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Taper equations are indispensable tools for characterizing the stem profile of trees, providing valuable insights for forest management, timber inventory, and optimal assortments allocation. The recent progress in Terrestrial Laser Scanning (TLS) has revolutionized forest inventory practices by enabling non-destructive data collection. In this study, four taper models from three different model categories were established based on point cloud data of 219 Pinus nigra trees. The taper equations fitted with TLS data were used to predict the diameter at specific stem heights and the total stem volume. The results show that among fitted models, the Max and Burkhart segmented model calibrated by the means of a mixed-effects approach provided the best estimate of the diameter at different heights and the total stem volume evaluated for different diameter at breast height (DBH) classes. In numerical terms, this model estimated the diameter and the volume with a respective overall error of 0.781 cm and 0.021 m3. The predicted profile also shows that above a relative height of 0.7, the diameter error tends to increase due to the low reliability of data collected beyond the base of the crown primarily caused by interference from branches and leaves. Nevertheless, this study shows that TLS technology presents a compelling opportunity and a promising non-destructive alternative for generating taper profiles and estimating tree volume.

Spatial biomass estimation using remote sensing at a regional or national scale requires ground reference plots for developing calibration models and product validation. The reference plot above-ground biomass (AGB) estimates rely on allometric models, which estimate tree-level AGB through measurements of tree diameter, height, and species information. Recent developments in applying terrestrial laser scanning (TLS) to measure 3D canopy structure in great detail have enabled new opportunities for extracting tree volumes non-destructively. In this study, we aim to use 3D point clouds from TLS to model individual trees to extract tree volumes and thereby generate a framework for developing local allometric equations in tropical dry deciduous forests of Betul, Madhya Pradesh, India. We have used TLS scans of 127 individual trees across different species to generate site-level and species-specific allometric models. The generated TLS-based allometric models using diameter and height as predictor variables are validated with an independent destructive sampling dataset (n = 25 trees). Our TLS allometry models indicate superior predictions with lower error estimates (root mean square error (RMSE) of 10.9% (concordance correlation coefficient [CCC] = 0.98) compared to the equivalent traditionally used volume equations over the study site. We have also evaluated the uncertainty due to sample size and found that the prediction error stabilizes when the number of samples exceeds 100 trees. The results imply that TLS data can potentially increase the range and sampling size of allometric equations through non-destructive volume estimation to improve the traditional allometric models and reduce uncertainty in landscape-level biomass estimates. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Grey poplar (Populus× canescens Smith.) is a natural hybrid of white poplar (Populus alba L.) and Eurasian aspen (Populus tremula L.). It can be found throughout Europe, where both parents are present. The above mentioned species of poplars (under the term of 'domestic poplars') cover approximately 5% of the forests of Hungary. Of these species, grey poplar holds significance in forestry, and its role in afforestation shows a growing tendency. For this reason, improving the growing technology of grey poplar is a timely topic. In this paper we introduce algorithms which help estimate grey poplar tree volumes without having to use volume tables. Based on the performed evaluations, both equations can be used for single tree volume estimation with an error of less than 5%. [ABSTRACT FROM AUTHOR]

Wood volume is the variable that best represents the yield of planted forests, and several regression models are used in its estimation. Artificial neural networks (ANNs) are recognised for their accuracy and generalisation capacity associated with the quality and quantity of data in training and validation. Box–Müller transformation generates random variables from the original data and provides a consistent dataset. Given the above, the hypothesis of this research is that the expansion of data by the Box–Müller theorem provides more accurate estimates for predicting wood volume in eucalyptus species. The objectives were to (i) to evaluate the efficiency of the Box–Müller method for expanding the dataset of eucalyptus sample tree cubing, (ii) use different ANN topologies to predict the wood volume of different Eucalyptus species, and (iii) compare the estimates with those obtained by using the Schumacher and Hall model. The experimental design used randomised blocks with four replicates, composed of the following treatments: Corymbia citriodora and different Eucalyptus species. Sample trees were cubed at ages 2 years and 4.5 years. The estimated volume was obtained using the Schumacher and Hall non-linear regression model for each species and compared with the ANNs through Pearson's correlation, and root mean square error at the steps training, validation, and utilisation. Two ANN architectures were tested, multilayer perceptron (MLP) and radial basis function (RBF). Dataset expansion of cut-down sample trees for cubing is efficient and can be used for ANNs training when there are cubing restrictions of sample size. The topology with seven neurons in the first hidden layer and 12 in the second with expanded data of RBF showed better performance for predicting wood volume. When evaluating all species, the accuracy of the estimates provided by ANNs was higher than that obtained with non-linear regression. [ABSTRACT FROM AUTHOR]

The adjustment of volumetric equations, as well as the form factor by species, represents valuable tools for conducting sustainable management plans. So the goal of this study was to evaluate the employment of volumetric equations and form factor to estimate the wood volume of native species from the Amazon biome. Two hundred nineteen trees, distributed in eleven species, were cut down and dragged to the storage patio for scaling by the Smalian method. Eight mathematical models were tested with simple and double entries, whose independent variables were their DBH and diameter at commercial height. The dependent variables were the commercial volume outsidebark, by species and for the mix of species. The statistics were analyzed alongside a graph for the observed and estimated volumes, and a graph for the residual dispersion and the average residual. The form factor was calculated both by species and for the mix of species. In general, the model that resulted in the best estimative was the Schumacher-Hall method. The same can be observed for the mix of species. The average form factor was 0.7978, differing from the established by the legislation, which is equal to 0.7. [ABSTRACT FROM AUTHOR]

Prediction of aboveground wood volume is one of most important stages when conducting a forest inventory and making forest management decisions. This is more difficult for native forest than for plantations given the high variability of the former (trees of different species and age groups). The objective of this work was to evaluate different strategies to estimate aboveground standing tree wood volume (v) using its diameter at breast height (DBH) and total height (h), comparing the use of form factors, volume equations fitted by ordinary least squares and mixed modelling, as well as the options from the literature. To achieve this, 351 trees were scaled during field campaigns, with 158 felled trees and 193 measured using Criterion equipment. The data collected from each scaled tree was: h, DBH, v and identification of the botanical species. We found that the best application of form factors occurred when the trees were divided by diameter classes. However, regression models, regardless of the fitting technique, presented better volume estimates than form factors. Mixed models, with either the species or diameter class as the random variable, provided the lowest errors when estimating tree volume. Thus, we recommend the use of mixed models as the best strategy to estimate volume of standing trees. The following equation can be used to estimate aboveground wood volume for trees from vegetation types similar to the ones of this study: ln(v) = −9.06013 + 1.91756 ln(DBH) + 0.69846 ln(h). [ABSTRACT FROM AUTHOR]

The coppice is a very flexible cultural system producing several calibers adapting to the demands of the market. Small-caliber roundwood from sweet chestnut (Castanea sativa Mill.) coppices, formerly in great demand, is now less interesting for the market. Thus, the improvement of coppices management by applying alternative silvicultural models in order to obtain benefits and sustainability is essential. For this purpose, four permanent plots (P1–P4) were established in 1994 to monitor different coppice management systems. The plots were installed in a coppice which resulted from the final clear cut of a sweet chestnut high-forest stand in 1992, at 50 years old. Three silvicultural management models were tested in order to produce roundwood of small (P1), medium (P2), and large (P4) diameters. A control plot was established without any type of silviculture which corresponds to most of the existing chestnut coppices (P3 = without intervention). Thinnings were applied in the plots according to the respective management model. Twenty-four years after the sprouting of the coppice, the silvicultural models were evaluated according to their objectives in terms of growth, yield, and quality of the sawlogs. This assessment period corresponds to the end of the rotation period for P1, and the results are in accordance with expected values. In P2 and P4 the observed growth closely matches expectations for this growth stage of the coppice. The quality of the sawlogs is clearly superior to that of the plot without intervention. Comparing the mean dendrometric values, higher values were observed in plots where the models were applied. The results also show that when roundwood is used for saw-timber, silvicultural management is essential. [ABSTRACT FROM AUTHOR]

Copyright of Revista Chapingo Serie Ciencias Forestales is the property of Universidad Autonoma Chapingo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Inventories are time- and money-consuming. Hence, accurate equations to estimate difficult-to-measure variables are desirable, especially for species that are not commercially established, such as Pinus lawsonii, P. leiophylla, P. pringlei and P. oocarpa. This study aimed to fit height and volume models for these species and to present stand attribute values for a plantation located in Guarei, Brazil, belonging to the company Resinas Brasil. Models were assessed by the adjusted coefficient of determination, mean square error and residual plots. For P. lawsonii and P. pringlei, the best hypsometric models were those of Van Soest and Mishailof, respectively. For P. leiophylla at 3 m × 1.5 m and 3 m × 3 m spacing, the best models were the linear and Mishailof models, respectively. For P. oocarpa planted at 3 m × 1.5 m and 3 m × 3 m spacing, the best models were those of Mishailof and Van Soest, respectively. The best volume model was the logarithmic Spurr for all species, except for P. oocarpa, where the Spurr model was the best. The mean stem form factor for all species was 0.53. Mean annual increment ranged from 8.4 to 24.5 m3 ha−1 (P. lawsonii and P. oocarpa), which can be considered satisfactory for plantations without genetic improvement and fertilisation, enforcing the species' commercial potential. [ABSTRACT FROM AUTHOR]

Stem volume equations were fitted for Cupressus lusitanica in Gergeda Forest, Ethiopia using six different established equation forms. A total of 260 trees were measured for their diameter at breast height (D), total height (H )and stem volume using destructive sampling methods. The data set was randomly divided into equal size for equation development and equation validation. Five fit statistics comprising of the fit index, root mean square error, bias (Ē ), absolute mean deviation and coefficient of variation were used to evaluate the performance of each equation. Among the different equations, the Schumacher and Hall function of the form V = b1Db2Hb3 (model 5), which estimates volume (V ) using diameter at breast height and total height as predicting variables, performed best and was then fitted to the combined data set for prediction of volume over-bark of C. lusitanica in Gergeda Forest. Overall, volume equations with two independent variables (D and H ) performed better than those with only one variable (D). The equations developed in this study can provide forest managers with accurate estimations of stem volumes for C. lusitanica in Gergeda Forest. [ABSTRACT FROM AUTHOR]

The diversity of species in native tropical forests causes difficulty in the interpretation of data that support their management and conservation. Species grouping, based on characteristics of interest, reduces significantly the number of volume equations and helps solve the problem of undersampling rare species. This study aims to group 32 Amazonian trees species of commercial interest based on regression coefficients of the Schumacher and Hall's model and their fit statistics. To accomplish this, we employ a two-stage approach, in which we first applied cluster analysis to classify species with higher sampling intensity (n > 30). This phase allowed us to allocate poorly sampled species (n < 30) to groups created by discriminant analysis, resulting in the second stage. This proposed approach has proven adequate for grouping timber species in the Amazon forest, and so the stem volume can be modelled on consistent groups of species. The grouping of Amazon rainforest commercial species, based on the regression coefficients and fit statistics, performs better in aggregation for the stem volume modelling, providing stabilisation of estimation error and supplying few equations for the evaluation of standing stock. [ABSTRACT FROM AUTHOR]

Objetivou-se, neste trabalho, avaliar o ajuste do modelo volumétrico de Schumacher e Hall por diferentes algoritmos, bem como a aplicação de redes neurais artificiais para estimação do volume de madeira de eucalipto em função do diâmetro a 1,30 m do solo (DAP), da altura total (Ht) e do clone. Foram utilizadas 21 cubagens de povoamentos de clones de eucalipto com DAP variando de 4,5 a 28,3 cm e altura total de 6,6 a 33,8 m, num total de 862 árvores. O modelo volumétrico de Schumacher e Hall foi ajustado nas formas linear e não linear, com os seguintes algoritmos: Gauss-Newton, Quasi-Newton, Levenberg-Marquardt, Simplex, Hooke-Jeeves Pattern, Rosenbrock Pattern, Simplex, Hooke-Jeeves e Rosenbrock, utilizado simultaneamente com o método Quasi-Newton e com o princípio da Máxima Verossimilhança. Diferentes arquiteturas e modelos (Multilayer Perceptron MLP e Radial Basis Function RBF) de redes neurais artificiais foram testados, sendo selecionadas as redes que melhor representaram os dados. As estimativas dos volumes foram avaliadas por gráficos de volume estimado em função do volume observado e pelo teste estatístico L&O. Assim, conclui-se que o ajuste do modelo de Schumacher e Hall pode ser usado na sua forma linear, com boa representatividade e sem apresentar tendenciosidade; os algoritmos Gauss-Newton, Quasi-Newton e Levenberg-Marquardt mostraram-se eficientes para o ajuste do modelo volumétrico de Schumacher e Hall, e as redes neurais artificiais apresentaram boa adequação ao problema, sendo elas altamente recomendadas para realizar prognose da produção de florestas plantadas.This research aimed at evaluating the adjustment of Schumacher and Hall volumetric model by different algorithms and the application of artificial neural networks to estimate the volume of wood of eucalyptus according to the diameter at breast height (DBH), total height (Ht) of the clone. For such, 21 scalings of stands of eucalyptus clones were used with DBH ranging from 4,5 to 28,3 cm and total height ranging from 6,6 to 33,8 m. The Schumacher and Hall volumetric model was adjusted linearly and nonlinearly with the following algorithms: Gauss-Newton, Quasi-Newton, Levenberg-Marquardt, Simplex, Hooke-Jeeves Pattern, Rosenbrock Pattern; Simplex, Hooke-Jeeves, and Rosenbrock, used simultaneously with the Quasi-Newton method and the principle of Maximum Likelihood. Different architectures and models (Multilayer Perceptron - MLP and Radial Basis Function - RBF) of artificial neural networks were tested and the networks that best represented the data were selected. Estimates of the volumes were evaluated by graphics of estimated volume according to the observed volume and by the L&O statistical test . It was concluded that the adjustment of the Schumacher and Hall model can be used in its linear form, with good representation and without presenting bias of the data; the Gauss-Newton, Quasi-Newton and Levenberg-Marquardt algorithms were effective in the adjustment of Schumacher and Hall volumetric model. The artificial neural networks showed good adequacy to the problem and are highly recommended to perform production prognoses of planted forests.

Copyright of Forestry Chronicle is the property of Canadian Institute of Forestry and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Medidas precisas de volume de madeira são ferramentas importantes no planejamento do uso do recurso florestal. Neste estudo, foram investigados modelos volumétricos para a Floresta Nacional do Tapirapé-Aquirí, na Serra dos Carajás (PA), baseados numa cubagem rigorosa de 55 árvores para obter o diâmetro, altura comercial do fuste e volume sólido. Um total de 8 modelos de dupla entrada e 4 de simples entrada foram testados para o diâmetro mínimo de 14 cm. Para seleção do melhor modelo foram usadas as estatísticas do coeficiente de determinação, erro padrão da estimativa e distribuição dos resíduos. Entre os modelos de simples entrada o modelo logarítmico de Husch se ajustou melhor aos dados (R² = 0,9105) e entre os de dupla entrada o logarítmico de Schumacher & Hall se ajustou melhor (R² = 0,9942). O uso do modelo da Flona de Tapajós ou o uso do modelo de volume cilíndrico com fator de forma 0,7 subestimam a volumetria na Flona do Tapirapé. Isso enfatiza a importância de modelos volumétricos locais para melhorar a precisão da estimativa de madeira.Accurate volume estimate is a crucial variable for effective forest management in the tropics. In this study, we investigated volumetric models for Tapirapé-Aquirí National Forest in Carajás, PA, Brazil, based on 55 cubed trees by obtaining dbh, stem commercial height, and solid stem volume. A total of 8 double- and 4 single-entry models were tested for minimum dbh at 14 cm. Statistical procedures, such as coefficient of determination (R²), distribution of residuals, and standard error of estimate, were used to evaluate the accuracy of the estimates. Among simple-entry models, Husch logarithmic model showed the best fit to the data (R² = 0.9105), whereas Schumacher & Hall logarithmic model showed the best performance among double-entry models (R² = 0.9942). One previously published regression model, developed for Tapajós National Forest, and a taper function with a form factor of 0.70 were also cross-validated against the trees of this study. These two models subestimated the true volume. This study therefore highlights the importance of developing local volumetric models in order to obtain accurate estimates.

This research aimed to evaluate the volumetric models fitting for Eucalyptus clone using normal and t-Student distributions, based on data from an experiment implanted at the Agronomic Institute of Pernambuco (IPA) in São Bento do Una, PE. In order to set the modified volumetric models of Silva and Bailey, modified Chapman and Richard, Schumacher and Hall, and modified Brody, we used data from 62 trees rigorously scaled by Smalian method. The criteria for equation comparing were the weighted value (PV) between the corrected index adjustment (IAc) and absolute mean error percentage (EPAM). According to the results, the model that best fits for the two distributions is Schumacher and Hall, with better adjustment related to the Student-t distribution. The t-Student distribution promoted improvements of equations regarding the Normal distribution, compared to the two distributions per equation. [ABSTRACT FROM AUTHOR]

The construction of volume tables for black alder [Alnus glutinosa (L.) Gaertn.] trees growing in even-aged stands ofthe Southern Belgium. This article deals with the construction of tree volume tables for black alder (Alnus glutinosa (L.)Gaertn.) in the Southern part of Belgium. Regression equations are calculated for estimating the volume over bark from stumpto a top girth of 22 cm, excluding all branches. A total of 210 felled trees were used in this analysis and collected from 29even-aged stands of black alder located in a large range of ecological and silvicultural conditions in the Southern part ofBelgium. For the tree volume table construction, we have used measurements such as total height, girth at breast height andgirths at fixed heights. We have built equations by weighted least squares method for estimating volume of black alder treeexpressed as a function of one variable (girth at 1.3 m) or two independent variables (girth at 1.3 m and total height, girth at1.3 m and dominant height of the stand). The volume can also be converted in other volumes limited to fixed girths usingratios calculated from appropriate equations. The study is limited to black alder trees growing in even-aged stands of theSouthern Belgium.

Although the small-leaved lime (Tilia cordataMill.) is a native tree in the Czech Republic, there are no volume tables, and its volume has so far been estimated according to beech (Fagus sylvaticaL.) tables. In order to increase accuracy of timber volume calculations, the most appropriate volume equations should be selected to develop volume tables specifically for lime. Based on literature sources eight volume equations were selected, and their accuracy was tested by statistical evaluation of assessed parameters and differences between calculated and sampled lime tree volume. Eighty-one sample trees were randomly selected for this study. The most suitable equation was Børset's equationaccording to the evaluation of equation parameters and comparison of the results obtained from the volume formula and from sample trees (difference of mean value 0.000009 m3). Finally, the calculated lime volumes were compared with the beech tables. The lime volumes are higher than beech volumes according to beech tables and positive differences for the lime, which varied from 0.05 m3 to 0.35 m3, support the need for new lime volume table. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: The amount of urban biomass waste derived from pruning operations represents a potential source of bioenergy little studied or considered in local bio-economies. This research focused on direct quantification of lignocellulosic residual biomass yielded during tree pruning, characterization of basic tree parameters and development of indirect biomass prediction models. Sample individuals of 30 Platanus hispanica Münchh. with mean diameter at breast height 23.56 cm, crown diameter 8.44 m, crown base height 3.76 m, and total height 11.57 m were examined. Wood formed 43.34% of pruned biomass before the drying process and wood moisture content in wet basis reached 40.16%. Mean quantity of dry biomass obtained per tree was 23.98 kg and standard deviation was 15.16 kg. Allometric relationships were analyzed. Significant coefficients of determination were observed for dry biomass and diameter at breast height (R 2 = 0.87), as well as for dry biomass and conical and parabolic crown volume (R 2 = 0.78). The best result (R 2 = 0.93) was obtained from a multiple regression model with several explicative variables. Indirect biomass prediction equations and characteristics of yielded residuals derived from this research can be useful for biomass planning and management purposes. These equations can be implemented for urban inventories, and the application of logistic models. The significance of this topic is beyond doubt for urban environment, especially for the possibilities of reducing carbon dioxide emissions and perspectives of biomass utilization as a biofuel. [Copyright &y& Elsevier]

Abstract: Large quantity of residual biomass with possible energy and industrial end can be obtained from management operations of urban forests. The profitability of exploiting these resources is conditioned by the amount of existing biomass within urban community ecosystems. This research was focused on direct and indirect quantification of lignocellulosic waste from urban tree pruning of Morus alba, which is widely deployed as ornamental vegetation in Mediterranean countries. The mean quantity of dried pruned biomass obtained in street and park location was 31.67 kg/tree and 77.78 kg/tree with standard deviation 16.88 kg/tree and 29.51 kg/tree, respectively. Mathematical models for predicting the available amount of pruning residues for this species were developed from easily measurable dendrometric parameters, such as diameter at breast height, crown diameter and total tree height. The best functions were obtained when several variables were combined in quadratics models. R 2 was 0.96 for topping type of pruning practice and street location, and 0.88 in maintenance pruning applied in park areas. Good results were also found when correlating apparent crown volume with kilograms of yielded residues. These models can be used for urban inventories and the application of logistic models. The analysis indicates that an abundant amount of residual biomass originating from pruning operations of ornamental species can be used to achieve ecological and energy targets. [Copyright &y& Elsevier]

Stem volume equations (overbark) were developed, using established volume equation forms, and validated using a subset of the data collected forPinus kesiyain Benguet province, Philippines. A total of 481 trees fromPinus kesiyastands in Benguet were measured through non-destructive sampling. The data set was randomly split into two subsets for initial model development (80% of the data set) and validation (20% of the data set). The performance of the different models was evaluated using evaluation statistics: fit index (FI), root mean square error (RMSE), bias (Ē), absolute mean difference (AMD) and coefficient of variation (CV%). The best model forms were selected for final model development using the combined data set (100%). Overall, volume models with two independent variables (DBH and total height) performed better than models with only one (DBH). In the validation of the models, it was observed that AMD of the models converged in the DBH classes with higher sample size. Furthermore, one of the best models in this study, Model 2, also performed better when compared to the general single volume equation developed for the non-dipterocarp species in regions 1, 2, 3 and the Cordillera Administrative Region (CAR) of the Philippines. The models developed in this study may assist forest managers acquire improved stem volume predictions ofPinus kesiyain the forests of Benguet, Philippines. [ABSTRACT FROM AUTHOR]

A system of additive equations was developed to predict whole-tree volume and the different components of Corsican pine. In this work, the nonlinear seemingly unrelated regression (NSUR) approach, which guarantees additivity in nonlinear equations, was evaluated. The effect of bark thickness on the accuracy of the results for all tree components was also assessed. Data for 351 trees, ranging in age from 10 to 72 years, were collected from 65 public and private sites. The volume estimates show average biases that range in absolute values from 2.19 to 31.02 dm3 for whole-tree, from 1.41 to 27.31 dm3 for wood, and from 1.05 to 16.52 dm3 for bark volume components. Errors in volume predictions were relatively small, representing less than 3% of the average observed wood volume and less than 6% of the average observed bark volume. This research showed that satisfactory predictions can be obtained from forcing additivity using NSUR approach with a minimal number of easily measurable tree variables, such as dbh and total height. [ABSTRACT FROM AUTHOR]

Abstract: Large quantity of residual biomass with possible energy and industrial end can be obtained from management operations of urban forests. The profitability of exploiting this resource is conditioned by the amount of existing biomass within urban community ecosystems. Prior research pointed out that residual biomass from Platanus hispanica and other tree species can be calculated from dendrometric parameters. In this study, two approaches have been analyzed: First, applicability of TLS was tested for residual biomass calculation from crown volume. In addition, traditional models for residual biomass prediction were developed from dendrometric parameters (tree height, crown diameter, and diameter at breast height). Next, a comparison between parameters obtained with both methodologies (standard methodologies vs TLS) was carried out. The results indicate a strong relationship (R 2 =0.906) between crown diameters and between total tree heights (R 2 =0.868). The crown volumes extracted from the TLS point cloud were calculated by 4 different methods: convex hull; convex hull by slices of 5cm height in the XY plane; triangulation by XY flat sections, and voxel modeling. The highest accuracy was found when the voxel method was used for pruned biomass prediction (R 2 =0.731). The results revealed the potential of TLS data to determine dendrometric parameters and biomass yielded from pruning quitar of urban forests. [Copyright &y& Elsevier]

Abstract: The amount of residual biomass from pruning operations of urban trees is a potentially abundant, and an underutilized source that could contribute significantly more to regional and national bio-economies than it does at present. Better utilization of woody biomass from urban green space, leisure and industrial areas could offer bio-based fuels for heat and power generation, reduce pressure on forests and reduce the management costs on a local and regional level. The aim of the work was to quantify woody biomass proceeding from pruning operations and verify the potential of using allometric relationships developed for urban forests. Quantitative results of the residual wood biomass obtained from annual pruning operations of Sophora japonica are presented in the paper according to the type of pruning practice applied. Wood formed 59.97% of total weight of all pruned material before the drying process, wood moisture content in wet basis was 44.88% and mean quantity of dry biomass (branches without leaves) obtained per tree was 18.07 kg. Regression models were applied to predict weight of dry biomass obtained per tree. Significant relationship was observed between quantity of biomass and diameter at breast height at R 2 = 0.60. The analysis indicates that an abundant amount of residual biomass originating from pruning operations of ornamental species can be used to achieve ecological and energy targets. Moreover, the presented methodology creates a tool for better prediction of income, field work and logistics management for the future. [Copyright &y& Elsevier]