares model. There were differences among the crown profiles among the four directions of dominant, intermediate, and suppressed trees. South-oriented crowns had the tendency to be the largest, which is likely to be mainly a result of light conditions. The competition status of the subject tree was the main reason leading to an asymmetric crown. Individual trees with strong competition levels had smaller crowns.

Estimation of tree crown volume from airborne lidar data using computational geometry

Although simple geometrical shapes are commonly used to describe tree crowns, computational geometry enables calculation of the individual crown properties directly from airborne lidar point clouds. Our objective was to calculate crown volumes (CVs) using this technique and validate the results by comparing them with field-measured values and modelled ellipsoidal crowns. The CVs of standing trees were obtained by measuring the crown radii at different heights, integrating the obtained crown profiles as solids of revolution, and finally averaging the volumes obtained from the four separate profiles. With the lidar data, the CVs were extracted using 3D alpha shape and 3D convex hull techniques. Crown base heights (CBHs) were also estimated from the lidar data and used to exclude echoes from the understory, which was also done using field-based CBHs to exclude this error source. The results show that the field-measured CVs had a high correlation with lidar-based estimates (best R 2 = 0.83), but the lidar-based estimates were generally smaller than the field values. The best correspondence (root mean square difference (RMSD) = 45.0%, average difference = –24.7%) was obtained using the convex hull of the point data and field-measured CBH. The CBHs were consistently overestimated (RMSD = 37.3%; average difference = –20.0%), especially in spruces with long crowns. Thus using lidar-based CBH also increased the inaccuracy of the CV estimates. While the underestimation of CV is mainly explained by the inadequate number of echoes from the lower regions of the crowns, the CVs obtained from the lidar were better than those obtained with ellipsoids fitted by using general models for crown dimensions. The utility of the estimated CVs in the prediction of stem diameter is also demonstrated.

What does optimization theory actually predict about crown profiles of photosynthetic capacity when models incorporate greater realism?

Measured profiles of photosynthetic capacity in plant crowns typically do not match those of average irradiance: the ratio of capacity to irradiance decreases as irradiance increases. This differs from optimal profiles inferred from simple models. To determine whether this could be explained by omission of physiological or physical details from such models, we performed a series of thought experiments using a new model that included more realism than previous models. We used ray-tracing to simulate irradiance for 8000 leaves in a horizontally uniform canopy. For a subsample of 500 leaves, we simultaneously optimized both nitrogen allocation (among pools representing carboxylation, electron transport and light capture) and stomatal conductance using a transdermally explicit photosynthesis model. Few model features caused the capacity/irradiance ratio to vary systematically with irradiance. However, when leaf absorptance varied as needed to optimize distribution of light-capture N, the capacity/irradiance ratio increased up through the crown - that is, opposite to the observed pattern. This tendency was counteracted by constraints on stomatal or mesophyll conductance, which caused chloroplastic CO(2) concentration to decline systematically with increasing irradiance. Our results suggest that height-related constraints on stomatal conductance can help to reconcile observations with the hypothesis that photosynthetic N is allocated optimally.

Differences in crown characteristics between black (Picea mariana) and white spruce (Picea glauca)

Black spruce ( Picea mariana (Mill.) Britton, Sterns & Poggenb.) and white spruce ( Picea glauca (Moench) Voss) are phylogenetically proximal species that differ in productivity. Crown characteristics of these two species have not been extensively studied, in spite of the importance of these two species to the Canadian boreal forest and the importance of tree crowns for understanding and modelling tree growth. In this paper, we characterize and compare the crown lengths, crown profiles (i.e., radii), shapes, and surface areas of these two species using 65 white spruce and 57 black spruce trees destructively sampled in the provinces of Alberta, Ontario, and Quebec, Canada. Crown length was measured on every sample tree, while crown profile was obtained by reconstructing crowns from branch measurements. Our results showed that crown lengths did not differ between these two species given the same tree size and growth conditions. However, these two species establish under different growth conditions resulting in crown length differences. Further, differences in crown radii and profiles were found even under the same growth conditions. White spruce trees had wider crown radii and profiles changed from a parabola to a cone shape under increased density. As a result, differences in crown surface areas were found.

Maximum and Largest Crown Width Equations for 15 Tree Species in Maine

Abstract An extensive statewide data set for seven conifer and eight hardwood species commonly occurring in Maine was used in the development of maximum and largest crown width equations. To establish the characteristics of open-grown trees, quantile regression was used to estimate the biological maximum crown width for a species at a given diameter. To predict crown widths of trees in forested settings, a constrained nonlinear equation was used, using the predicted maximum crown width, tree diameter, and crown ratio. The models performed well across the wide range of stand conditions present in the data set and improved predictions over the currently used crown width equations for most species (reduction of mean absolute error ranged from 1 to 23%). In general, predictions of largest crown width were not greatly improved with the inclusion of crown ratio, and there was a high amount of unexplained variation for shade-tolerant hardwood species, such as American beech (Fagus grandifolia) and sugar maple (Acer saccharum). The equations presented herein can be used in examining tree crown profiles, computing measurements of stand density, and investigating canopy dynamics for species common to the forests of Maine.

A crown profile model for Pinus radiata D. Don in northwestern Spain

A crown profile model was developed for radiata pine ( Pinus radiata D. Don) in Galicia (northwestern Spain). Data from 443 trees located in 56 permanent plots, established by the Unidade de Xestión Forestal Sostible (UXFS) of the University of Santiago de Compostela in plantations of this species in the region, were used. The crowns of the trees were measured by a visual method based on similar triangles. Both simple geometric shapes and mathematical equations were used to describe the crown profiles. As crown profile models usually require variables that are expensive to measure, equations to estimate the maximum crown radius and the height to the maximum crown radius were also developed, using other easily measured tree and stand variables. Several models were fitted using a system of equations approach and accounting for an autocorrelated, heteroscedastic error structure. The selected crown profile model consists of a system of two allometric equations for the crown below (primarily shade needles) and above (primarily sun needles) maximum crown radius. The model explained 88% of the variability in crown radius with a mean error of 0.24 m.

Capturing tree crown formation through implicit surface reconstruction using airborne lidar data

Forest structure data derived from lidar is being used in forest science and management for inventory analysis, biomass estimation, and wildlife habitat analysis. Regression analysis dominated previous approaches to the derivation of tree stem and crown parameters from lidar. The regression model for tree parameters is locally applied based on vertical lidar point density, the tree species involved, and stand structure in the specific research area. The results of this approach, therefore, are location-specific, limiting its applicability to other areas. For a more widely applicable approach to derive tree parameters, we developed an innovative method called ‘wrapped surface reconstruction’ that employs radial basis functions and an isosurface. Utilizing computer graphics, we capture the exact shape of an irregular tree crown of various tree species based on the lidar point cloud and visualize their exact crown formation in three-dimensional space. To validate the tree parameters given by our wrapped surface approach, survey-grade equipment (a total station) was used to measure the crown shape. Four vantage points were established for each of 55 trees to capture whole-tree crown profiles georeferenced with post-processed differential GPS points. The observed tree profiles were linearly interpolated to estimate crown volume. These fieldwork-generated profiles were compared with the wrapped surface to assess goodness of fit. For coniferous trees, the following tree crown parameters derived by the wrapped surface method were highly correlated ( p < 0.05) with the total station-derived measurements: tree height ( R 2 = 0.95), crown width ( R 2 = 0.80), live crown base ( R 2 = 0.92), height of the lowest branch ( R 2 = 0.72), and crown volume ( R 2 = 0.84). For deciduous trees, wrapped surface-derived parameters of tree height ( R 2 = 0.96), crown width ( R 2 = 0.75), live crown base ( R 2 = 0.53), height of the lowest branch ( R 2 = 0.51), and crown volume ( R 2 = 0.89) were correlated with the total station-derived measurements. The wrapped surface technique is less susceptible to errors in estimation of tree parameters because of exact interpolation using the radial basis functions. The effect of diminished energy return causes the low correlation for lowest branches in deciduous trees ( R 2 = 0.51), even though leaf-off lidar data was used. The wrapped surface provides fast and automated detection of micro-scale tree parameters for specific applications in areas such as tree physiology, fire modeling, and forest inventory.

Simplified tree crown model using standard forest mensuration data for Scots pine

Crown profiles of 260 Scots pines in central Finland were measured using a new method developed in the study, and a simple model for crown shape, belonging to the Lamé curve family, was derived using these data. Relatively accurate estimates of the crown maximum radius and its height, parameters needed for application of the model, were obtained using breast height diameter (dbh) and tree height. Results suggest that the model could potentially be used to generate the crown shape directly from routine stand data.

Accuracy and precision of crown profile, volume, and surface area measurements of 29-year-old Japanese cypress trees using a Spiegel relascope

The crown profile, volume, and surface area obtained from 25 trees in a stand of 29-year-old Japanese cypress (Chamaecyparis obtusa Endl.) using a Spiegel relascope were compared with those obtained by direct measurement after tree felling. In 17 of the 25 trees, the crown profile measured with the relascope was identical to the crown profile obtained by direct measurement. For the 17 trees, the mean relative errors of crown volume and surface area tended to be unbiased. On the other hand, the crown profiles obtained by the two methods were different in five of the 25 trees, while it could not been judged whether the crown profiles obtained by the two methods were identical or different in three of the 25 trees. However, for each group of five or three trees, the mean relative errors of crown volume and surface area were also unbiased. Moreover, for both crown volume and surface area, no significant differences were detected in variance of error among the groups of 17, five, and three trees. Therefore, the discrepancy between crown profiles obtained by the two methods for the five and three trees might be negligible in terms of the accuracy and precision of crown volume and surface area measurements. The standard errors for both crown volume and surface area were larger in each of the five and three trees than in the 17 trees. However, even for the five and three trees, the crown volume and surface area obtained using the relascope were more precise than those based on the assumption that crown form was a cone or paraboloid. We concluded that using a Spiegel relascope would enable us to obtain an accurate and precise crown profile, volume, and surface area of Japanese cypress trees for practical use, especially when the main objective of measurement is determining crown volume or surface area.

Sensitivity analyses of woody species exposed to air pollution based on ecophysiological measurements.

Air pollution has been of a major problem in the Pearl River Delta of south China, particularly during the last two decades. Emissions of air pollutants from industries have already led to damages in natural communities and environments in a wide range of the Delta area. Leaf parameters such as chlorophyll fluorescence, leaf area (LA), dry weight (DW) and leaf mass per area (LMA) had once been used as specific indexes of environmental stress. This study aims to determine in situ if the daily variation of chlorophyll fluorescence and other ecophysiological parameters in five seedlings of three woody species, Ilex rotunda, Ficus microcarpa and Machilus chinensis, could be used alone or in combination with other measurements for sensitivity indexes to make diagnoses under air pollution stress and, hence, to choose the correct tree species for urban afforestation in the Delta area. Five seedlings of each species were transplanted in pot containers after their acclimation under shadowing conditions. Chlorophyll fluorescence measurements were made in situ by a portable fluorometer (OS-30, Opti-sciences, U.S.A). Ten random samples of leaves were picked from each species for LA measurements by area-meter (CI-203, CID, Inc., U.S.A). DW was determined after the leaf samples were dried to a constant weight at 65 degrees C. LMA was calculated as the ratio of DW/LA. Leaf N content was analyzed according to the Kjeldhal method, and the extraction of pigments was carried out according Lin et al. The daily mean Fv/Fm (Fv is the variable fluorescence and Fm is the maximum fluorescence) analysis showed that Ilex rotunda and Ficus microcarpa were more highly resistant to pollution stress, followed by Machilus chinensis, implying that the efficiency of photosystem II in I. rotunda was less affected by air pollutants than the other two species. Little difference in daily change of Fv/Fm in I. rotunda between the polluted and the clean site was also observed. However, a relatively large variation of Fv/Fm appeared in the other two species, particularly in M. chinensis, suggesting that they were more sensitive to air pollutants than I. rotunda. The mean LA was reduced for all species growing at the polluted site. The mean LMA for all species exceeded the sclerophylly threshold given by Cowling and Campbell and increased for those under pollution stress, which could be explained as one of the acclimation strategies for plants to air pollution stress. Little difference in leaf chlorophyll content was observed in F. microcarpa and M. chinensis, while remarkable differences were found in I. rotunda growing at the polluted and the clean site. Content of leaf carotenoids was largely reduced in I. rotunda growing at the polluted site, but increased in F. microcarpa and M. chinensis, compared with plants growing at the clean site. Plants growing at the clean site had a lower leaf N content than those growing at the polluted site. In addition, species with a higher resistance to pollution stress showed less difference in leaf N content than those sensitive species. Based on Fv/Fm measurements of the three woody species, I. rotunda showed the highest resistance to air pollutants from ceramic industries, followed by F. microcarpa. M. chinensis was the most sensitive species to air pollution, had lowest capacities to cope with the air pollution stress, which was consistent with visual injury symptoms observed in the crown profiles of plants at the polluted site. Fv/Fm, LAM, LA, leaf pigments and N content could be used alone or in combination to diagnose the extent of the physiological injury. The ratio of Fv/Fm, however, was the best and most effective parameter. Tree species which have higher air-pollutant resistance, as diagnosed by such ecophysiological parameters, should be considered first and planted widely for urban afforestation or forest regeneration in areas where the forest was seriously degraded or forest health was markedly effected by the same kind of air pollutants.

Autoregressive moving average models of conifer crown profiles

A time-series autoregressive moving average (ARMA) approach was used to develop stochastic models of tree crown profiles for five conifer species of the Sierran mixed conifer habitat type. Models consisted of three components: (1) a polynomial trend: (2) and ARMA model; and (3) rand om error. A Bayesian information criterion was used to evaluate alternative models. It was found that 70% of the crown profiles could be modeled using first-order ARMA [AR(1) or MA(1)] models, and that an additional 25% could be modeled using a white noise model [(AR(0)]. When the coefficients of the ARMA models were statistically significant, the models proved to be both visually and statistically an improvement over the polynomial trend (a Euclideam model). A binary classification system was used to determine if model type was related to tree or stand characteristics. Using this classification we found that it was possible to relat the appropriate model type to forest tree size and forest stand density with acceptable accuracy.