Journal articles: 'Tree data'

1

D, Christy Sujatha, and Gnana Jayanthi Dr.J. "LASH Tree: LASSO Regression Hoeffding for Streaming Data." International Journal of Psychosocial Rehabilitation 24, no. 04 (February 28, 2020): 3022–33. http://dx.doi.org/10.37200/ijpr/v24i4/pr201415.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Dobashi, Nao, Shota Saito, Yuta Nakahara, and Toshiyasu Matsushima. "Meta-Tree Random Forest: Probabilistic Data-Generative Model and Bayes Optimal Prediction." Entropy 23, no. 6 (June 18, 2021): 768. http://dx.doi.org/10.3390/e23060768.

Full text

Abstract:

This paper deals with a prediction problem of a new targeting variable corresponding to a new explanatory variable given a training dataset. To predict the targeting variable, we consider a model tree, which is used to represent a conditional probabilistic structure of a targeting variable given an explanatory variable, and discuss statistical optimality for prediction based on the Bayes decision theory. The optimal prediction based on the Bayes decision theory is given by weighting all the model trees in the model tree candidate set, where the model tree candidate set is a set of model trees in which the true model tree is assumed to be included. Because the number of all the model trees in the model tree candidate set increases exponentially according to the maximum depth of model trees, the computational complexity of weighting them increases exponentially according to the maximum depth of model trees. To solve this issue, we introduce a notion of meta-tree and propose an algorithm called MTRF (Meta-Tree Random Forest) by using multiple meta-trees. Theoretical and experimental analyses of the MTRF show the superiority of the MTRF to previous decision tree-based algorithms.

APA, Harvard, Vancouver, ISO, and other styles

3

Randall, Bryan L., Alan R. Ek, Jerold T. Hahn, and Roland G. Buchman. "STEMS Model Projection Capability with Incomplete Tree List Input Data." Northern Journal of Applied Forestry 5, no. 3 (September 1, 1988): 190–94. http://dx.doi.org/10.1093/njaf/5.3.190.

Full text

Abstract:

Abstract Projections were made using the STEMS individual tree based stand growth model for plots in red pine, maple-birch, and aspen cover types for periods up to 50 years. Effects of incomplete tree list input data on plots in the form of small tree censorship (omission of small trees) and tree list aggregation (by size class) were examined by comparing projections made for complete plot tree lists (controls) with projections made after these tree lists were censored and aggregated (treatments). Basal area and number of trees estimates proved highly sensitive to censorship, while volume estimates were much less sensitive. Augmentation of censored distributions by an “average” small tree distribution for the cover type resulted in significant improvement of these estimates. Projection model capability using input data aggregated by size class depended on the degree of aggregation. For some types of aggregation, for example by 2-in. dbh classes, the STEMS model retains much of its predictive utility. North. J. Appl. For. 5:190-194, Sept. 1988.

APA, Harvard, Vancouver, ISO, and other styles

4

Hsiao, Pei-Yung. "Nearly Balanced Quad List Quad Tree -A Data Structure for VLSI Layout Systems." VLSI Design 4, no. 1 (January 1, 1996): 17–32. http://dx.doi.org/10.1155/1996/82789.

Full text

Abstract:

In the past ten years, many researchers have focused attention on developing better data structures for storing graphical information. Among the proposed data structures, the quad tree data structure provides a good way to organize objects on a 2-D plane. Region searches proceed at logarithmic speeds a desirable characteristic, but no previously proposed VLSI quad tree data structure distributed objects to subdivide the spatial area. This has been a major drawback for operations such as tree searching and window query. In this paper, we present a new division method to reconstruct those quad trees including the multiple storage quad tree (MSQT) and the quad list quad tree (QLQT) into nearly balanced quad tree data structures. Nearly balanced quad trees based on our new spatial division method are constructed by dynamically translating unbalanced multiple storage quad trees or unbalanced quad list quad trees into balanced structures. All benefits of the original quad tree data structures are completely retained. In addition, this method is simple and balanced quad trees memory require less than the original quad trees. Experimental results illustrate that the improvement in region queries of the presented nearly balanced quad trees to both of the QLQT and the MSQT is better than the improvement of the QLQT to the MSQT.

APA, Harvard, Vancouver, ISO, and other styles

5

Tennekes, Martijn, and Edwin de Jonge. "Tree Colors: Color Schemes for Tree-Structured Data." IEEE Transactions on Visualization and Computer Graphics 20, no. 12 (December 31, 2014): 2072–81. http://dx.doi.org/10.1109/tvcg.2014.2346277.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Guan, H., S. Cao, Y. Yu, J. Li, N. Liu, P. Chen, and Y. Li. "STREET-SCENE TREE SEGMENTATION FROM MOBILE LASER SCANNING DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 9, 2016): 221–25. http://dx.doi.org/10.5194/isprsarchives-xli-b3-221-2016.

Full text

Abstract:

Our work addresses the problem of extracting trees from mobile laser scanning data. The work is a two step-wise strategy, including terrain point removal and tree segmentation. First, a voxel-based upward growing filtering is proposed to remove terrain points from the mobile laser scanning data. Then, a tree segmentation is presented to extract individual trees via a Euclidean distance clustering approach and Voxel-based Normalized Cut (VNCut) segmentation approach. A road section data acquired by a RIEGL VMX-450 system are selected for evaluating the proposed tree segmentation method. Qualitative analysis shows that our algorithm achieves a good performance.

APA, Harvard, Vancouver, ISO, and other styles

7

Guan, H., S. Cao, Y. Yu, J. Li, N. Liu, P. Chen, and Y. Li. "STREET-SCENE TREE SEGMENTATION FROM MOBILE LASER SCANNING DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 9, 2016): 221–25. http://dx.doi.org/10.5194/isprs-archives-xli-b3-221-2016.

Full text

Abstract:

Our work addresses the problem of extracting trees from mobile laser scanning data. The work is a two step-wise strategy, including terrain point removal and tree segmentation. First, a voxel-based upward growing filtering is proposed to remove terrain points from the mobile laser scanning data. Then, a tree segmentation is presented to extract individual trees via a Euclidean distance clustering approach and Voxel-based Normalized Cut (VNCut) segmentation approach. A road section data acquired by a RIEGL VMX-450 system are selected for evaluating the proposed tree segmentation method. Qualitative analysis shows that our algorithm achieves a good performance.

APA, Harvard, Vancouver, ISO, and other styles

8

Woodard, P. M., D. Needham, W. E. Phillips, and L. F. Constantino. "A Christmas tree market analysis: implications from Alberta, Canada data." Forestry Chronicle 70, no. 4 (August 1, 1994): 443–48. http://dx.doi.org/10.5558/tfc70443-4.

Full text

Abstract:

The 1990 Christmas tree market in Alberta, Canada was assessed in an attempt to determine the feasibility of growing such trees for local consumption. Almost 5 500 questionnaires were delivered to households and commercial establishments as part of this survey. In addition, many personal interviews were conducted. The information presented pertains to the wholesale and retail sales volumes and values by tree species. The socio-economic background of tree buying consumers and their traditional celebration and purchasing habits are also included. Our results suggest Albertans spent over $7 million (retail) to buy 300,000 natural Christmas trees during the 1990 holiday season, and that 87% of the wholesale value or $2.6 million was spent to buy trees from outside of Alberta. Consumers would prefer to buy high-quality, locally-grown trees.

APA, Harvard, Vancouver, ISO, and other styles

9

Shen, Dan, Haipeng Shen, Shankar Bhamidi, Yolanda Muñoz Maldonado, Yongdai Kim, and J. S. Marron. "Functional Data Analysis of Tree Data Objects." Journal of Computational and Graphical Statistics 23, no. 2 (April 3, 2014): 418–38. http://dx.doi.org/10.1080/10618600.2013.786943.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Kumazaki, R., and Y. Kunii. "APPLICATION OF 3D TREE MODELING USING POINT CLOUD DATA BY TERRESTRIAL LASER SCANNER." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 995–1000. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-995-2020.

Full text

Abstract:

Abstract. Constructing 3D models for trees such as those found in Japanese gardens, in which many species exist, requires the generation of tree shapes that combine the characteristics of the tree's species and natural diversity. Therefore, this study proposes a method for constructing a 3D tree model with highly-accurate tree shape reproducibility from tree point cloud data acquired by TLS. As a method, we attempted to construct a 3D tree model using the TreeQSM, which is open source for TLS-QSM method. However, in TreeQSM, since processing is based on the assumption that the tree point cloud consists of data related to trunks and branches, measuring trees in which leaves have fallen is recommended. To solve this problem, we proposed an efficient classification process that mainly uses thresholds for deviation and reflectance, which are the adjunct data of the object that can be acquired by laser measurement. Furthermore, to verify accuracy of the model, position coordinates from the constructed 3D tree model were extracted. The extracted coordinates were compared with the those of the tree point cloud data to clarify the extent to which the 3D tree model was constructed from the tree point cloud data. As a result, the 3D tree model was constructed within the standard deviation of 0.016 m from the tree point cloud data. Therefore, the reproducibility of the tree shape by the TLS-QSM method was also effective in terms of accuracy.

APA, Harvard, Vancouver, ISO, and other styles

11

Zellweger, Paul. "The Aleph Data Relation in Structured Data, A Tree within a Tree Visualization." Electronic Imaging 2016, no. 1 (February 14, 2016): 1. http://dx.doi.org/10.2352/issn.2470-1173.2016.1.vda-499.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Gougherty, Andrew V., Stephen R. Keller, Anton Kruger, Cathlyn D. Stylinski, Andrew J. Elmore, and Matthew C. Fitzpatrick. "Estimating tree phenology from high frequency tree movement data." Agricultural and Forest Meteorology 263 (December 2018): 217–24. http://dx.doi.org/10.1016/j.agrformet.2018.08.020.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Jackson, Toby D., Sarab Sethi, Ebba Dellwik, Nikolas Angelou, Amanda Bunce, Tim van Emmerik, Marine Duperat, et al. "The motion of trees in the wind: a data synthesis." Biogeosciences 18, no. 13 (July 6, 2021): 4059–72. http://dx.doi.org/10.5194/bg-18-4059-2021.

Full text

Abstract:

Abstract. Interactions between wind and trees control energy exchanges between the atmosphere and forest canopies. This energy exchange can lead to the widespread damage of trees, and wind is a key disturbance agent in many of the world's forests. However, most research on this topic has focused on conifer plantations, where risk management is economically important, rather than broadleaf forests, which dominate the forest carbon cycle. This study brings together tree motion time-series data to systematically evaluate the factors influencing tree responses to wind loading, including data from both broadleaf and coniferous trees in forests and open environments. We found that the two most descriptive features of tree motion were (a) the fundamental frequency, which is a measure of the speed at which a tree sways and is strongly related to tree height, and (b) the slope of the power spectrum, which is related to the efficiency of energy transfer from wind to trees. Intriguingly, the slope of the power spectrum was found to remain constant from medium to high wind speeds for all trees in this study. This suggests that, contrary to some predictions, damping or amplification mechanisms do not change dramatically at high wind speeds, and therefore wind damage risk is related, relatively simply, to wind speed. Conifers from forests were distinct from broadleaves in terms of their response to wind loading. Specifically, the fundamental frequency of forest conifers was related to their size according to the cantilever beam model (i.e. vertically distributed mass), whereas broadleaves were better approximated by the simple pendulum model (i.e. dominated by the crown). Forest conifers also had a steeper slope of the power spectrum. We interpret these finding as being strongly related to tree architecture; i.e. conifers generally have a simple shape due to their apical dominance, whereas broadleaves exhibit a much wider range of architectures with more dominant crowns.

APA, Harvard, Vancouver, ISO, and other styles

14

BEYAZ, Abdullah, and Mücahit Taha ÖZKAYA. "Canopy analysis and thermographic abnormalities determination possibilities of olive trees by using data mining algorithms." Notulae Botanicae Horti Agrobotanici Cluj-Napoca 49, no. 1 (January 21, 2021): 12139. http://dx.doi.org/10.15835/nbha49112139.

Full text

Abstract:

In order to take the appropriate tree protection measures, it is crucial to determine and track abnormalities that may occur in olive trees in time to time for many reasons. Abnormalities start in different sections of the trees, depending on the environmental effects of the olive tree, with a specific impact like fungal diseases, drought, etc. after a certain age especially in non-resistant species. Protection steps may be taken when abnormalities are apparent or predictable in certain olive trees, using some external indicators. However, when abnormalities formed within trees cannot be identified externally, there is a sudden breakdown and overthrow of valuable properties, such as monument trees. In the literature, various devices and methods are explained to classify these defects in different trees. By the way, in this research, a non-destructive inspection method (thermography) was clarified and used to assess anomalies in old olive trees without damage in the interior. According to the results of average thermal data, 60, 400, 600 year-old olive trees, 60-40, 70-30 and 80-20 learning-prediction data rates decision tree and random forest results according to normal and abnormal thermal difference, the thermal range was found as 35.95 ℃ at 60 year-old tree, also it was found as 36.25 ℃ at 400 year-old tree and it was found as 38.25 ℃ at 600 year-old tree.

APA, Harvard, Vancouver, ISO, and other styles

15

Guan, H., Y. Yu, W. Yan, D. Li, and J. Li. "3D-CNN BASED TREE SPECIES CLASSIFICATION USING MOBILE LIDAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 989–93. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-989-2019.

Full text

Abstract:

<p><strong>Abstract.</strong> Our work addresses the problem of classifying tree species from mobile LiDAR data. The work is a two step-wise strategy, including tree segmentation and tree species classification. In the tree segmentation step, a voxel-based upward growing filtering is proposed to remove terrain points from the mobile laser scanning data. Then, individual trees are segmented via a Euclidean distance clustering approach and Voxel-based Normalized Cut (VNCut) segmentation approach. In the tree species classification, a voxel-based 3D convolutional neural network (3D-CNN) model is developed based on intensity information. A road section data acquired by a RIEGL VMX-450 system are selected for evaluating the proposed tree classification method. Qualitative analysis shows that our algorithm achieves a good performance.</p>

APA, Harvard, Vancouver, ISO, and other styles

16

Chalothorn, Tawunrat, and Jeremy Ellman. "Using Arbiter and Combiner Tree to Classify Contexts of Data." International Journal of Computer Theory and Engineering 8, no. 5 (October 2016): 434–38. http://dx.doi.org/10.7763/ijcte.2016.v8.1085.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Kumar, D. Sampath, and N. Suma N. Suma. "New Scheme For Data Hiding Using N-Ary Tree Structure." International Journal of Scientific Research 1, no. 3 (June 1, 2012): 34–35. http://dx.doi.org/10.15373/22778179/aug2012/13.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

De Rosa, Rocco, and Nicolò Cesa-Bianchi. "Confidence Decision Trees via Online and Active Learning for Streaming Data." Journal of Artificial Intelligence Research 60 (December 26, 2017): 1031–55. http://dx.doi.org/10.1613/jair.5440.

Full text

Abstract:

Decision tree classifiers are a widely used tool in data stream mining. The use of confidence intervals to estimate the gain associated with each split leads to very effective methods, like the popular Hoeffding tree algorithm. From a statistical viewpoint, the analysis of decision tree classifiers in a streaming setting requires knowing when enough new information has been collected to justify splitting a leaf. Although some of the issues in the statistical analysis of Hoeffding trees have been already clarified, a general and rigorous study of confidence intervals for splitting criteria is missing. We fill this gap by deriving accurate confidence intervals to estimate the splitting gain in decision tree learning with respect to three criteria: entropy, Gini index, and a third index proposed by Kearns and Mansour. We also extend our confidence analysis to a selective sampling setting, in which the decision tree learner adaptively decides which labels to query in the stream. We provide theoretical guarantees bounding the probability that the decision tree learned via our selective sampling strategy classifies suboptimally the next example in the stream. Experiments on real and synthetic data in a streaming setting show that our trees are indeed more accurate than trees with the same number of leaves generated by state-of-the-art techniques. In addition to that, our active learning module empirically uses fewer labels without significantly hurting the performance.

APA, Harvard, Vancouver, ISO, and other styles

19

Yousef M. T. El Gimati. "Comparison estimating of classification error rate in decision tree: Data mining." Global Journal of Engineering and Technology Advances 7, no. 2 (May 30, 2021): 067–82. http://dx.doi.org/10.30574/gjeta.2021.7.2.0068.

Full text

Abstract:

Decision Tree (DT) typically splitting criteria using one variable at a time. In this way, the final decision partition has boundaries that are parallel to axes. An observation is misclassified when it falls in a region which does not have the same class membership. Misclassification rate in classification tree is defined as the proportion of observations classified to the wrong class while in the regression tree is defined as a mean squared error. In this paper, we present two of the important methods for estimating the misclassification (error) rate in decision trees, as we know that all classification procedures, including decision trees, can produce errors. Constructed DT model by using a training dataset and tested it based on an independent test dataset. There are several procedures for estimating the error rate of decision tree-structured classifiers, as K-fold cross-validation and bootstrap estimates. This comparison aimed to characterize the performance of the two methods in terms of test error rates based on real datasets. The results indicate that 10-fold cross-validation and bootstrap yield a tree fairly close to the best available measured by tree size.

APA, Harvard, Vancouver, ISO, and other styles

20

Zhao, Yingyi, Qingwu Hu, Haidong Li, Shaohua Wang, and Mingyao Ai. "Evaluating Carbon Sequestration and PM2.5 Removal of Urban Street Trees Using Mobile Laser Scanning Data." Remote Sensing 10, no. 11 (November 7, 2018): 1759. http://dx.doi.org/10.3390/rs10111759.

Full text

Abstract:

Street trees are an important part of urban facilities, and they can provide both aesthetic benefits and ecological benefits for urban environments. Ecological benefits of street trees now are attracting more attention because of environmental deterioration in cities. Conventional methods of evaluating ecological benefits require a lot of labor and time, and establishing an efficient and effective evaluating method is challenging. In this study, we investigated the feasibility to use mobile laser scanning (MLS) data to evaluate carbon sequestration and fine particulate matter (PM2.5) removal of street trees. We explored the approach to extract individual street trees from MLS data, and street trees of three streets in Nantong City were extracted. The correctness rates and completeness rates of extraction results were both over 92%. Morphological parameters, including tree height, crown width, and diameter at breast height (DBH), were measured for extracted street trees, and parameters derived from MLS data were in a good agreement with field-measured parameters. Necessary information about street trees, including tree height, DBH, and tree species, meteorological data and PM2.5 deposition velocities were imported into i-Tree Eco model to estimate carbon sequestration and PM2.5 removal. The estimation results indicated that ecological benefits generated by different tree species were considerably varied and the differences for trees of the same species were mainly caused by the differences in morphological parameters (tree height and DBH). This study succeeds in estimating the amount of carbon sequestration and PM2.5 removal of individual street trees with MLS data, and provides researchers with a novel and efficient way to investigate ecological benefits of urban street trees or urban forests.

APA, Harvard, Vancouver, ISO, and other styles

21

Gagie, Travis, Meng He, Gonzalo Navarro, and Carlos Ochoa. "Tree path majority data structures." Theoretical Computer Science 833 (September 2020): 107–19. http://dx.doi.org/10.1016/j.tcs.2020.05.039.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Zhang, Long, Yubo Zhang, Zhongding Jiang, Luying Li, Wei Chen, and Qunsheng Peng. "Precomputing data-driven tree animation." Computer Animation and Virtual Worlds 18, no. 4-5 (2007): 371–82. http://dx.doi.org/10.1002/cav.205.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Schmidt, Nikita, and Ahmed Patel. "Rule-driven processing of tree-structured data using pointed trees." Computer Standards & Interfaces 25, no. 5 (September 2003): 463–75. http://dx.doi.org/10.1016/s0920-5489(03)00068-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Raumonen, P., E. Casella, K. Calders, S. Murphy, M. Åkerbloma,, and M. Kaasalainen. "MASSIVE-SCALE TREE MODELLING FROM TLS DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W4 (March 11, 2015): 189–96. http://dx.doi.org/10.5194/isprsannals-ii-3-w4-189-2015.

Full text

Abstract:

This paper presents a method for reconstructing automatically the quantitative structure model of every tree in a forest plot from terrestrial laser scanner data. A new feature is the automatic extraction of individual trees from the point cloud. The method is tested with a 30-m diameter English oak plot and a 80-m diameter Australian eucalyptus plot. For the oak plot the total biomass was overestimated by about 17 %, when compared to allometry (N = 15), and the modelling time was about 100 min with a laptop. For the eucalyptus plot the total biomass was overestimated by about 8.5 %, when compared to a destructive reference (N = 27), and the modelling time was about 160 min. The method provides accurate and fast tree modelling abilities for, e.g., biomass estimation and ground truth data for airborne measurements at a massive ground scale.

APA, Harvard, Vancouver, ISO, and other styles

25

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

26

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

27

Czerwinski, Wojciech, Wim Martens, Matthias Niewerth, and Pawel Parys. "Optimizing Tree Patterns for Querying Graph- and Tree-Structured Data." ACM SIGMOD Record 46, no. 1 (May 12, 2017): 15–22. http://dx.doi.org/10.1145/3093754.3093759.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Tennekes, Martijn, and Edwin de Jonge. "Errata to “Tree Colors: Color Schemes for Tree-Structured Data”." IEEE Transactions on Visualization and Computer Graphics 21, no. 1 (January 1, 2015): 136. http://dx.doi.org/10.1109/tvcg.2014.2368383.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

30

Parmehr, Ebadat G., Marco Amati, and Clive S. Fraser. "MAPPING URBAN TREE CANOPY COVER USING FUSED AIRBORNE LIDAR AND SATELLITE IMAGERY DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-7 (June 7, 2016): 181–86. http://dx.doi.org/10.5194/isprsannals-iii-7-181-2016.

Full text

Abstract:

Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

APA, Harvard, Vancouver, ISO, and other styles

31

Parmehr, Ebadat G., Marco Amati, and Clive S. Fraser. "MAPPING URBAN TREE CANOPY COVER USING FUSED AIRBORNE LIDAR AND SATELLITE IMAGERY DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-7 (June 7, 2016): 181–86. http://dx.doi.org/10.5194/isprs-annals-iii-7-181-2016.

Full text

Abstract:

Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

APA, Harvard, Vancouver, ISO, and other styles

32

Chang, Chia-Yo, Jason T. L. Wang, and Roger K. Chang. "Scientific Data Mining: A Case Study." International Journal of Software Engineering and Knowledge Engineering 08, no. 01 (March 1998): 77–96. http://dx.doi.org/10.1142/s0218194098000078.

Full text

Abstract:

Scientific data mining is the activity of finding significant information in scientific data. This paper presents an example of scientific data mining: the discovery of approximately common patterns in RNA secondary structures. We represent an RNA secondary structure by an ordered labeled tree based on a previously proposed scheme. The patterns in the trees are substructures that can differ in both substitutions and deletions/insertions of nodes of the trees. Our techniques incorporate approximate tree matching algorithms and novel heuristics for discovery and optimization. Experimental results obtained by running these algorithms on both generated data and RNA secondary structures show the good performance of the algorithms. It is shown that the optimization heuristics speed up the discovery algorithm by a factor of 10. Moreover, our optimized approach is 100,000 times faster than the brute force method.

APA, Harvard, Vancouver, ISO, and other styles

33

Novak, Thomas P. "Log-Linear Trees: Models of Market Structure in Brand Switching Data." Journal of Marketing Research 30, no. 3 (August 1993): 267–87. http://dx.doi.org/10.1177/002224379303000301.

Full text

Abstract:

Log-linear trees restrict the log-linear model of quasi-symmetry so that parameters are interpretable as arc lengths in an additive tree. The tree representation can be interpreted further in terms of consumer heterogeneity, affording a dual interpretation in terms of both market structure and opportunities for market segmentation.

APA, Harvard, Vancouver, ISO, and other styles

34

Kimball, Kenneth D., and MaryBeth Keifer. "Climatic comparisons with tree-ring data from montane forests: are the climatic data appropriate?" Canadian Journal of Forest Research 18, no. 4 (April 1, 1988): 385–90. http://dx.doi.org/10.1139/x88-057.

Full text

Abstract:

The appropriateness of relating spatially proximate (40-km radius) temperature and precipitation data from different elevations to montane forest growth patterns was investigated for Mount Washington, New Hampshire. Monthly mean temperature and total precipitation data (1933–1983) were correlated (p < 0.05) among all pairs of meteorological stations (280, 420, 610, 1915 m and regional averages) on or near Mount Washington. The unexplained variance (1 − r2) for precipitation comparisons between meteorological stations was greater relative to temperature. When correlated with the average tree-ring index chronology of 90 red spruce trees on Mount Washington (800–1200 m), the monthly temperature data yielded similar correlative patterns among the four meteorological stations. However, the monthly temperature data from the meteorological stations (610 and 1915 m) most proximate to the montane forest study site were correlated (p < 0.10) with the tree-ring indices for two to three times as many months as the temperature data from the lower elevations. There was no consistency in correlative results of tree-ring indices with monthly precipitation data among the four meteorological stations. However, precipitation measurements and Palmer drought indices are poor indicators of moisture availability in montane forests. We conclude that spatially proximate, low elevation temperature data can underestimate correlative relationships between temperature and montane tree-ring data in the northeastern United States.

APA, Harvard, Vancouver, ISO, and other styles

35

Homainejad, A. S. "NEW APPROACH FOR SEGMENTATION AND EXTRACTION OF SINGLE TREE FROM POINT CLOUDS DATA AND AERIAL IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1287–92. http://dx.doi.org/10.5194/isprsarchives-xli-b8-1287-2016.

Full text

Abstract:

This paper addresses a new approach for reconstructing a 3D model from single trees via Airborne Laser Scanners (ALS) data and aerial images. The approach detects and extracts single tree from ALS data and aerial images. The existing approaches are able to provide bulk segmentation from a group of trees; however, some methods focused on detection and extraction of a particular tree from ALS and images. Segmentation of a single tree within a group of trees is mostly a mission impossible since the detection of boundary lines between the trees is a tedious job and basically it is not feasible. In this approach an experimental formula based on the height of the trees was developed and applied in order to define the boundary lines between the trees. As a result, each single tree was segmented and extracted and later a 3D model was created. Extracted trees from this approach have a unique identification and attribute. The output has application in various fields of science and engineering such as forestry, urban planning, and agriculture. For example in forestry, the result can be used for study in ecologically diverse, biodiversity and ecosystem.

APA, Harvard, Vancouver, ISO, and other styles

36

Homainejad, A. S. "NEW APPROACH FOR SEGMENTATION AND EXTRACTION OF SINGLE TREE FROM POINT CLOUDS DATA AND AERIAL IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1287–92. http://dx.doi.org/10.5194/isprs-archives-xli-b8-1287-2016.

Full text

Abstract:

This paper addresses a new approach for reconstructing a 3D model from single trees via Airborne Laser Scanners (ALS) data and aerial images. The approach detects and extracts single tree from ALS data and aerial images. The existing approaches are able to provide bulk segmentation from a group of trees; however, some methods focused on detection and extraction of a particular tree from ALS and images. Segmentation of a single tree within a group of trees is mostly a mission impossible since the detection of boundary lines between the trees is a tedious job and basically it is not feasible. In this approach an experimental formula based on the height of the trees was developed and applied in order to define the boundary lines between the trees. As a result, each single tree was segmented and extracted and later a 3D model was created. Extracted trees from this approach have a unique identification and attribute. The output has application in various fields of science and engineering such as forestry, urban planning, and agriculture. For example in forestry, the result can be used for study in ecologically diverse, biodiversity and ecosystem.

APA, Harvard, Vancouver, ISO, and other styles

37

Yang, Sheng-I., and Harold E. Burkhart. "Robustness of Parametric and Nonparametric Fitting Procedures of Tree-Stem Taper with Alternative Definitions for Validation Data." Journal of Forestry 118, no. 6 (August 31, 2020): 576–83. http://dx.doi.org/10.1093/jofore/fvaa036.

Full text

Abstract:

Abstract This study aims to evaluate the robustness of parametric and nonparametric procedures using alternative definitions of validation data for loblolly pine. Specifically, four data division strategies were implemented: random selection of one-third of the trees in the data set, selection of the smallest one-third of the trees by diameter at breast height (DBH), selection of the middle third of the trees by DBH, and selection of the largest third of the trees by DBH. Results indicate that tree taper was predicted reasonably well by both procedures when the smallest, medium-sized, or randomly selected trees were withheld for validation. However, when the largest trees were withheld for validation, diameters predicted by the nonparametric random forest algorithm were considerably less accurate than those predicted by the parametric models, especially for diameters near the tree top. When extrapolation is anticipated, a carefully designed data-partitioning strategy should provide some protection against poor results for given prediction objectives. Study Implications Parametric tree-stem taper models have been widely applied in forestry. Recently, nonparametric methods with computationally intensive algorithms were proposed for estimating tree taper, but reliability of the methods has not been explicitly examined. In practice, models are commonly applied to predict unknown populations, which may vary from the observations used in model development. This study provides insights for natural resource and forest managers to select appropriate validation procedures when developing models for predicting tree-stem taper and examining robustness of parametric and nonparametric fitting of tree-stem taper under varying levels of interpolation/extrapolation from fitting to validation of data.

APA, Harvard, Vancouver, ISO, and other styles

38

Zhao, Ling Li, Shu Ai Liu, and Jun Sheng Li. "The Index Storage Model for Urbanization Data Combined Query." Advanced Materials Research 532-533 (June 2012): 1186–90. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.1186.

Full text

Abstract:

Urban information is a kind of multi-sources data, the paper is focused on data indexes construction, classified indexes for non-spatial data, R-trees index for spatial data and the paper puts forward an area hiberarchy index tree structure to build up direct relationship between spatial data and non-spatial data for combined queries, and the experiment shows that the hiberarchy index tree is much validated and something useful is obtained.

APA, Harvard, Vancouver, ISO, and other styles

39

Csank, Adam Z. "An International Tree-Ring Isotope Data Bank– A Proposed Repository for Tree-Ring Isotopic Data." Tree-Ring Research 65, no. 2 (July 2009): 163–64. http://dx.doi.org/10.3959/1536-1098-65.2.163.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Wang, Xiao-Hu, Yi-Zhuo Zhang, and Miao-Miao Xu. "A Multi-Threshold Segmentation for Tree-Level Parameter Extraction in a Deciduous Forest Using Small-Footprint Airborne LiDAR Data." Remote Sensing 11, no. 18 (September 10, 2019): 2109. http://dx.doi.org/10.3390/rs11182109.

Full text

Abstract:

The development of new approaches to tree-level parameter extraction for forest resource inventory and management is an important area of ongoing research, which puts forward high requirements for the capabilities of single-tree segmentation and detection methods. Conventional methods implement segmenting routine with same resolution threshold for overstory and understory, ignoring that their lidar point densities are different, which leads to over-segmentation of the understory trees. To improve the segmentation accuracy of understory trees, this paper presents a multi-threshold segmentation approach for tree-level parameter extraction using small-footprint airborne LiDAR (Light Detection And Ranging) data. First, the point clouds are pre-processed and encoded to canopy layers according to the lidar return number, and multi-threshold segmentation using DSM-based (Digital Surface Model) method is implemented for each layer; tree segments are then combined across layers by merging criteria. Finally, individual trees are delineated, and tree parameters are extracted. The novelty of this method lies in its application of multi-resolution threshold segmentation strategy according to the variation of LiDAR point density in different canopy layers. We applied this approach to 271 permanent sample plots of the University of Kentucky’s Robinson Forest, a deciduous canopy-closed forest with complex terrain and vegetation conditions. Experimental results show that a combination of multi-resolution threshold segmentation based on stratification and cross-layer tree segments merging method can provide a significant performance improvement in individual tree-level forest measurement. Compared with DSM-based method, the proposed multi-threshold segmentation approach strongly improved the average detection rate (from 52.3% to 73.4%) and average overall accuracy (from 65.2% to 76.9%) for understory trees. The overall accuracy increased from 75.1% to 82.6% for all trees, with an increase of the coefficient of determination R2 by 20 percentage points. The improvement of tree detection method brings the estimation of structural parameters for single trees up to an accuracy level: For tree height, R2 increased by 5.0 percentage points from 90% to 95%; and for tree location, the mean difference decreased by 23 cm from 105 cm to 82 cm.

APA, Harvard, Vancouver, ISO, and other styles

41

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

42

Berland, Adam, Lara A. Roman, and Jess Vogt. "Can Field Crews Telecommute? Varied Data Quality from Citizen Science Tree Inventories Conducted Using Street-Level Imagery." Forests 10, no. 4 (April 20, 2019): 349. http://dx.doi.org/10.3390/f10040349.

Full text

Abstract:

Street tree inventories are a critical component of urban forest management. However, inventories conducted in the field by trained professionals are expensive and time-consuming. Inventories relying on citizen scientists or virtual surveys conducted remotely using street-level photographs may greatly reduce the costs of street tree inventories, but there are fundamental uncertainties regarding the level of data quality that can be expected from these emerging approaches to data collection. We asked 16 volunteers to inventory street trees in suburban Chicago using Google Street ViewTM imagery, and we assessed data quality by comparing their virtual survey data to field data from the same locations. We also compared virtual survey data quality according to self-rated expertise by measuring agreement within expert, intermediate, and novice analyst groups. Analyst agreement was very good for the number of trees on each street segment, and agreement was markedly lower for tree diameter class and tree identification at the genus and species levels, respectively. Interrater agreement varied by expertise, such that experts agreed with one another more often than novices for all four variables assessed. Compared to the field data, we observed substantial variability in analyst performance for diameter class estimation and tree identification, and some intermediate analysts performed as well as experts. Our findings suggest that virtual surveys may be useful for documenting the locations of street trees within a city more efficiently than field crews and with a high level of accuracy. However, tree diameter and species identification data were less reliable across all expertise groups, and especially novice analysts. Based on this analysis, virtual street tree inventories are best suited to collecting very basic information such as tree locations, or updating existing inventories to determine where trees have been planted or removed. We conclude with evidence-based recommendations for effective implementation of this type of approach.

APA, Harvard, Vancouver, ISO, and other styles

43

Zhang, Zhi Tong. "Optimization of History Tree in 3DR-Tree Index Structure." Applied Mechanics and Materials 347-350 (August 2013): 2521–23. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2521.

Full text

Abstract:

Many optimizations have been done to 3DR-tree index structure and many opinions have been proposed. Modification by splitting mechanism is one of them. There are two index trees in 3DR-tree index structure after modification: one is a history tree for past data storage and the other is an active tree for current data storage. In this article, optimization of history tree is firstly done and is proved theoretically. Then a correspondent insert algorithm is designed.

APA, Harvard, Vancouver, ISO, and other styles

44

Easwarakumar, K. S., and T. Hema. "BITS-Tree -- An Efficient Data Structure for Segment Storage and Query Processing." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 10 (December 5, 2013): 3108–16. http://dx.doi.org/10.24297/ijct.v11i10.2980.

Full text

Abstract:

In this paper, a new and novel data structure is proposed to dynamically insert and delete segments. Unlike the standard segment trees, the proposed data structure permits insertion of a segment with interval range beyond the interval range of the existing tree, which is the interval between minimum and maximum values of the end points of all the segments. Moreover, the number of nodes in the proposed tree is lesser as compared to the dynamic version of the standard segment trees, and is able to answer both stabbing and range queries practically much faster compared to the standard segment trees.

APA, Harvard, Vancouver, ISO, and other styles

45

Yan, Wanqian, Haiyan Guan, Lin Cao, Yongtao Yu, Cheng Li, and JianYong Lu. "A Self-Adaptive Mean Shift Tree-Segmentation Method Using UAV LiDAR Data." Remote Sensing 12, no. 3 (February 5, 2020): 515. http://dx.doi.org/10.3390/rs12030515.

Full text

Abstract:

Unmanned aerial vehicles using light detection and ranging (UAV LiDAR) with high spatial resolution have shown great potential in forest applications because they can capture vertical structures of forests. Individual tree segmentation is the foundation of many forest research works and applications. The tradition fixed bandwidth mean shift has been applied to individual tree segmentation and proved to be robust in tree segmentation. However, the fixed bandwidth-based segmentation methods are not suitable for various crown sizes, resulting in omission or commission errors. Therefore, to increase tree-segmentation accuracy, we propose a self-adaptive bandwidth estimation method to estimate the optimal kernel bandwidth automatically without any prior knowledge of crown size. First, from the global maximum point, we divide the three-dimensional (3D) space into a set of angular sectors, for each of which a canopy surface is simulated and the potential tree crown boundaries are identified to estimate average crown width as the kernel bandwidth. Afterwards, we use a mean shift with the automatically estimated kernel bandwidth to extract individual tree points. The method is iteratively implemented within a given area until all trees are segmented. The proposed method was tested on the 7 plots acquired by a Velodyne 16E LiDAR system, including 3 simple plots and 4 complex plots, and 95% and 80% of trees were correctly segmented, respectively. Comparative experiments show that our method contributes to the improvement of both segmentation accuracy and computational efficiency.

APA, Harvard, Vancouver, ISO, and other styles

46

Wang, Li-Gen, Tommy Tsan-Yuk Lam, Shuangbin Xu, Zehan Dai, Lang Zhou, Tingze Feng, Pingfan Guo, et al. "Treeio: An R Package for Phylogenetic Tree Input and Output with Richly Annotated and Associated Data." Molecular Biology and Evolution 37, no. 2 (October 24, 2019): 599–603. http://dx.doi.org/10.1093/molbev/msz240.

Full text

Abstract:

Abstract Phylogenetic trees and data are often stored in incompatible and inconsistent formats. The outputs of software tools that contain trees with analysis findings are often not compatible with each other, making it hard to integrate the results of different analyses in a comparative study. The treeio package is designed to connect phylogenetic tree input and output. It supports extracting phylogenetic trees as well as the outputs of commonly used analytical software. It can link external data to phylogenies and merge tree data obtained from different sources, enabling analyses of phylogeny-associated data from different disciplines in an evolutionary context. Treeio also supports export of a phylogenetic tree with heterogeneous-associated data to a single tree file, including BEAST compatible NEXUS and jtree formats; these facilitate data sharing as well as file format conversion for downstream analysis. The treeio package is designed to work with the tidytree and ggtree packages. Tree data can be processed using the tidy interface with tidytree and visualized by ggtree. The treeio package is released within the Bioconductor and rOpenSci projects. It is available at https://www.bioconductor.org/packages/treeio/.

APA, Harvard, Vancouver, ISO, and other styles

47

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

48

Lynch, Thomas B., and Robert F. Wittwer. "n-Tree distance sampling for per-tree estimates with application to unequal-sized cluster sampling of increment core data." Canadian Journal of Forest Research 33, no. 7 (July 1, 2003): 1189–95. http://dx.doi.org/10.1139/x03-036.

Full text

Abstract:

Samples from the n trees nearest to a point or plot center are sometimes used to estimate per-tree values such as age or growth from increment cores. Clutter et al. (J.L. Clutter, J.C. Fortson, L.V. Pienaar, G.H. Brister, and R.L. Bailey. 1983. Timber management: a quantitative approach. John Wiley & Sons, New York) indicated that this procedure can be biased because it is more likely to sample large trees occupying large amounts of space. This sampling procedure falls into the category of n-tree distance sampling in which the nth closest tree to a point defines a plot radius that can be used to estimate number of trees or amount of volume per hectare. When a ratio of n-tree per-hectare estimates is used to estimate per-tree attributes, the resulting estimator is a weighted average in which weights are the inverse of the n-tree sampling plot size. Since this ratio estimator essentially weights observations inversely with plot size, it is not subject to the objections of Clutter et al. (1983). This estimator is used to estimate age by diameter at breast height class for eastern cottonwood (Populus deltoides Bartr. ex Marsh.) on the Cimarron National Grassland.

APA, Harvard, Vancouver, ISO, and other styles

49

Asbeck, T., M. Basile, J. Stitt, J. Bauhus, I. Storch, and K. T. Vierling. "Tree-related microhabitats are similar in mountain forests of Europe and North America and their occurrence may be explained by tree functional groups." Trees 34, no. 6 (August 4, 2020): 1453–66. http://dx.doi.org/10.1007/s00468-020-02017-3.

Full text

Abstract:

Abstract Key message Drivers of the abundance and richness of tree-related microhabitats are similar in mountain forests of Europe and North America and their occurrence may be explained by tree functional groups. Abstract A common approach to support forest-dwelling species in managed forests is to preserve valuable habitat trees. To assess the quality of habitat trees, a hierarchical typology of tree-related microhabitats (TreMs) is applied in the European context for inventory standardization. The first aim of this study was to evaluate whether it is possible to use this hierarchical typology as a standard protocol regardless of location, which is important for potentially standardizing future studies of TreMs, by testing whether the typology could be applied to the western North American mountain forests of Idaho. The second aim of the study was to analyse drivers that influence TreMs in forests of the region. Thirdly, we assessed whether the occurrence of TreMs could be explained by functional groups of trees across the western mountain forests of Idaho and Central European mountain forests, using TreM inventory data previously collected in the Black Forest, Germany. Abundance and richness of TreMs per tree were analyzed as a function of tree species, live status (dead vs. live trees), diameter at breast height (DBH), and site factors (latitude and altitude). Our results show that the TreM typology could be applied with slight modifications in the forests of Idaho. The abundance and richness of TreMs per tree increased with DBH. Snags offered more TreMs per tree than live trees. We were able to group tree species from the two continents in functional groups that were related to the occurrence of certain TreMs. Tree functional groups offer an opportunity to predict the role of certain tree species for habitat provision through TreMs. Combinations of trees from different functional groups could be used to optimize provisioning of TreMs within forest stands.

APA, Harvard, Vancouver, ISO, and other styles

50

Puliti, Stefano, Johannes Breidenbach, and Rasmus Astrup. "Estimation of Forest Growing Stock Volume with UAV Laser Scanning Data: Can It Be Done without Field Data?" Remote Sensing 12, no. 8 (April 14, 2020): 1245. http://dx.doi.org/10.3390/rs12081245.

Full text

Abstract:

Laser scanning data from unmanned aerial vehicles (UAV-LS) offer new opportunities to estimate forest growing stock volume ( V ) exclusively based on the UAV-LS data. We propose a method to measure tree attributes and using these measurements to estimate V without the use of field data for calibration. The method consists of five steps: i) Using UAV-LS data, tree crowns are automatically identified and segmented wall-to-wall. ii) From all detected tree crowns, a sample is taken where diameter at breast height (DBH) can be recorded reliably as determined by visual assessment in the UAV-LS data. iii) Another sample of crowns is taken where tree species were identifiable from UAV image data. iv) DBH and tree species models are fit using the samples and applied to all detected tree crowns. v) Single tree volumes are predicted with existing allometric models using predicted species and DBH, and height directly obtained from UAV-LS. The method was applied to a Riegl-VUX data set with an average density of 1130 points m−2 and 3 cm orthomosaic acquired over an 8.8 ha managed boreal forest. The volumes of the identified trees were aggregated to estimate plot-, stand-, and forest-level volumes which were validated using 58 independently measured field plots. The root-mean-square deviance ( R M S D % ) decreased when increasing the spatial scale from the plot (32.2%) to stand (27.1%) and forest level (3.5%). The accuracy of the UAV-LS estimates varied given forest structure and was highest in open pine stands and lowest in dense birch or spruce stands. On the forest level, the estimates based on UAV-LS data were well within the 95% confidence interval of the intense field survey estimate, and both estimates had a similar precision. While the results are encouraging for further use of UAV-LS in the context of fully airborne forest inventories, future studies should confirm our findings in a variety of forest types and conditions.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Tree data'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles