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1
Trouillier, Mario, Marieke van der Maaten-Theunissen, Jill Harvey, David Würth, Martin Schnittler, and Martin Wilmking. "Visualizing Individual Tree Differences in Tree-Ring Studies." Forests 9, no. 4 (April 19, 2018): 216. http://dx.doi.org/10.3390/f9040216.
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Temesgen, Hailemariam, and Stephen J. Mitchell. "An Individual-Tree Mortality Model for Complex Stands of Southeastern British Columbia." Western Journal of Applied Forestry 20, no. 2 (April 1, 2005): 101–9. http://dx.doi.org/10.1093/wjaf/20.2.101.
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Abstract An individual-tree mortality model was developed for major tree species in complex stands (multi-cohort, multiaged, and mixed species) of southeastern British Columbia (BC), Canada. Data for 29,773 trees were obtained from permanent sample plots established in BC. Average annual diameter increment and mortality rates ranged from 0.08 to 0.17 cm/year and from 0.3 to 2.6%, respectively. Approximately 70% of the trees were used for model development and 30% for model evaluation. After evaluating the model, all 29,773 trees were used to fit the final model. A generalized logistic model was used to relate mortality to tree size, competition, and relative position of trees in a stand. The evaluation test demonstrated that the model appears to be well behaved and robust for the tree species considered in this study. For the eight tree species, the average deviation between observed and predicted annual mortality rates varied from −0.5 to 0.7% in the test data. West. J. Appl. For. 20(2):101–109.
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Hindell, MA, and AK Lee. "Tree Use by Individual Koalas in a Natural Forest." Wildlife Research 15, no. 1 (1988): 1. http://dx.doi.org/10.1071/wr9880001.
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The home ranges and species of trees used by 20 koalas (Phascolarctos cinereus) were determined in a forest in Victoria containing 6 Eucalyptus spp. Eight animals showed a preference for a tree species from those available within their home ranges. Four koalas preferred E. viminalis, 2 E. ovata and 2 E. macrorhyncha. Preference for tree species was detected only where the preferred species was in low abundance within the animal's home range. These observations confirm that koalas may show individual differences in the species of food trees they prefer. E. viminalis, the preferred species of this population, was the predominant tree species within the home range of 15 of the koalas, which may account for the lack of evidence of preference in the majority of animals.
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Qin, Jianhua, and Quang V. Cao. "Using disaggregation to link individual-tree and whole-stand growth models." Canadian Journal of Forest Research 36, no. 4 (April 1, 2006): 953–60. http://dx.doi.org/10.1139/x05-284.
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Data from 200 plots randomly selected from the Southwide Pine Seed Source Study of loblolly pine (Pinus taeda L.) were used to fit whole-stand and individual-tree equations. Another 100 plots, also randomly selected, were used for validation. Outputs from the individual-tree model were then adjusted to match observed stand attributes (number of trees, basal area, and volume per hectare) by four disaggregation methods: proportional yield, proportional growth, constrained least squares, and coefficient adjustment. The first three are existing methods, and the fourth is new. The four methods produced similar results, and the coefficient adjustment was then selected as the method to disaggregate predicted stand growth among trees in the tree list. Results showed that, compared to the unadjusted individual tree model, the adjusted tree model performed much better in predicting stand attributes, while providing comparable predictions of tree diameter, height, and survival probability. The proposed approach showed promise in the ongoing effort to link growth models having different resolutions.
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Yang, Yuqing, Shongming Huang, Shawn X. Meng, Guillermo Trincado, and Curtis L. VanderSchaaf. "A multilevel individual tree basal area increment model for aspen in boreal mixedwood stands." Canadian Journal of Forest Research 39, no. 11 (November 2009): 2203–14. http://dx.doi.org/10.1139/x09-123.
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Based on a multilevel nonlinear mixed model approach, a basal area increment model was developed for individual aspen ( Populus tremuloides Michx.) trees growing in boreal mixedwood stands in Alberta. Various stand and tree characteristics were evaluated for their contributions to model improvement. Total stand basal area, basal area of larger trees, and the ratio of target tree height to maximum stand height were found to be significant predictors. When random effects were modeled at the plot level alone, correlations among normalized residuals remained significant. These correlations were successfully removed when random effects were modeled at both plot and tree levels. The predictive abilities of two alternative models were evaluated at the population, plot, and tree levels. At the tree level, a tree measured at the first growth period was used for estimating random parameters, and basal area increments of that tree in future growth periods were subsequently predicted. At the plot level, one to five trees in each plot at each growth period were used to estimate random parameters. Basal area increments of the remaining trees in the same plot at the same growth period were subsequently predicted. The final model provided accurate predictions at all three levels.
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Mahour, Milad, Valentyn Tolpekin, and Alfred Stein. "Automatic Detection of Individual Trees from VHR Satellite Images Using Scale-Space Methods." Sensors 20, no. 24 (December 15, 2020): 7194. http://dx.doi.org/10.3390/s20247194.
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This research investigates the use of scale-space theory to detect individual trees in orchards from very-high resolution (VHR) satellite images. Trees are characterized by blobs, for example, bell-shaped surfaces. Their modeling requires the identification of local maxima in Gaussian scale space, whereas location of the maxima in the scale direction provides information about the tree size. A two-step procedure relates the detected blobs to tree objects in the field. First, a Gaussian blob model identifies tree crowns in Gaussian scale space. Second, an improved tree crown model modifies this model in the scale direction. The procedures are tested on the following three representative cases: an area with vitellaria trees in Mali, an orchard with walnut trees in Iran, and one case with oil palm trees in Indonesia. The results show that the refined Gaussian blob model improves upon the traditional Gaussian blob model by effectively discriminating between false and correct detections and accurately identifying size and position of trees. A comparison with existing methods shows an improvement of 10–20% in true positive detections. We conclude that the presented two-step modeling procedure of tree crowns using Gaussian scale space is useful to automatically detect individual trees from VHR satellite images for at least three representative cases.
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Forrester, David I. "Does individual-tree biomass growth increase continuously with tree size?" Forest Ecology and Management 481 (February 2021): 118717. http://dx.doi.org/10.1016/j.foreco.2020.118717.
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Foroozan, Zeynab, Jussi Grießinger, Kambiz Pourtahmasi, and Achim Bräuning. "Evaluation of Different Pooling Methods to Establish a Multi-Century δ18O Chronology for Paleoclimate Reconstruction." Geosciences 9, no. 6 (June 20, 2019): 270. http://dx.doi.org/10.3390/geosciences9060270.
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To develop multi-century stable isotope chronologies from tree rings, pooling techniques are applied to reduce laboratory costs and time. However, pooling of wood samples from different trees may have adverse effects on the signal amplitude in the final isotope chronology. We tested different pooling approaches to identify the method that is most cost-efficient, without compromising the ability of the final chronology to reflect long-term climate variability as well as climatic extreme years. As test material, we used δ18O data from juniper trees (Juniperus polycarpus) from Northern Iran. We compared inter-tree and shifted 5-year blocks serial pooling of stable isotope series from 5 individual trees and addition of one single series to a shifted serial pooled chronology. The inter-tree pooled chronology showed the strongest climate sensitivity and most synchronous δ18O variations with the individual tree ring analyses, while the shifted block chronologies showed a marked decline in high-frequency signals and no correlations with climate variables of the growth year. Combinations of block-pooled and single isotope series compensated the high-frequency decline but added tree-individual climatic signals. Therefore, we recommend pooling calendar synchronous tree rings from individual trees as a viable alternative to individual-tree isotope measurements for robust paleoclimate reconstructions.
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Shen, Guanghong, James A. Moore, and Charles R. Hatch. "The effect of habitat type and rock type on individual tree basal area growth response to nitrogen fertilization." Canadian Journal of Forest Research 30, no. 4 (April 1, 2000): 613–23. http://dx.doi.org/10.1139/x99-249.
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Individual tree basal area increment models for nitrogen fertilized stands were developed using data from permanent research plots located throughout the Inland Northwest. Results show that tree size, stand density, habitat type, and rock type significantly interact to affect individual tree basal area growth response to nitrogen fertilization. Suppressed trees growing on moist habitat types and all rock types, except metasedimentary, exhibited greater relative response than did dominant or codominant trees growing in the same stand. However, suppressed trees growing on dry sites or on soils derived from granite rocks did not show different relative response than dominant or codominant trees growing in the same stand. This study quantitatively demonstrates that individual tree competitive relationships are significantly affected by rock type. Rock types proved to be useful in representing broad differences in a site's nutrient environment. Incorporating the new equations into individual tree growth and yield simulators would provide better representation of N fertilization response differences within a stand.
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Williams, Roger A. "Use of Randomized Branch and Importance Sampling to Estimate Loblolly Pine Biomass." Southern Journal of Applied Forestry 13, no. 4 (November 1, 1989): 181–84. http://dx.doi.org/10.1093/sjaf/13.4.181.
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Abstract A previously developed sampling method utilizing randomized branch and importance sampling for the purpose of quickly estimating tree biomass was tested on five loblolly pine (Pinus taeda L.) trees. Results show a wide range of per-tree sampling error, ranging from 5.3 to 28.9%. Largevariation in foliage content among selected branches per treee may be a major source of error. However, the sampling error for the total biomass of the five trees tested was only 3.3%. This sampling method appears to be reliable and efficient in obtaining precise estimates of the total biomassof a population of trees. Increased sampling intensity per tree is necessary to obtain precise estimates of individual tree biomass. South. J. Appl. For. 13(4):181-184.
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Pitkänen, Juho. "Individual tree detection in digital aerial images by combining locally adaptive binarization and local maxima methods." Canadian Journal of Forest Research 31, no. 5 (May 1, 2001): 832–44. http://dx.doi.org/10.1139/x01-013.
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Locating local maxima of grey levels in aerial images was used for individual tree detection in boreal, closed forest conditions in southern Finland. Image smoothing and binarization were used as preprocessing steps. Binarization was used to restrict the local maxima searching to the bright areas of the images, which were assumed to be tree crowns. Because brightness variations are typical of aerial images, both within and among images, locally adaptive methods were suggested for binarization. Aerial digital camera images and mapped tree data of eight stands in three field plots were used. Four adaptive binarization methods were compared. Differences in tree detection accuracy were small even though the appearance of the binarized images were different. Image smoothing improved the results of tree detection in the three stands that had the largest mean tree size. Tree detection worked fairly well in all seven stands with a density of less than 1500 trees/ha. In these stands, 7095% of the trees were detected, whereas only 54% were detected in the last stand, which had a density of approximately 1900 trees/ha.
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Moradi, A., M. Satari, and M. Momeni. "INDIVIDUAL TREE OF URBAN FOREST EXTRACTION FROM VERY HIGH DENSITY LIDAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 9, 2016): 337–43. http://dx.doi.org/10.5194/isprsarchives-xli-b3-337-2016.
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Airborne LiDAR (Light Detection and Ranging) data have a high potential to provide 3D information from trees. Most proposed methods to extract individual trees detect points of tree top or bottom firstly and then using them as starting points in a segmentation algorithm. Hence, in these methods, the number and the locations of detected peak points heavily effect on the process of detecting individual trees. In this study, a new method is presented to extract individual tree segments using LiDAR points with 10cm point density. In this method, a two-step strategy is performed for the extraction of individual tree LiDAR points: finding deterministic segments of individual trees points and allocation of other LiDAR points based on these segments. This research is performed on two study areas in Zeebrugge, Bruges, Belgium (51.33° N, 3.20° E). The accuracy assessment of this method showed that it could correctly classified 74.51% of trees with 21.57% and 3.92% under- and over-segmentation errors respectively.
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Moradi, A., M. Satari, and M. Momeni. "INDIVIDUAL TREE OF URBAN FOREST EXTRACTION FROM VERY HIGH DENSITY LIDAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 9, 2016): 337–43. http://dx.doi.org/10.5194/isprs-archives-xli-b3-337-2016.
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Airborne LiDAR (Light Detection and Ranging) data have a high potential to provide 3D information from trees. Most proposed methods to extract individual trees detect points of tree top or bottom firstly and then using them as starting points in a segmentation algorithm. Hence, in these methods, the number and the locations of detected peak points heavily effect on the process of detecting individual trees. In this study, a new method is presented to extract individual tree segments using LiDAR points with 10cm point density. In this method, a two-step strategy is performed for the extraction of individual tree LiDAR points: finding deterministic segments of individual trees points and allocation of other LiDAR points based on these segments. This research is performed on two study areas in Zeebrugge, Bruges, Belgium (51.33° N, 3.20° E). The accuracy assessment of this method showed that it could correctly classified 74.51% of trees with 21.57% and 3.92% under- and over-segmentation errors respectively.
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Laforest-Lapointe, Isabelle, Christian Messier, and Steven W. Kembel. "Tree phyllosphere bacterial communities: exploring the magnitude of intra- and inter-individual variation among host species." PeerJ 4 (August 24, 2016): e2367. http://dx.doi.org/10.7717/peerj.2367.
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BackgroundThe diversity and composition of the microbial community of tree leaves (the phyllosphere) varies among trees and host species and along spatial, temporal, and environmental gradients. Phyllosphere community variation within the canopy of an individual tree exists but the importance of this variation relative to among-tree and among-species variation is poorly understood. Sampling techniques employed for phyllosphere studies include picking leaves from one canopy location to mixing randomly selected leaves from throughout the canopy. In this context, our goal was to characterize the relative importance of intra-individual variation in phyllosphere communities across multiple species, and compare this variation to inter-individual and interspecific variation of phyllosphere epiphytic bacterial communities in a natural temperate forest in Quebec, Canada.MethodsWe targeted five dominant temperate forest tree species including angiosperms and gymnosperms:Acer saccharum,Acer rubrum,Betula papyrifera,Abies balsameaandPicea glauca. For one randomly selected tree of each species, we sampled microbial communities at six distinct canopy locations: bottom-canopy (1–2 m height), the four cardinal points of mid-canopy (2–4 m height), and the top-canopy (4–6 m height). We also collected bottom-canopy leaves from five additional trees from each species.ResultsBased on an analysis of bacterial community structure measured via Illumina sequencing of the bacterial 16S gene, we demonstrate that 65% of the intra-individual variation in leaf bacterial community structure could be attributed to the effect of inter-individual and inter-specific differences while the effect of canopy location was not significant. In comparison, host species identity explains 47% of inter-individual and inter-specific variation in leaf bacterial community structure followed by individual identity (32%) and canopy location (6%).DiscussionOur results suggest that individual samples from consistent positions within the tree canopy from multiple individuals per species can be used to accurately quantify variation in phyllosphere bacterial community structure. However, the considerable amount of intra-individual variation within a tree canopy ask for a better understanding of how changes in leaf characteristics and local abiotic conditions drive spatial variation in the phyllosphere microbiome.
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Cosenza, Diogo Nepomuceno, Vicente Paulo Soares, Helio Garcia Leite, José Marinaldo Gleriani, Cibele Hummel do Amaral, Joel Gripp Júnior, Antonilmar Araújo Lopes da Silva, Paula Soares, and Margarida Tomé. "Airborne laser scanning applied to eucalyptus stand inventory at individual tree level." Pesquisa Agropecuária Brasileira 53, no. 12 (December 2018): 1373–82. http://dx.doi.org/10.1590/s0100-204x2018001200010.
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Abstract: The objective of this work was to evaluate the application of airborne laser scanning (ALS) to a large-scale eucalyptus stand inventory by the method of individual trees, as well as to propose a new method to estimate tree diameter as a function of the height obtained from point clouds. The study was carried out in a forest area of 1,681 ha, consisting of eight eucalyptus stands with ages varying from four to seven years. After scanning, tree heights were obtained using the local maxima algorithm, and total wood stock by summing up individual volumes. To determine tree diameters, regressions fit using data measured in the inventory plots were used. The results were compared with the estimates obtained from field sampling. The equation system proposed is adequate to be applied to the tree height data derived from ALS point clouds. The tree individualization approach by local maxima filters is efficient to estimate number of trees and wood stock from ALS data, as long as the results are previously calibrated with field data.
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Kempf, Christian, Jiaojiao Tian, Franz Kurz, Pablo D’Angelo, Thomas Schneider, and Peter Reinartz. "Oblique view individual tree crown delineation." International Journal of Applied Earth Observation and Geoinformation 99 (July 2021): 102314. http://dx.doi.org/10.1016/j.jag.2021.102314.
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Tahar, K. N., M. A. Asmadin, S. A. H. Sulaiman, N. Khalid, A. N. Idris, and M. H. Razali. "Individual Tree Crown Detection Using UAV Orthomosaic." Engineering, Technology & Applied Science Research 11, no. 2 (April 11, 2021): 7047–53. http://dx.doi.org/10.48084/etasr.4093.
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Unmanned Aerial Vehicles (UAVs) are increasingly used in forestry as they are economical and flexible. This study aims to present the advantages of the drone photogrammetry method in collecting individual tree crowns, as individual tree crown detection could deliver essential ecological and economic information. The referred accuracy for individual tree crown extraction is 79.2%. Only crowns that were clearly visible were selected and manually delineated on the image because the distribution of the true crown size is significantly different from the segmented crowns. The aim of this study is to investigate UAVs orthomosaics in individual tree crown detection. The objectives of this study are to produce the orthomosaic of tree crown extraction mapping using the Pix4D software and analyze the tree crowns using tree crown delineation and the OBIA algorithm. Data processing involves the processing of aerial images using Pix4Dmapper. Automatic tree crown detection involves a tree crown delineation algorithm and OBIA operations to process the tree crown extraction. The crown delineation algorithm and OBIA algorithm operation will be compared to the actual tree crown measurement in terms of diameter and area. The tree crown delineation method obtained a 0.347m mean diameter difference from the actual tree crown diameter, while the OBIA approach obtained 4.98m. The tree crown delineation method obtained 97.26% of the actual tree crown area, while OBIA obtained 91.74%.
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Bian, Yan Shan, Ling Da Wu, Rong Huan Yu, and Zhi Ke Chen. "Individual Tree Detection from High Spatial Resolution Imagery Using Color and Texture Features." Applied Mechanics and Materials 519-520 (February 2014): 703–7. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.703.
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An automatic individual tree detection method from pure image is proposed. Color and texture features are selected to form a vector for a pixel-level classification, then trained to assign a label to each pixel. Other features can be integrated into the pixel vector for extracting more information of trees. An ensemble method combining multiple logistic regression classifiers improves effectiveness of the single pixel-level classifier. Then spectral, shape and knowledge characteristics of individual tree crowns are used for tree top localization. At last, tree crowns are delineated by region-based algorithm.
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Maschler, Julia, Clement Atzberger, and Markus Immitzer. "Individual Tree Crown Segmentation and Classification of 13 Tree Species Using Airborne Hyperspectral Data." Remote Sensing 10, no. 8 (August 3, 2018): 1218. http://dx.doi.org/10.3390/rs10081218.
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Knowledge of the distribution of tree species within a forest is key for multiple economic and ecological applications. This information is traditionally acquired through time-consuming and thereby expensive field work. Our study evaluates the suitability of a visible to near-infrared (VNIR) hyperspectral dataset with a spatial resolution of 0.4 m for the classification of 13 tree species (8 broadleaf, 5 coniferous) on an individual tree crown level in the UNESCO Biosphere Reserve ‘Wienerwald’, a temperate Austrian forest. The study also assesses the automation potential for the delineation of tree crowns using a mean shift segmentation algorithm in order to permit model application over large areas. Object-based Random Forest classification was carried out on variables that were derived from 699 manually delineated as well as automatically segmented reference trees. The models were trained separately for two strata: small and/or conifer stands and high broadleaf forests. The two strata were delineated beforehand using CHM-based tree height and NDVI. The predictor variables encompassed spectral reflectance, vegetation indices, textural metrics and principal components. After feature selection, the overall classification accuracy (OA) of the classification based on manual delineations of the 13 tree species was 91.7% (Cohen’s kappa (κ) = 0.909). The highest user’s and producer’s accuracies were most frequently obtained for Weymouth pine and Scots Pine, while European ash was most often associated with the lowest accuracies. The classification that was based on mean shift segmentation yielded similarly good results (OA = 89.4% κ = 0.883). Based on the automatically segmented trees, the Random Forest models were also applied to the whole study site (1050 ha). The resulting tree map of the study area confirmed a high abundance of European beech (58%) with smaller amounts of oak (6%) and Scots pine (5%). We conclude that highly accurate tree species classifications can be obtained from hyperspectral data covering the visible and near-infrared parts of the electromagnetic spectrum. Our results also indicate a high automation potential of the method, as the results from the automatically segmented tree crowns were similar to those that were obtained for the manually delineated tree crowns.
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Shahidan, Mohd. "Potential of Individual and Cluster Tree Cooling Effect Performances Through Tree Canopy Density Model Evaluation in Improving Urban Microclimate." Current World Environment 10, no. 2 (August 24, 2015): 398–413. http://dx.doi.org/10.12944/cwe.10.2.04.
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Technically, trees can provide cooling effect and able to reduce ambient temperature in its own way. This paper investigates the potential of individual and cluster tree cooling effect performances in improving urban microclimate through the evaluation of urban trees canopy density. The evaluation is based on the actual measurement of Leaf Area Index (LAI) and Leaf Area Density (LAD) and uses tested computer simulation tools ENVI-met. The study found that each tree has different capabilities in modifying each microclimate variables. However, it was revealed that the optimum effect of cooling of each tree was found during the hottest day to takes place approximately at 15:00 hours when the sun is overhead and solar angle height is close to 90°. Besides, trees with higher densities such as Ficus benjamina (i.e. LAI 9.7, LAD > 1.5) showed a remarkable reduction in comparison to the other loose density trees. It is also revealed that the implementation of cluster tree planting at larger scale could maximize the effects of cooling. Nevertheless, the downside of implementing high tree density could create a reduction of 63% of wind speed that might possibly influence the air movement in urban areas due to the drag force of tree canopy. The study concluded that the performance of tree cooling effect is well correlated with tree canopy density and it is also suggested the optimum cooling effect could achieved by higher tree density (mean LAD > 1.5) and larger tree quantities with tree cluster planting.
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Newberry, James D., Harold E. Burkhart, and Ralph L. Amateis. "Individual tree merchantable volume to total volume ratios based on geometric solids." Canadian Journal of Forest Research 19, no. 5 (May 1, 1989): 679–83. http://dx.doi.org/10.1139/x89-105.
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Individual tree volume ratio equations were developed on the basis of the volume formulas of certain geometric solids. Two parameter-free and two parameterized models were formulated, based on different basal diameters. The parameter-free models should be useful when few individual tree volume ratio data exist for a given species or for a particular population of trees. The parameterized models are appropriate, of course, to those situations where volume ratio data exist. The parameter-free models performed as well as the parameterized models in the upper half of the tree stem for the loblolly pine data used for comparison. The parameterized models performed well all along the tree stem.
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Ram P, Sharma, Vacek Zdeněk, Vacek Stanislav, Jansa Václav, and Kučera Miloš. "Modelling individual tree diameter growth for Norway spruce in the Czech Republic using a generalized algebraic difference approach." Journal of Forest Science 63, No. 5 (May 26, 2017): 227–38. http://dx.doi.org/10.17221/135/2016-jfs.
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Individual tree-based growth models precisely describe the growth of individual trees irrespective of stand complexity. These models are more useful than the stand-based growth models for effective management of forests. We developed an individual tree diameter growth model for Norway spruce (Picea abies /Linnaeus/ H. Karsten) using permanent research plot data collected from Krkonoše National Park in the Czech Republic. The model was tested against a part of the Czech National Forest Inventory (NFI) data that originated from the western region of the country. Among various models derived by a generalized algebraic difference approach (GADA), the GADA model derived from the Chapman-Richards function best suited to our data. Tree-specific parameters unique to each growth series, which describe tree-specific growth conditions, were estimated simultaneously with global parameters common to all growth series using the iterative nested regressions. The model described most of the variations in diameter growth for model calibration data (R<sup>2</sup><sub>adj</sub> = 0.9901, RMSE = 0.5962), leaving no significant trends in the residuals. A test against NFI data also confirms that the model is precise enough for predictions of diameter growth for ranges of site quality, tree size, age, and growth condition. The model also possesses biologically desirable properties because it produces the curves with growth rates and asymptotes that increase with increasing site quality. The GADA model is path-invariant and therefore applicable for both forward and backward predictions, meaning that the model can precisely predict diameter growth at any past ages of the trees.
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Zhang, Lianjun, Changhui Peng, and Qinglai Dang. "Individual-tree basal area growth models for jack pine and black spruce in northern Ontario." Forestry Chronicle 80, no. 3 (June 1, 2004): 366–74. http://dx.doi.org/10.5558/tfc80366-3.
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Individual-tree models of five-year basal area growth were developed for jack pine (Pinus banksiana Lamb.) and black spruce (Picea mariana (Mill.) BSP) in northern Ontario. Tree growth data were collected from long-term permanent plots of pure and mixed stands of the two species. The models were fitted using mixed model methods due to correlated remeasurements of tree growth over time. Since the data covered a wide range of stand ages, stand conditions and tree sizes, serious heterogeneous variances existed in the data. Therefore, the coefficients of the final models were obtained using weighted regression techniques. The models for the two species were evaluated across 4-cm diameter classes using independent data. The results indicated (1) the models of jack pine and black spruce produced similar prediction errors and biases for intermediate-sized trees (1228 cm in tree diameter), (2) both models yielded relatively large errors and biases for larger trees (> 28 cm) than those for smaller trees, and (3) the jack pine model produced much larger errors and biases for small-sized trees (< 12 cm) than did the black spruce model. Key words: mixed models, repeated measures, model validation
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Woodall, C. W., C. E. Fiedler, and K. S. Milner. "Intertree competition in uneven-aged ponderosa pine stands." Canadian Journal of Forest Research 33, no. 9 (September 1, 2003): 1719–26. http://dx.doi.org/10.1139/x03-096.
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Intertree competition indices and effects were examined in 14 uneven-aged ponderosa pine (Pinus ponderosa var. scopulorum Engelm.) stands in eastern Montana. Location, height, diameter at breast height (DBH), basal area increment, crown ratio, and sapwood area were determined for each tree (DBH >3.8 cm) on one stem-mapped plot (0.2-0.4 ha) in each sample stand. Based on tree locations, various competition indices were derived for each sample tree and correlated with its growth efficiency by diameter class. In addition, trends in individual tree attributes by diameter class and level of surrounding competition were determined. For trees with a DBH <10 cm, growth efficiency was most strongly correlated with the sum of surrounding tree heights within 10.6 m. The index most highly correlated for larger trees was the sum of surrounding basal area within 6.1 m. Regardless of tree size, individual tree growth efficiency, basal area increment, and crown ratio all decreased under increasing levels of competition, with the effect more pronounced in smaller trees. These results suggest that individual trees in uneven-aged stands experience competition from differing sources at varying scales based on their size, with response to competition diminishing as tree size increases.
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Gillespie, Andrew R., and Harold W. Hocker Jr. "The influence of competition on individual white pine thinning response." Canadian Journal of Forest Research 16, no. 6 (December 1, 1986): 1355–59. http://dx.doi.org/10.1139/x86-239.
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A model predicting white pine (Pinusstrobus L.) diameter growth after thinning included competition, initial diameter, and crown class as independent variables. Model coefficients indicated a decrease in percent 8-year diameter growth with increasing crown suppression, crown competition, or tree size class. Variables selected were superior to age, percent live crown, and prethinning growth. Equations predicting basal area and volume growth were similar in form to diameter growth. Height growth, however, was more closely correlated with crown characteristics and unaffected by competition. Annual growth patterns were similar to periodic growth patterns, revealing decreased growth with increasing competition or crown suppression. Trees having little competition and dominant crowns utilized their growing season longer, with earlier initial growth and faster growth than trees having greater competition or crown suppression. Within a crown class, diameter growth decreased as competition increased. Individual tree competition was seen as the most important factor influencing tree growth that a forester can control.
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Naveed, F., and B. Hu. "INDIVIDUAL TREE CROWN DELINEATION USING MULTI-WAVELENGTH TITAN LIDAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W3 (October 19, 2017): 143–48. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w3-143-2017.
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The inability to detect the Emerald Ash Borer (EAB) at an early stage has led to the enumerable loss of different species of ash trees. Due to the increasing risk being posed by the EAB, a robust and accurate method is needed for identifying Individual Tree Crowns (ITCs) that are at a risk of being infected or are already diseased. This paper attempts to outline an ITC delineation method that employs airborne multi-spectral Light Detection and Ranging (LiDAR) to accurately delineate tree crowns. The raw LiDAR data were initially pre-processed to generate the Digital Surface Models (DSM) and Digital Elevation Models (DEM) using an iterative progressive TIN (Triangulated Irregular Network) densification method. The DSM and DEM were consequently used for Canopy Height Model (CHM) generation, from which the structural information pertaining to the size and shape of the tree crowns was obtained. The structural information along with the spectral information was used to segment ITCs using a region growing algorithm. The availability of the multi-spectral LiDAR data allows for delineation of crowns that have otherwise homogenous structural characteristics and hence cannot be isolated from the CHM alone. This study exploits the spectral data to derive initial approximations of individual tree tops and consequently grow those regions based on the spectral constraints of the individual trees.
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Akpo, Hospice A., Gilbert Atindogbé, Maxwell C. Obiakara, Arios B. Adjinanoukon, Madaï Gbedolo, Philippe Lejeune, and Noël H. Fonton. "Image Data Acquisition for Estimating Individual Trees Metrics: Closer Is Better." Forests 11, no. 1 (January 19, 2020): 121. http://dx.doi.org/10.3390/f11010121.
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Background and Objectives: The recent use of Structure-from-Motion with Multi-View Stereo photogrammetry (SfM-MVS) in forestry has underscored its robustness in tree mensuration. This study evaluated the differences in tree metrics resulting from various related SfM-MVS photogrammetric image acquisition scenarios. Materials and Methods: Scaled tri-dimensional models of 30 savanna trees belonging to five species were built from photographs acquired in a factorial design with shooting distance (d = 1, 2, 3, 4 and 5 m away from tree) and angular shift (α = 15°, 30°, 45° and 60°; nested in d). Tree stem circumference at 1.3 m and bole volume were estimated using models resulting from each of the 20 scenarios/tree. Mean absolute percent error (MAPE) was computed for both metrics in order to compare the performance of each scenario in relation to reference data collected using a measuring tape. Results: An assessment of the effect of species identity (s), shooting distance and angular shift showed that photographic point cloud density was dependent on α and s, and optimal for 15° and 30°. MAPEs calculated on stem circumferences and volumes significantly differed with d and α, respectively. There was a significant interaction between α and s for both circumference and volume MAPEs, which varied widely (1.6 ± 0.4%–20.8 ± 23.7% and 2.0 ± 0.6%–36.5 ± 48.7% respectively), and were consistently lower for smaller values of d and α. Conclusion: The accuracy of photogrammetric estimation of individual tree attributes depended on image-capture approach. Acquiring images 2 m away and with 30° intervals around trees produced reliable estimates of stem circumference and bole volume. Research Highlights: This study indicates that the accuracy of photogrammetric estimations of individual tree attributes is species-dependent. Camera positions in relation to the subject substantially influence the level of uncertainty in measurements.
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Maltamo, M., K. Mustonen, J. Hyyppä, J. Pitkänen, and X. Yu. "The accuracy of estimating individual tree variables with airborne laser scanning in a boreal nature reserve." Canadian Journal of Forest Research 34, no. 9 (September 1, 2004): 1791–801. http://dx.doi.org/10.1139/x04-055.
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This study examines the ability of high-density laser scanning to produce single-tree estimates in mixed stands of heterogeneous structure. Individual trees were detected from a constructed digital canopy height model by locating local maxima of the height values. The reference material comprised accurately measured field data for 10 mapped sample plots containing Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and different birches. To verify the accuracy of height measurements of single trees in more detail, the height of 29 Scots pine trees and their annual shoots of the last few years was carefully measured with a tacheometer and a glass fibre rod. The considered variables were the proportion of detected trees and tree height. As more than 80% of the dominant trees were detected, the results indicated that laser scanning can accurately describe the trees of the dominant tree layer. Because of the dense understorey tree layer in most of the sample plots, about 40% of all trees were detected. On the plot level, the stand structure affected the accuracy of the results considerably. The scanning-based tree height was most accurate for Norway spruce and least accurate for birches. The height of the separately measured 29 Scots pine trees was obtained with an accuracy of ±50 cm or better.
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Buchanan, Megan L., and Justin L. Hart. "A methodological analysis of canopy disturbance reconstructions using Quercus alba." Canadian Journal of Forest Research 41, no. 6 (June 2011): 1359–67. http://dx.doi.org/10.1139/x11-057.
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Forest disturbance history reconstructions in the eastern US commonly rely on the analysis of a single tree-ring series per individual. However, this method can result in an underrepresentation of radial growth releases and canopy disturbance events. We analyzed paired tree-ring series from 884 Quercus alba L. individuals to quantify discrepant patterns of intratree release frequency, magnitude, and initiation years. We also developed a model for Q. alba that accounts for this underrepresentation of releases. Of the 884 trees analyzed, 216 exhibited radial growth releases. Only 13 of these 216 trees recorded the same canopy disturbance events in both series. Through analysis of a single growth-ring series per tree, a minimum of 39 and a maximum of 241 releases could be detected from the trees in the data set. Of the total number of release events, 238 (85%) occurred only in one of the paired tree-ring series. For stand development studies requiring the frequency of canopy disturbance alone, a multiplicative factor of 1.72 can provide the information necessary without deviating from the standard practice in the eastern US of collecting and analyzing a single increment core per tree. Studies requiring spatially and temporally explicit information regarding disturbance should extract and analyze two or more tree-ring series per individual.
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Dong, Xinyu, Zhichao Zhang, Ruiyang Yu, Qingjiu Tian, and Xicun Zhu. "Extraction of Information about Individual Trees from High-Spatial-Resolution UAV-Acquired Images of an Orchard." Remote Sensing 12, no. 1 (January 1, 2020): 133. http://dx.doi.org/10.3390/rs12010133.
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The extraction of information about individual trees is essential to supporting the growing of fruit in orchard management. Data acquired from spectral sensors mounted on unmanned aerial vehicles (UAVs) have very high spatial and temporal resolution. However, an efficient and reliable method for extracting information about individual trees with irregular tree-crown shapes and a complicated background is lacking. In this study, we developed and tested the performance of an approach, based on UAV imagery, to extracting information about individual trees in an orchard with a complicated background that includes apple trees (Plot 1) and pear trees (Plot 2). The workflow involves the construction of a digital orthophoto map (DOM), digital surface models (DSMs), and digital terrain models (DTMs) using the Structure from Motion (SfM) and Multi-View Stereo (MVS) approaches, as well as the calculation of the Excess Green minus Excess Red Index (ExGR) and the selection of various thresholds. Furthermore, a local-maxima filter method and marker-controlled watershed segmentation were used for the detection and delineation, respectively, of individual trees. The accuracy of the proposed method was evaluated by comparing its results with manual estimates of the numbers of trees and the areas and diameters of tree-crowns, all three of which parameters were obtained from the DOM. The results of the proposed method are in good agreement with these manual estimates: The F-scores for the estimated numbers of individual trees were 99.0% and 99.3% in Plot 1 and Plot 2, respectively, while the Producer’s Accuracy (PA) and User’s Accuracy (UA) for the delineation of individual tree-crowns were above 95% for both of the plots. For the area of individual tree-crowns, root-mean-square error (RMSE) values of 0.72 m2 and 0.48 m2 were obtained for Plot 1 and Plot 2, respectively, while for the diameter of individual tree-crowns, RMSE values of 0.39 m and 0.26 m were obtained for Plot 1 (339 trees correctly identified) and Plot 2 (203 trees correctly identified), respectively. Both the areas and diameters of individual tree-crowns were overestimated to varying degrees.
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Lejeune, P. "Développement d'un modèle de type arbre appliqué à la croissance des peuplements feuillus irréguliers du sud de la Belgique." Canadian Journal of Forest Research 26, no. 10 (October 1, 1996): 1838–48. http://dx.doi.org/10.1139/x26-209.
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A model predicting circumference growth of individual trees has been developed for mixed irregular stands dominated by Fagussilvatica L. in southeastern Belgium. This model integrates simultaneously tree, stand, and growing site characteristics without considering distances between individual trees. It has a determination coefficient of 40.1% and a residual standard deviation of 0.45 cm/year. Forest mensuration variables considered in the model are circumference, tree social position represented by the total basal area of trees greater than the subject tree, stand basal area, and some index of stand structure corresponding to the ratio of the variance over the mean circumference. The site component is essentially expressed by the length of the growing period. The low accuracy obtained for individual tree growth is relative because the results are used mainly after individual trees have been distributed into size classes. We have been able to show that the introduction of crown description in the model can increase its accuracy. But this modification requires a submodel describing crown changes over time.
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APOSTOL, Bogdan, Adrian LORENT, Marius PETRILA, Vladimir GANCZ, and Ovidiu BADEA. "Height Extraction and Stand Volume Estimation Based on Fusion Airborne LiDAR Data and Terrestrial Measurements for a Norway Spruce [Picea abies (L.) Karst.] Test Site in Romania." Notulae Botanicae Horti Agrobotanici Cluj-Napoca 44, no. 1 (June 14, 2016): 313–23. http://dx.doi.org/10.15835/nbha44110155.
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The objective of this study was to analyze the efficiency of individual tree identification and stand volume estimation from LiDAR data. The study was located in Norway spruce [Picea abies (L.) Karst.] stands in southwestern Romania and linked airborne laser scanning (ALS) with terrestrial measurements through empirical modelling. The proposed method uses the Canopy Maxima algorithm for individual tree detection together with biometric field measurements and individual trees positioning. Field data was collected using Field-Map real-time GIS-laser equipment, a high-accuracy GNSS receiver and a Vertex IV ultrasound inclinometer. ALS data were collected using a Riegl LMS-Q560 instrument and processed using LP360 and Fusion software to extract digital terrain, surface and canopy height models. For the estimation of tree heights, number of trees and tree crown widths from the ALS data, the Canopy Maxima algorithm was used together with local regression equations relating field-measured tree heights and crown widths at each plot. When compared to LiDAR detected trees, about 40-61% of the field-measured trees were correctly identified. Such trees represented, in general, predominant, dominant and co-dominant trees from the upper canopy. However, it should be noted that the volume of the correctly identified trees represented 60-78% of the total plot volume. The estimation of stand volume using the LiDAR data was achieved by empirical modelling, taking into account the individual tree heights (as identified from the ALS data) and the corresponding ground reference stem volume. The root mean square error (RMSE) between the individual tree heights measured in the field and the corresponding heights identified in the ALS data was 1.7-2.2 meters. Comparing the ground reference estimated stem volume (at trees level) with the corresponding ALS estimated tree stem volume, an RMSE of 0.5-0.7 m3 was achieved. The RMSE was slightly lower when comparing the ground reference stem volume at plot level with the ALS-estimated one, taking into account both the identified and unidentified trees in the LiDAR data (0.4-0.6 m3).
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Medlyn, B. E., D. A. Pepper, A. P. O'Grady, and H. Keith. "Linking leaf and tree water use with an individual-tree model." Tree Physiology 27, no. 12 (December 1, 2007): 1687–99. http://dx.doi.org/10.1093/treephys/27.12.1687.
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Comas, C., L. Mehtätalo, and J. Miina. "Analysing space–time tree interdependencies based on individual tree growth functions." Stochastic Environmental Research and Risk Assessment 27, no. 7 (April 8, 2013): 1673–81. http://dx.doi.org/10.1007/s00477-013-0704-3.
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Tomșa, Vlăduț Remus, Alexandru Lucian Curtu, and Mihai Daniel Niță. "Tree Shape Variability in a Mixed Oak Forest Using Terrestrial Laser Technology: Implications for Mating System Analysis." Forests 12, no. 2 (February 22, 2021): 253. http://dx.doi.org/10.3390/f12020253.
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The accuracy of the description regarding tree architecture is crucial for data processing. LiDAR technology is an efficient solution for capturing the characteristics of individual trees. The aim of the present study was to analyze tree shape variability in a mixed oak forest consisting of four European white oak species: Quercus petraea, Q. frainetto, Q. pubescens, and Q. robur. Moreover, we tested for association between tree shape and individual heterozygosity and whether oak trees identified as pollen donors in a previous genetic study have a larger size in terms of crown and trunk characteristics than non-donors. The woody structure of a tree was defined by the quantitative structure model (QSM) providing information about topology (branching structure), geometry, and volume. For extracting the 3D point clouds a high-speed 3D scanner (FARO FocusS 70) was used. The crown variables were strongly correlated to each other, the branch volume being influenced by branch length, maximum branch order, and the number of branches but not influenced by diameter at breast height (DBH), trunk length, trunk volume, or tree height. There was no relationship between the individual heterozygosity based on nuclear microsatellite genetic markers and crown and trunk characteristics, respectively. Branch volume, total area, DBH, trunk volume, and the total volume of tree were significantly larger in pollen donors compared to non-donor Q. petraea trees. Thus, the mean branch volume was more than three times higher. Pollen donors had nearly two and half times larger total area in comparison to non-donor individuals. Our results suggest that a thorough characterization of tree phenotype using terrestrial laser scanning may contribute to a better understanding of mating system patterns in oak forests.
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Mendes, Fábio K., Andrew P. Livera, and Matthew W. Hahn. "The perils of intralocus recombination for inferences of molecular convergence." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1777 (June 3, 2019): 20180244. http://dx.doi.org/10.1098/rstb.2018.0244.
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Accurate inferences of convergence require that the appropriate tree topology be used. If there is a mismatch between the tree a trait has evolved along and the tree used for analysis, then false inferences of convergence (‘hemiplasy’) can occur. To avoid problems of hemiplasy when there are high levels of gene tree discordance with the species tree, researchers have begun to construct tree topologies from individual loci. However, due to intralocus recombination, even locus-specific trees may contain multiple topologies within them. This implies that the use of individual tree topologies discordant with the species tree can still lead to incorrect inferences about molecular convergence. Here, we examine the frequency with which single exons and single protein-coding genes contain multiple underlying tree topologies, in primates and Drosophila , and quantify the effects of hemiplasy when using trees inferred from individual loci. In both clades, we find that there are most often multiple diagnosable topologies within single exons and whole genes, with 91% of Drosophila protein-coding genes containing multiple topologies. Because of this underlying topological heterogeneity, even using trees inferred from individual protein-coding genes results in 25% and 38% of substitutions falsely labelled as convergent in primates and Drosophila , respectively. While constructing local trees can reduce the problem of hemiplasy, our results suggest that it will be difficult to completely avoid false inferences of convergence. We conclude by suggesting several ways forward in the analysis of convergent evolution, for both molecular and morphological characters. This article is part of the theme issue ‘Convergent evolution in the genomics era: new insights and directions’.
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Shokirov, Shukhrat, and Géza Király. "Analysis of multitemporal aerial images for fenyőfő Forest change detection." Landscape & Environment 10, no. 2 (October 14, 2016): 89–100. http://dx.doi.org/10.21120/le/10/2/4.
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This study evaluated the use of 40 cm spatial resolution aerial images for individual tree crown delineation, forest type classification, health estimation and clear-cut area detection in Fenyőfő forest reserves in 2012 and 2015 years. Region growing algorithm was used for segmentation of individual tree crowns. Forest type (coniferous/deciduous trees) were distinguished based on the orthomosaic images and segments. Research also investigated the height of individual trees, clear-cut areas and cut crowns between 2012 and 2015 years using Canopy Height Models. Results of the research were examined based on the field measurement data. According to our results, we achieved 75.2% accuracy in individual tree crown delineation. Heights of tree crowns have been calculated with 88.5% accuracy. This study had promising result in clear cut area and individual cut crown detection. Overall accuracy of classification was 77.2%, analysis showed that coniferous tree type classification was very accurate, but deciduous tree classification had a lot of omission errors. Based on the results and analysis, general information about forest health conditions has been presented. Finally, strengths and limitations of the research were discussed and recommendations were given for further research.
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Shafii, Bahman, James A. Moore, and James D. Newberry. "Individual-tree diameter growth models for quantifying within-stand response to nitrogen fertilization." Canadian Journal of Forest Research 20, no. 8 (August 1, 1990): 1149–55. http://dx.doi.org/10.1139/x90-153.
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Diameter-increment models for nitrogen-fertilized stands were developed using data from permanent research plots in northern Idaho. The equations partially resembled PROGNOSIS model diameter growth formulations. Results indicated that both initial tree size and initial stand density produced significant interactions with treatment to explain an individual tree's response to fertilization. Larger trees in a stand showed more fertilization response than smaller trees. Furthermore, individual trees in low-density stands showed more fertilization response than those growing in high-density stands. These diameter increment predictive equations were formulated to be compatible with individual-tree distance-independent simulation models.
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Pérez-Cruzado, César, Christoph Kleinn, Paul Magdon, Juan Gabriel Álvarez-González, Steen Magnussen, Lutz Fehrmann, and Nils Nölke. "The Horizontal Distribution of Branch Biomass in European Beech: A Model Based on Measurements and TLS Based Proxies." Remote Sensing 13, no. 5 (March 9, 2021): 1041. http://dx.doi.org/10.3390/rs13051041.
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Forest biomass is currently among the most important and most researched target variables in forest monitoring. The common approach of observing individual tree biomass in forest inventory is to assign the total tree biomass to the dimensionless point of the tree position. However, the tree biomass, in particular in the crown, is horizontally distributed above the crown projection area. This horizontal distribution of individual tree biomass (HBD) has not attracted much attention—but if quantified, it can improve biomass estimation and help to better represent the spatial distribution of forest fuel. In this study, we derive a first empirical model of the branch HBD for individual trees of European beech (Fagus sylvatica L.). We destructively measured 23 beech trees to derive an empirical model for the branch HBD. We then applied Terrestrial Laser Scanning (TLS) to a subset of 17 trees to test a simple point cloud metric predicting the branch HBD. We observed similarities between a branch HBD and commonly applied taper functions, which inspired our HBD model formulations. The models performed well in representing the HBD both for the measured biomass, and the TLS-based metric. Our models may be used as first approximations to the HBD of individual trees—while our methodological approach may extend to trees of different sizes and species.
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Zhang, X., and Y. Lei. "A linkage among whole-stand model, individual-tree model and diameter-distribution model." Journal of Forest Science 56, No. 12 (December 17, 2010): 600–608. http://dx.doi.org/10.17221/102/2009-jfs.
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Stand growth and yield models include whole-stand models, individual-tree models and diameter-distribution models. In this study, the three models were linked by forecast combination and parameter recovery methods one after another. Individual-tree models combine with whole-stand models through forecast combination. Forecast combination method combines information from different models, disperses errors generated from different models, and then improves forecast accuracy. And then the forecast combination model was linked to diameter-distribution models via parameter recovery methods. During the moment estimation, two methods were used, arithmetic mean diameter and quadratic mean diameter method (A-Q method), and arithmetic mean diameter and diameter variance method (A-V method). Results showed that the forecast combination for predicting stand variables outperformed over the stand-level and tree-level models respectively; A-V method was superior to A-Q method on estimating Weibull parameters; these three different models could be linked very well via forecast combination and parameter recovery.
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Ramos, Soledad, Francisco M. Vázquez, and Trinidad Ruiz. "Ecological Implications of Acorn Size at the Individual Tree Level in Quercus suber L." ISRN Botany 2013 (August 5, 2013): 1–6. http://dx.doi.org/10.1155/2013/310828.
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Few studies have determined the influence of acorn size on germination and predation percentage at tree level. To evaluate the seed size influence at individual tree level, trees producing two different sizes of acorn were chosen. Our results show that smaller acorns were significantly more infested (49.6–75.3%) than larger ones (11.0–27.33%). About germination, big acorns achieved the best germination percentage compared to the smaller ones (18% in infested and 76% in sound acorns for the small acorn group versus 69.3% in infested and 93.3% in sound acorns belonging to the big acorn group). We also found that there was a difference in behaviour between big and small seeds at tree level. The same size belonging to different functional groups presented a difference at the behavioural level per tree. Infested small acorns from trees 8 and 10 had only 33 and 13% germination, while big acorns from trees 2, 3, and 6 (there was no difference between both sizes) presented 67, 97, and 83%, respectively. These results indicate that the production of acorns with two different sizes could be a strategy for species regeneration, producing each size for a different purpose.
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Jiao, Jichao, and Zhongliang Deng. "Individual Building Rooftop and Tree Crown Segmentation from High-Resolution Urban Aerial Optical Images." Journal of Sensors 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/1795205.
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We segment buildings and trees from aerial photographs by using superpixels, and we estimate the tree’s parameters by using a cost function proposed in this paper. A method based on image complexity is proposed to refine superpixels boundaries. In order to classify buildings from ground and classify trees from grass, the salient feature vectors that include colors, Features from Accelerated Segment Test (FAST) corners, and Gabor edges are extracted from refined superpixels. The vectors are used to train the classifier based on Naive Bayes classifier. The trained classifier is used to classify refined superpixels as object or nonobject. The properties of a tree, including its locations and radius, are estimated by minimizing the cost function. The shadow is used to calculate the tree height using sun angle and the time when the image was taken. Our segmentation algorithm is compared with other two state-of-the-art segmentation algorithms, and the tree parameters obtained in this paper are compared to the ground truth data. Experiments show that the proposed method can segment trees and buildings appropriately, yielding higher precision and better recall rates, and the tree parameters are in good agreement with the ground truth data.
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Jurado, J., M. Ramos, C. Enríquez, and F. Feito. "The Impact of Canopy Reflectance on the 3D Structure of Individual Trees in a Mediterranean Forest." Remote Sensing 12, no. 9 (May 1, 2020): 1430. http://dx.doi.org/10.3390/rs12091430.
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The characterization of 3D vegetation structures is an important topic, which has been addressed by recent research in remote sensing. The forest inventory requires the proper extraction of accurate structural and functional features of individual trees. This paper presents a novel methodology to study the impact of the canopy reflectance on the 3D tree structure. A heterogeneous natural environment in a Mediterranean forest, in which various tree species (pine, oak and eucalyptus) coexist, was covered using a high-resolution digital camera and a multispectral sensor. These devices were mounted on an Unmanned Aerial Vehicle (UAV) in order to observe the tree architecture and the spectral reflectance at the same time. The Structure from Motion (SfM) method was applied to model the 3D structures using RGB images from the high-resolution camera. The geometric accuracy of the resulting point cloud was validated by georeferencing the study area through multiple ground control points (GCPs). Then, the point cloud was enriched with the reflected light in four narrow-bands (green, near-infrared, red and red-edge). Furthermore, the Normalized Difference Vegetation Index (NDVI) was calculated in order to measure the tree vigor. A comprehensive analysis based on structural and spectral features of individual trees was proposed. A spatial segmentation was developed to detect single-trees in a forest and for each one to identify the crown and trunk. Consequently, structural parameters were extracted, such as the tree height, the diameter at breast height (DBH) and the crown volume. The validation of these measurements was performed by field data, which were taken using a Total Station (TS). In addition, these characteristics were correlated with the mean reflectance in the tree canopy. Regarding the observed tree species, a statistical analysis was carried out to study the impact of reflectance on the 3D tree structure. By applying our method, a more detailed knowledge of forest dynamics can be gained and the impact of available solar irradiance on single-trees can be analyzed.
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Mokroš, Martin, Jozef Výbošťok, Julián Tomaštík, Alžbeta Grznárová, Peter Valent, Martin Slavík, and Ján Merganič. "High Precision Individual Tree Diameter and Perimeter Estimation from Close-Range Photogrammetry." Forests 9, no. 11 (November 10, 2018): 696. http://dx.doi.org/10.3390/f9110696.
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Close-range photogrammetry (CRP) can be used to provide precise and detailed three-dimensional data of objects. For several years, CRP has been a subject of research in forestry. Several studies have focused on tree reconstruction at the forest stand, plot, and tree levels. In our study, we focused on the reconstruction of trees separately within the forest stand. We investigated the influence of camera lens, tree species, and height of diameter on the accuracy of the tree perimeter and diameter estimation. Furthermore, we investigated the variance of the perimeter and diameter reference measurements. We chose four tree species (Fagus sylvatica L., Quercus petraea (Matt.) Liebl., Picea abies (L.) H. Karst. and Abies alba Mill.). The perimeters and diameters were measured at three height levels (0.8 m, 1.3 m, and 1.8 m) and two types of lenses were used. The data acquisition followed a circle around the tree at a 3 m radius. The highest accuracy of the perimeter estimation was achieved when a fisheye lens was used at a height of 1.3 m for Fagus sylvatica (root mean square error of 0.25 cm). Alternatively, the worst accuracy was achieved when a non-fisheye lens was used at 1.3 m for Quercus petraea (root mean square error of 1.27 cm). The tree species affected the estimation accuracy for both diameters and perimeters.
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Wan Mohd Jaafar, Wan, Iain Woodhouse, Carlos Silva, Hamdan Omar, Khairul Abdul Maulud, Andrew Hudak, Carine Klauberg, Adrián Cardil, and Midhun Mohan. "Improving Individual Tree Crown Delineation and Attributes Estimation of Tropical Forests Using Airborne LiDAR Data." Forests 9, no. 12 (December 5, 2018): 759. http://dx.doi.org/10.3390/f9120759.
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Individual tree crown (ITC) segmentation is an approach to isolate individual tree from the background vegetation and delineate precisely the crown boundaries for forest management and inventory purposes. ITC detection and delineation have been commonly generated from canopy height model (CHM) derived from light detection and ranging (LiDAR) data. Existing ITC segmentation methods, however, are limited in their efficiency for characterizing closed canopies, especially in tropical forests, due to the overlapping structure and irregular shape of tree crowns. Furthermore, the potential of 3-dimensional (3D) LiDAR data is not fully realized by existing CHM-based methods. Thus, the aim of this study was to develop an efficient framework for ITC segmentation in tropical forests using LiDAR-derived CHM and 3D point cloud data in order to accurately estimate tree attributes such as the tree height, mean crown width and aboveground biomass (AGB). The proposed framework entails five major steps: (1) automatically identifying dominant tree crowns by implementing semi-variogram statistics and morphological analysis; (2) generating initial tree segments using a watershed algorithm based on mathematical morphology; (3) identifying “problematic” segments based on predetermined set of rules; (4) tuning the problematic segments using a modified distance-based algorithm (DBA); and (5) segmenting and counting the number of individual trees based on the 3D LiDAR point clouds within each of the identified segment. This approach was developed in a way such that the 3D LiDAR points were only examined on problematic segments identified for further evaluations. 209 reference trees with diameter at breast height (DBH) ≥ 10 cm were selected in the field in two study areas in order to validate ITC detection and delineation results of the proposed framework. We computed tree crown metrics (e.g., maximum crown height and mean crown width) to estimate aboveground biomass (AGB) at tree level using previously published allometric equations. Accuracy assessment was performed to calculate percentage of correctly detected trees, omission and commission errors. Our method correctly identified individual tree crowns with detection accuracy exceeding 80 percent at both forest sites. Also, our results showed high agreement (R2 > 0.64) in terms of AGB estimates using 3D LiDAR metrics and variables measured in the field, for both sites. The findings from our study demonstrate the efficacy of the proposed framework in delineating tree crowns, even in high canopy density areas such as tropical rainforests, where, usually the traditional algorithms are limited in their performances. Moreover, the high tree delineation accuracy in the two study areas emphasizes the potential robustness and transferability of our approach to other densely forested areas across the globe.
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Chang, K. T., C. Lin, Y. C. Lin, and J. K. Liu. "ACCURACY ASSESSMENT OF CROWN DELINEATION METHODS FOR THE INDIVIDUAL TREES USING LIDAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 585–88. http://dx.doi.org/10.5194/isprsarchives-xli-b8-585-2016.
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Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.
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Chang, K. T., C. Lin, Y. C. Lin, and J. K. Liu. "ACCURACY ASSESSMENT OF CROWN DELINEATION METHODS FOR THE INDIVIDUAL TREES USING LIDAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 585–88. http://dx.doi.org/10.5194/isprs-archives-xli-b8-585-2016.
Full textAbstract:
Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.
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Ledermann, Thomas, and Albert R. Stage. "Effects of competitor spacing in individual-tree indices of competition." Canadian Journal of Forest Research 31, no. 12 (December 1, 2001): 2143–50. http://dx.doi.org/10.1139/x01-153.
Full textAbstract:
All indices of competition represent effects of distance between competing trees. However, the functional forms of these distance relations differ, because distance interacts with tree size in the many of the indices. In particular, some of the newer indices use vertical angles and crown geometry to define the effect of separation implicitly. Graphical displays showing effects of distance between subject tree and a competitor in published distance-dependent indices of competition are presented to permit visual comparisons of the indices. Nine pairs of subject and competitor crown classes are included for each index. Relation of these distance functions to the function implicit in distance-independent (stand-level) variables included in the growth prediction model is discussed.
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Host, George E., Harlan W. Stech, Kathryn E. Lenz, Kyle Roskoski, and Richard Mather. "Forest patch modeling: using high performance computing to simulate aboveground interactions among individual trees." Functional Plant Biology 35, no. 10 (2008): 976. http://dx.doi.org/10.1071/fp08075.
Full textAbstract:
Functional–structural plant models (FSPMs) typically integrate suites of detailed physiological and phenological processes to simulate the growth of individual plants. Recent advances in high-performance computing have allowed FSPMs to be extended to patches of interacting trees. Here, we describe a parallel modelling strategy to run simultaneous individual tree models across an 8 × 8 patch of trees. The 64 ‘core’ trees are surrounded by multiple rings of neighbour trees to remove edge effects. A sensitivity analysis of the patch model demonstrates that computational factors such as the number of independently simulated trees (9 v. 36) or number of neighbour rings (3 v. 6) did not significantly influence model estimates of tree volume growth. Updated submodels for phenology and redistribution of overwinter carbohydrate storage allow the simulation to be more responsive to above ground competition among trees in a patch over multiple growing seasons. An 8-year patch-scale simulation of aspen clones 216 and 259 was conducted using high-resolution environmental data from the Aspen FACE Experiment, a long-term free-air carbon dioxide enrichment (FACE) study. Tree heights and volumes were comparable to 8-year growth measurements made at the Aspen FACE site.
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Zhou, X., L. Liao, D. Cheng, X. Chen, and Q. Huang. "EXTRACTION OF THE INDIVIDUAL TREE INFECTED BY PINE WILT DISEASE USING UNMANNED AERIAL VEHICLE OPTICAL IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 247–52. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-247-2020.
Full textAbstract:
Abstract. For eliminating pine trees infected pine wilt disease in southern China based on remote sensing technique, it is important to ensure the provision of timely information about individual diseased tree. It is not easy to detect and extract the diseased pine trees from conventional remote sensing techniques. This paper proposes a new approach for extracting information about individual diseased tree, without the use of satellite images and aerial hyperspectral images. Field measurements in different leaf infected stages indicates the possibility of extracting diseased trees by using only the three regular bands, red, green and blue. VEG was selected and proved to be the optimal index in 12 vegetation indices from the three visible bands. Using the adaptive local threshold selection methods, VEG grayscale image pixels could be automatically segmented into the diseased trees region. Based on mathematical morphology, the accuracy of individual tree information extraction reached 90%.