Tree Crown Size Research Articles

Allometric equations for integrating remote sensing imagery into forest monitoring programmes.

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able – for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed – specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large‐scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.

Lidar detection of individual tree size in tropical forests

Abstract Characterization of tropical forest trees has been limited to field-based techniques focused on measurement of diameter of the cylindrical part of the bole, with large uncertainty in measuring large trees with irregular shapes, and other size attributes such as total tree height and the crown size. Here, we introduce a methodology to decompose lidar point cloud data into 3D clusters corresponding to individual tree crowns (ITC) that enables the estimation of many biophysical variables of tropical forests such as tree height, crown area, crown volume, and tree number density. The ITC-based approach was tested using airborne high-resolution lidar data collected over the 50-ha Center for Tropical Forest Science (CTFS) plot in the Barro Colorado Island, Panama. The lack of tree height and crown size measurements in the field prohibits the direct validation of the ITC metrics. We assess the reliability of our method by comparing the aboveground biomass (AGB) estimated using ground and lidar individual tree measurements at multiple spatial scales, namely 1 ha, 2.25 ha, 4 ha, and 6.25 ha. We examined four different lidar-derived AGB models, with three based on individual tree height, crown volume, and crown area, and one with mean top canopy height (TCH) calculated at the plot level using the lidar canopy height model. Results show that the predictive power of all models based on ITC size and TCH increases with decreasing spatial resolution from 16.9% at 1 ha for the worst model to 5.0% at 6.25 ha for the best model. The TCH-based model performed slightly better than ITC-based models except at higher spatial scales (~ 4 ha) and when errors due to edge effects associated with tree crowns were reduced. Unlike the TCH models that change regionally depending on forest type and structure allometry, the ITC-based models are derived as a function of individual tree allometry and can be extended globally to all tropical forests. The method for lidar detection of individual crown size overcome some limitations of ground-based inventories such as 1) it is able to access crowns of large trees and 2) it enables the assessment of directional changes in tree density, canopy architecture and forest dynamics over large and inaccessible areas to support robust tropical ecological studies.

Improved method for estimating tree crown diameter using high-resolution airborne data

IFER—Institute of Forest Ecosystem Research, Cs. armady 655,Jilove u Prahy 254 01, Czech RepublicAbstract. Automatic mapping of tree crown size (radius, diameter, or width) from remote sens-ing can provide a major benefit for practical and scientific purposes, but requires the develop-ment of accurate methods. This study presents an improved method for average tree crowndiameter estimation at a forest plot level from high-resolution airborne data. The improvedmethod consists of the combination of a window binarization procedure and a granulometricalgorithm, and avoids the complicated crown delineation procedure that is currently used toestimate crown size. The systematic error in average crown diameter estimates is correctedwith the improved method. The improved method is tested with coniferous, beech, andmixed-species forest plots based on airborne images of various spatial resolutions. The absolute(quantitative) accuracy of the improved crown diameter estimates is comparable or higher forboth monospecies plots and mixed-species plots than the current methods. The ability of theimproved method to produce good estimates for average crown diameters for monocultureand mixed species, to use remote sensing data of various spatial resolution and to operate inautomatic mode promisingly suggests its applicability to a wide range of forest systems.

Tree crown size as a measure of tree biosocial position in 135-year-old oak (Quercus L.) stand

Abstract The paper presents an attempt to apply measurable traits of a tree – crown projection area, crown length, diameter at breast height and tree height for classification of 135-year-old oak (Quercus L.) trees into Kraft classes. Statistical multivariate analysis was applied to reach the aim. Empirical material was collected on sample plot area of 0.75 ha, located in 135-year-old oak stand. Analysis of dimensional traits of oaks from 135-year-old stand allows quite certain classification of trees into three groups: pre-dominant, dominant and co-dominant and dominated ones. This seems to be quite promising, providing a tool for the approximation of the biosocial position of tree with no need for assessment in forest. Applied analyses do not allow distinguishing trees belonging to II and III Kraft classes. Unless the eye-estimation-based classification is completed, principal component analysis (PCA) method provided simple, provisional solution for grouping trees from 135-year-old stand into three over-mentioned groups. Discriminant analysis gives more precise results compared with PCA. In the analysed stand, the most important traits for the evaluation of biosocial position were diameter at breast height, crown projection area and height.

Unsupervised individual tree crown detection in high-resolution satellite imagery

Rapidly and accurately detecting individual tree crowns in satellite imagery is a critical need for monitoring and characterizing forest resources. We present a two-stage semiautomated approach for detecting individual tree crowns using high spatial resolution (0.6 m) satellite imagery. First, active contours are used to recognize tree canopy areas in a normalized difference vegetation index image. Given the image areas corresponding to tree canopies, we then identify individual tree crowns as local extrema points in the Laplacian of Gaussian scale-space pyramid. The approach simultaneously detects tree crown centers and estimates tree crown sizes, parameters critical to multiple ecosystem models. As a demonstration, we used a ground validated, 0.6 m resolution QuickBird image of a sparse forest site. The two-stage approach produced a tree count estimate with an accuracy of 78% for a naturally regenerating forest with irregularly spaced trees, a success rate equivalent to or better than existing approaches. In addition, our approach detects tree canopy areas and individual tree crowns in an unsupervised manner and helps identify overlapping crowns. The method also demonstrates significant potential for further improvement.

Realistic Representation of Trees in an Urban Canopy Model

A single-layer urban canopy model that captures sub-facet heterogeneity and various hydrological processes is further developed to explicitly incorporate trees within the urban canyon. The physical processes associated with trees are shortwave/longwave radiation exchange, including mutual interception and shading by trees and buildings and multiple reflections, sensible heat and latent heat (through transpiration) exchange, and root water uptake. A computationally-efficient geometric approach is applied to the radiation exchanges, requiring a priori knowledge of view factors. These view factors are first obtained from independent Monte Carlo ray-tracing simulations, and subsequently simple relations, which are functions of canyon aspect ratio and tree-crown ratio, are proposed to estimate them. The developed model is evaluated against field observations at two urban sites and one suburban site, showing improved performance for latent heat flux compared to the previous version that only includes ground vegetation. The trees in the urban canopy act to considerably decrease sensible heat flux and increase latent heat flux, and these effects are found to be more significant in the more dense urban site. Sensitivity tests are then performed to examine the effects of tree geometry relative to canyon geometry. The results indicate that the tree-crown size relative to canyon width is the most influential parameter to decrease sensible heat flux and increase latent heat flux, resulting in cooling of the urban area.

Retrieval of three-dimensional tree canopy and shade using terrestrial laser scanning (TLS) data to analyze the cooling effect of vegetation

Urban warming has become a serious problem due to global warming and rapid urbanization. One important phenomenon is the increasing urban heat island (UHI) effect, which has a serious negative impact on energy consumption, environmental pollution, and human well-being. Trees lower land surface and air temperatures by providing shade and through the process of evapotranspiration and therefore are useful in effectively mitigating the UHI effect. The cooling effects of trees vary depending on the tree crown size and density and the optical properties of their leaves. Selection of the best species to plant is important in achieving effective mitigation of the UHI effect. In this research, we examined four woodlands. Three of these woodlands are dominated by species (Cinnamomum camphora, Metasequoia glyptostroboides, Magnolia grandiflora) that are frequently planted in Nanjing, China and one is a mixed woodland. Terrestrial laser scanning (TLS) was employed to detail the vegetation canopy structure and capture the volume of three-dimensional point clouds of the leaves (L_V3DPC), as well as the shade at each case study site. Meteorological parameters were measured at each site. Statistical analysis was used to assess the cooling effects of the different woodlands and their impacts. This research revealed that trees can influence the microclimate beneath their canopies and that the degree of the impact is different for different tree species. Statistical analyses showed that the woodlands studied exhibit obvious temperature reductions during the daytime (05:00–19:30) and weaker temperature reductions during the nighttime (19:30–05:00). The temperature reduction was greatest for M. glyptostroboides, followed by C. camphora, M. grandiflora, and the trees in the mixed broad-leaved woodland. These results indicate that small-leaved species tend to be more effective at cooling than large-leaved species. Comparisons of the Leaf Area Index (LAI) and Sky View Factor (SVF) with L_V3DPC and shade, respectively, show that L_V3DPC and shade better reflect the impact of the vegetation canopy on the cooling effect. Multiple linear regression analyses showed that shading by trees is of prime importance in cooling the thermal environment. The high significance of L_V3DPC and shade indicate that the tree canopy is a major component of the contribution of trees to microclimatic environments, particularly the cooling effect under the tree canopy. This paper presents an innovative technique for determining tree canopy shade using TLS data for the purpose of analyzing the cooling effect of trees. The findings can be used as a guide to aid in the selection of the best species for urban greenspace planning and design to cool the thermal environment and enhance energy savings in urban environments.

Динаміка стану та структура сосняків в умовах забруднення атмосфери викидами Рівненського відкритого акціонерного товариства «Азот»

Представлено результати дослідження протягом 1993-2013 рр. стану та просторової структури сосняків в умовах аеротехногенного забруднення в Поліссі. Вивчено середньовікові сосняки, що розташовані на відстані 4,5-25 км від Рівненського ВАТ «Азоту» і складають екологічний ряд за рівнем забруднення. Встановлено, що через погіршення стану та падіння приросту зменшилися розмір та частка крон у висоті дерева і як наслідок – знизилася потужність біогоризонту фотосинтезу сосняків. За гострого пошкодження гірший стан був надпанівних та панівних дерев, а за хронічного він найгірший у нижній частині намету. Зі зростанням пошкодження дерев вирівнюються у висоті і порушується співвідношення груп класів Крафта. Зростає відсоток дерев,які мають парасолькоподібну форму крони, що є свідченням передчасного старіння дерев унаслідок дії аеротехногенного забруднення.

Estimating average tree crown size using high-resolution airborne data

Tree crown size is a key parameter of tree structure that has a variety of uses, including assessment of stand density, tree growth, and amount of timber volume assessment. Remote sensing techniques provide a potentially low-cost alternative to field-based assessments, but require the development of algorithms to easily and accurately extract the required information. This study presents a method for average crown diameter estimation on a plot level based on high-resolution airborne data. The method consists of the combination of a window binarization procedure and a granulometric algorithm. This approach avoids the complicated crown delineation procedure that is currently used to estimate crown size. The method was applied to a spruce mountain forest and was verified on 23 reference plots. The method achieved best results of R 2 =76% [ RMSE=0.37 m (11.2% of the observed mean)] and R 2 =79% [ RMSE=0.49 m (16.7% of the observed mean)]. The study investigates the dependence of the algorithm results on the sun altitude of each image, and determines the optimal combination of spectral bands from hyperspectral airborne images for the application of the method.

Crown size and growing space requirement of common tree species in urban centres, parks, and forests

Tree crown size determines among others tree's growth, carbon sequestration, shading, filtering of fine air particulates, and risk of wind-breaking. The dependence of crown size on species, resource supply, and tree age complicates an accurate evaluation of a tree's space requirement, and its size-dependent functions and services in urban as well as in forested areas.Based on a world-wide dataset of tree crown measurements of 22 common urban tree species we first derived species-specific crown radius–stem diameter relationships for open grown conditions. By cluster analysis we then assigned the 22 species to 5 crown extension types and developed mean relationships of tree height, crown radius, crown projection area, and crown volume depending on tree diameter for each type. This allometric analysis yielded auxiliary relationships which can be used for estimating the species-specific crown size and dynamics at a given tree dimension. We discuss how the results can support the choice and initial spacing of particular species and the assessment and prognosis of their functions and services.

Effects of tree morphometry on net snow cover radiation on forest floor for varying vegetation densities

AbstractUsing a forest radiation model, this paper explores the effects of tree morphometric parameters and shape on net snow cover radiation on the forest floor. Results show that tree shape, height and crown size and density have significant effects on the amount of radiation on forest floor and its variation with vegetation density. In clear sky conditions, where net radiation frequently shows a nonmonotonic decreasing then increasing trend with increasing vegetation density, a smaller radiation minimum is obtained for taller trees, larger and denser crowns, and cylindrical‐shaped crowns. The obtained radiation minimum is also expressed at a smaller vegetation density for these tree configurations. In contrast, trees with smaller crown dimensions show propensity for a monotonically decreasing trend in net radiation with increasing vegetation density. The sensitivity to tree morphometric parameters, especially tree height and crown width and density, on forest floor radiation are however relatively modest for interspersed cloudy conditions. The results will facilitate identification of forest management strategies to minimize or maximize net radiation in snow‐dominated forested watersheds and will allow intercomparison of snowmelt rates between forests with different vegetation densities and morphological characteristics.

Application of a single-tree identification algorithm to LiDAR data for the simulation of stem volume current annual increment

A single-tree identification method has been applied to light detection and ranging (LiDAR) data acquired over a protected coastal area in Tuscany (San Rossore Regional Park, Central Italy). The method, which is based on the computation of the convergence index from the LiDAR tree-height image, is capable of identifying individual pine trees in densely populated stands. The main features of each pine tree (height and crown size) are also estimated, which allows the final prediction of stem volume. The accuracy of the stem volume estimates is first assessed through a comparison with the ground measurements of a recent forest inventory of the park [San Rossore Forest Inventory (SRFI)]. This test indicates that stem volume is predicted with moderate accuracy at stand level ( r around 0.65). The stem volume estimates are then used to drive a modeling strategy which, on the basis of remotely sensed and ancillary data, is capable of predicting stem volume current annual increment (CAI). A final accuracy assessment indicates that the use of LiDAR stem volumes in place of the SRFI measurements only slightly deteriorates the quality of the obtained stand CAI estimates.

Quantifying scattered sound energy from a single tree by means of reverberation time

Trees in urban spaces surrounded by buildings may be effective in dispersing sound energy, and this could affect sound level distribution and street canyon reverberation. To quantify this effect of trees with a view to including it in numerical predictions, this paper examines sound scattering from a single tree in open field by means of reverberation time (RT). Five trees of different species and crown sizes were considered. The influence of ground condition, receiver height, crown size and shape, foliage condition, and source-receiver angle and distance has been assessed. The results show that RT20 is proportional to the tree crown size, which is the most important factor. The maximum RT20 measured was 0.28 s at 4000 Hz for the studied trees when in leaf (with foliage). The presence of leaves increased RT20 at high frequencies, typically by 0.08 s at 4000 Hz. It was also demonstrated that the source-receiver angle can affect the characteristics of decay curves significantly. With increasing source-receiver distance within 40 m, RT20 was slightly changed. It was shown that ground condition and receiver height affect the decay curves, especially at low and mid frequencies, where sound scattering is of relatively limited importance.

Model-Based Analysis–Synthesis for Realistic Tree Reconstruction and Growth Simulation

Due to complexity, vegetation analysis and reconstruction of remote sensing data are challenging problems. Using architectural tree models combined with model inputs estimated from aerial image analysis, this paper presents an analysis-synthesis approach for urban vegetation detection, modeling, and reconstruction. Tree species, height, and crown size information are extracted by aerial image analysis. These variables serve for model inversion to retrieve plant age, climatic growth conditions, and competition with neighbors. Functional-structural individual-based tree models are used to reconstruct and visualize virtual trees and their time evolutions realistically in a 3-D viewer rendering the models with geographical coordinates in the reconstructed scene. Our main contributions are: 1) a novel approach for generating plant models in 3-D reconstructed scenes based on the analysis of the geometric properties of the data, and 2) a modeling workflow for the reconstruction and growth simulation of vegetation in urban or natural environments.

Automated tree crown detection and size estimation using multi-scale analysis of high-resolution satellite imagery

We tested an automated multi-scale approach for detecting individual trees and estimating tree crown geometry using high spatial resolution satellite imagery. Individual tree crowns are identified as local extrema points in the Laplacian-of-Gaussian scale-space pyramid that is constructed based on linear scale-space theory. The approach simultaneously detects tree crown centres and estimates tree crown sizes (radiuses). We evaluated our method using two 0.6-m resolution QuickBird images of a forest site that underwent a large shift in tree density between image captures due to drought-associated mortality. The automated multi-scale approach produced tree count estimates with an accuracy of 54% and 73% corresponding to the dense and sparse forests, respectively. Estimated crown diameters were linearly correlated with field-measured crown diameters (r = 0.73–0.86). Tree count accuracies and size estimates were comparable with alternative methods. Future use of the presented approach is merited based on the results of our study, but requires further investigation in a broader range of forest types.

Three-dimensional forest reconstruction and structural parameter retrievals using a terrestrial full-waveform lidar instrument (Echidna®)

Three-dimensional (3-D) reconstructions of forest stands, constructed from scans of the Echidna® full-waveform terrestrial lidar, provide a new pathway to estimate forest structural parameters such as tree diameter at breast height, tree height, crown diameter, and stem count density (trees per hectare). We provide such reconstructions using data from the Echidna® Validation Instrument (EVI), which emits laser pulses at 1064nm wavelength and digitizes the full return waveform. We reconstructed four stands from the Sierra National Forest and two stands from Harvard Experimental Forest of 50m by 50m size, with varying tree density and species, using data acquired in 2008 and 2009. Our procedure processes each lidar pulse return to identify one or multiple “hits” and their associated peak return power; converts peak power to apparent reflectance; locates hits in Cartesian coordinate space and stores them as points in a point cloud with associated attributes; registers and merges five (Sierra) or nine (Harvard) overlapping scans into a single point cloud; identifies the ground plane and classifies ground hits; produces a local digital elevation model; classifies non-ground hits as trunk/branch or foliage hits using the relative width of the return pulse; and uses commercial software tools to display, manipulate, and interact with the point cloud to make direct measurements of trees in the virtual space of the reconstruction. Results show good to very good agreement between virtual and manual measurements of tree diameter, height, and crown size, with R2 values ranging from 0.70 to 0.99.

Mapping wild pear trees (Pyrus bourgaeana) in Mediterranean forest using high-resolution QuickBird satellite imagery

Recent advances in spatial and spectral resolution of satellite imagery as well as in processing techniques are opening new possibilities of fine-scale vegetation analysis with interesting applications in natural resource management. Here we present the main results of a study carried out in Sierra Morena, Cordoba (southern Spain), aimed at assessing the potential of remote-sensing techniques to discriminate and map individual wild pear trees (Pyrus bourgaeana) in Mediterranean open woodland dominated by Quercus ilex. We used high spatial resolution (2.4 m multispectral/0.6 m panchromatic) QuickBird satellite imagery obtained during the summer of 2008. Given the size and features of wild pear tree crowns, we applied an atmospheric correction method, Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercube (FLAASH), and six different fusion ‘pan-sharpening’ methods (wavelet ‘à trous’ weighted transform, colour normalized (CN), Gram–Schmidt (GS), hue–saturation–intensity (HSI) colour transformation, multidirection–multiresolution (MDMR), and principal component (PC)), to determine which procedure provides the best results. Finally, we assessed the potential of supervised classification techniques (maximum likelihood) to discriminate and map individual wild pear trees scattered over the Mediterranean open woodland.

EXTRACTION OF FOREST STANDS PARAMETERS FROM ASTER DATA IN OPEN FOREST

Abstract. Tree crown size (CS) and stem number per hectare (SN) has become increasingly important for forest management and ecosystem monitoring. Tree crown size is also strongly related to other canopy structural parameters, such as diameter at breast height, tree height and biomass. For both issues, remote sensing data are attractive for their large-area and up-to-date mapping capacities. The QuickBird and ASTER imagery used in this study was acquired over Zagros Forests in southern Zagros region, Fars province of Iran on 1 August 2005 and 1 July 2005, respectively. For the forest site investigated in this study, we concentrated on stands of Quercus Persica which is the dominant species in Zagros region. This study was conducted to investigate the capabilities of ASTER-L1B data to estimate some of forest parameters at individual tree and stand level in dry area. The forest stand parameters are crown area, crown density, average crown area. Obtaining the accuracy of classification the ground truth map was prepared by tree crown delineation using the panchromatic band of QuickBird data. Individual tree crowns were automatically delineated by color segmentation of QuickBird imagery. Simple linear regression procedure was used to show the relationships between spectral variables and the individual trees and forest stand parameters. With decreasing the crown density the effects of background will increase. Our results indicated that crown size could be accurately extracted from panchromatic band of QuickBird images especially for open forest stands. This paper demonstrates that using high-resolution satellite imagery in the open forest offers a unique opportunity for deriving single tree attributes and allowing reliable ground truth map to estimate stand structure. ASTER data and its indices showed good capability to estimate crown area in this study.

Interannual Variation in Nut Abundance Is Related to Agonistic Interactions of Foraging Female Japanese Macaques (Macaca fuscata)

The importance of dominance status to foraging and ultimately survival or reproductive success in wild primates is known; however, few studies have addressed these variables simultaneously. We investigated foraging and social behavior among 17 adult female Japanese macaques (Macaca fuscata) on Kinkazan Island, northern Japan, from September to November in 2 consecutive years (2004 and 2005) to determine whether interannual variation in food availability was related to variation in agonistic interactions over food resources and the feeding behavior of individuals of different dominance rank. We compared energy obtained with daily energy requirements and also examined the effect of variation in feeding behavior on female survival and reproductive success. Fruiting conditions differed considerably between the 2 yr: of four nut-producing species, the nuts of only Torreya nucifera fruited in 2004, whereas all four species, particularly Fagus crenata, produced nuts in abundance in 2005. The abundance and average crown size of trees of Torreya nucifera were smaller than those of Fagus crenata, and there was a higher frequency of agonistic interactions during 2004, when dominant, but not subordinate, individuals were able to satisfy daily energy requirements from nut feeding alone through longer nut feeding bouts. In contrast, all macaques, regardless of their dominance rank, were able to satisfy their energy requirements by feeding on nuts in 2005. Subordinate macaques appeared to counter their disadvantage in 2004 by moving and searching for food more and maintaining larger interindividual distances. Several lower-ranking females died during the food-scarce season of 2004, and only one dominant female gave birth the following birth season. In contrast, none of the adult females died during the food-scarce season of 2005, and 12 females gave birth the following birth season. These findings suggest that an interaction between dominance rank and interannual variation in food availability are related to macaque behavior, survival, and reproduction.

Determining Biophysical Parameters for Olive Trees Using CASI‐Airborne and Quickbird‐Satellite Imagery

This study reports on the development of remote sensing methods for estimation of biophysical parameters in olive orchards. Field and airborne campaigns were conducted in 2003 and 2004 in two orchards located in southern Spain. Ground measurements of crown transmittance and leaf area index (LAI) of individual olive trees (Olea europaea L.) were done using the LAI‐2000 Plant Canopy Analyzer. Hyperspectral images were acquired with a compact airborne spectrographic imager (CASI) at 1‐m spatial and with QuickBird satellite sensor at 2.5‐m spatial resolution. The panchromatic 0.6‐m spatial resolution image was also acquired with QuickBird. These images enabled the application of automatic algorithms for olive crown identification and delineation, to determine tree crown size and LAI. These methods proved successful for determining projected olive crown area, obtaining determination coefficients (r 2) in the range of 0.82 to 0.65, and root mean square errors (RMSE) of 4.8 and 6.2 m2 for CASI hyperspectral and QuickBird panchromatic images, respectively. The olive crown volume was estimated using image‐estimated projected crown area values, yielding r 2 ranging between 0.87 and 0.70, with RMSE of 8.4 and 11.3 m3 for CASI hyperspectral and QuickBird panchromatic images, respectively. Olive crown transmittance and LAI of individual olive trees were evaluated using spectral vegetation indices (normalized difference vegetation index [NDVI], renormalized difference vegetation index [RDVI], simple ratio index [SR], modified simple ratio [MSR]) yielding better correlations with CASI images, r 2 in the range 0.71 to 0.75 (P < 0.0001) and 0.57 to 0.62 (P < 0.0001) for crown transmittance and LAI, respectively. These methods enable obtaining maps of biophysical parameters in olive trees at farm scale in an operational way demonstrating the validity of the methodology used.