scholarly journals Influences of determined and estimated dendrometric variables on the precision of volumetric modelling

2021 ◽  
Vol 67 (No. 12) ◽  
pp. 553-561
Author(s):  
José Antonio Aleixo Da Silva ◽  
Rinaldo Luiz Caraciolo Ferreira
Keyword(s):  
Tree Height ◽  
Information Criterion ◽  
Ground Level ◽  
Percentage Error ◽  
Individual Tree ◽  
Significance Level ◽  
Independent Variables ◽  
Semi Arid Region ◽  
Fit Index ◽  
Total Tree

The use of independent variables in volumetric modelling is an important step in fitting models to represent tree or stand characteristics. The DBH measured at 1.3 m from the ground level and total tree height (Ht) are the most commonly used independent variables when modelling individual tree volumes. This work aimed to analyze the importance of independent variables in fitting and selecting volumetric equations. A total of 750 trees from an experiment with three Eucalyptus spp. clones planted in five spacings in the semi-arid region of Pernambuco were used. Four statistical procedures were applied to compare the equations: Adjusted Fit Index (AFI), Akaike information criterion (AIC), mean absolute percentage error (MAPE), and a completely random design having the real tree volume as control and the fit equations as treatments. The error measuring heights in the field (EH) was also analyzed. Four heights were evaluated: Ht, height estimated in the field (He) and heights adjusted (Ha) from hypsometric relationships using the DBH [Ha (a)] and D<sub>1.7</sub> [Ha (b)], which was the diameter most correlated with the volume. The result indicates that all 18 fitted models provided high precision volumetric equations which do not differ at the 5% significance level.

scholarly journals Allometric models to estimate tree height in northern Amazonian ecotone forests

2019 ◽  
Vol 49 (2) ◽  
pp. 81-90 ◽  
Author(s):  
Reinaldo Imbrozio BARBOSA ◽  
Perla Natalia RAMÍREZ-NARVÁEZ ◽  
Philip Martin FEARNSIDE ◽  
Carlos Darwin Angulo VILLACORTA ◽  
Lidiany Camila da Silva CARVALHO
Keyword(s):  
Amazon Basin ◽  
Nonlinear Models ◽  
Tree Height ◽  
Information Criterion ◽  
Specific Model ◽  
Stem Diameter ◽  
Coefficient Of Determination ◽  
Allometric Models ◽  
Peripheral Areas ◽  
Total Tree

ABSTRACT Allometric models defining the relationship between stem diameter and total tree height in the Amazon basin are important because they refine the estimates of tree carbon stocks and flow in the region. This study tests different allometric models to estimate the total tree height from the stem diameter in an ecotone zone between ombrophilous and seasonal forests in the Brazilian state of Roraima, in northern Amazonia. Stem diameter and total height were measured directly in 65 recently fallen trees (live or dead). Linear and nonlinear regressions were tested to represent the D:H relation in this specific ecotone zone. Criteria for model selection were the standard error of the estimate (Syx) and the adjusted coefficient of determination (R²adj), complemented by the Akaike Information Criterion (AIC). Analysis of residuals of the most parsimonious nonlinear models showed a tendency to overestimate the total tree height for trees in the 20-40 cm diameter range. Application of our best fitted model (Michaelis-Menten) indicated that previously published general equations for the tropics that use diameter as the independent variable can either overestimate tree height in the study area by 10-29% (Weibull models) or underestimate it by 8% (climate-based models). We concluded that our site-specific model can be used in the ecotone forests studied in Roraima because it realistically reflects the local biometric relationships between stem diameter and total tree height. Studies need to be expanded in peripheral areas of northern Amazonia in order to reduce uncertainties in biomass and carbon estimates that use the tree height as a variable in general models.

scholarly journals Individual Tree Diameter and Height Growth Models for 30 Tree Species in Mixed-Species and Uneven-Aged Forests of Mexico

Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 429
Author(s):  
Jaime Briseño-Reyes ◽  
José Javier Corral-Rivas ◽  
Raúl Solis-Moreno ◽  
Jaime Roberto Padilla-Martínez ◽  
Daniel José Vega-Nieva ◽  
...  
Keyword(s):  
Tree Species ◽  
Forest Ecosystems ◽  
Growth Models ◽  
Mixed Forest ◽  
Tree Height ◽  
Height Growth ◽  
Site Factors ◽  
Individual Tree ◽  
Species Specific ◽  
Total Tree

Lack of knowledge of individual tree growth in species-rich, mixed forest ecosystems impedes their sustainable management. In this study, species-specific models for predicting individual diameter at breast height (dbh) and total tree height (h) growth were developed for 30 tree species growing in mixed and uneven-aged forest stands in Durango, Mexico. Growth models were also developed for all pine, all oaks, and all other species of the genus Arbutus (strawberry trees). A database of 55,158 trees with remeasurements of dbh and h of a 5-year growth period was used to develop the models. The data were collected from 217 stem-mapped plots located in the Sierra Madre Occidental (Mexico). Weighted regression was used to remove heteroscedasticity from the species-specific dbh and h growth models using a power function of the tree size independent variables. The final models developed in the present study to predict dbh and total tree height growth included size variables, site factors, and competition variables in their formulation. The developed models fitted the data well and explained between 98 and 99% and of the observed variation of dbh, and between 77 and 98% of the observed variation of total tree height for the studied species and groups of species. The developed models can be used for estimating the individual dbh and h growth for the analyzed species and can be integrated in decision support tools for management planning in these mixed forest ecosystems.

scholarly journals HOW TO ESTIMATE BLACK WATTLE ABOVEGROUND BIOMASS FROM HETEROSCEDASTIC DATA?

FLORESTA ◽  
2020 ◽  
Vol 51 (1) ◽  
pp. 028
Author(s):  
Thiago Wendling Gonçalves de Oliveira ◽  
Vinícius Morais Coutinho ◽  
Luan Demarco Fiorentin ◽  
Mateus Niroh Inoue Sanquetta ◽  
Carlos Roberto Sanquetta ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Nonlinear Models ◽  
Basic Density ◽  
Tree Height ◽  
Error Variance ◽  
Total Biomass ◽  
Independent Variables ◽  
Independent Variable ◽  
Black Wattle ◽  
Total Tree

This study developed a system of equations for predicting total aboveground and component biomass in black wattle trees. A total of 140 black wattle trees at age 10 years were measured regarding their diameter at 1.30 m height above the ground (d), total tree height (h), basic wood density (branches and stem), and biomass (stem, crown, and aboveground). We evaluated the performance of linear and nonlinear allometric models by comparing the statistics of R2adj., RRMSE%, and BIC. Nonlinear models performed better when predicting crown biomass (using only d as an independent variable), and stem and aboveground biomass (using d and h as independent variables). Adding basic density did not significantly improve biomass modeling. The residuals had non-homogeneous variance; thus, the fitted equations were weighted, with weights derived from a function containing the same independent variables of the fitted biomass function. Subsequently, we used a simultaneous set of equations to ensure that the sum of each component's estimated biomass values was equal to the total biomass values. Simultaneous fitting improved the performance of the equations by guaranteeing the components' additivity, and weighted regression allowed to stabilize error variance, ensuring the homoscedasticity of the residuals.

Restore and sequester: estimating biomass in native Australian woodland ecosystems for their carbon-funded restoration

2011 ◽  
Vol 59 (7) ◽  
pp. 640 ◽  
Author(s):  
J. H. Jonson ◽  
D. Freudenberger
Keyword(s):  
Native Species ◽  
Basal Area ◽  
Tree Height ◽  
Ground Level ◽  
Stem Diameter ◽  
Allometric Equations ◽  
Total Biomass ◽  
Tree Biomass ◽  
Below Ground ◽  
Total Tree

In the south-western region of Australia, allometric relationships between tree dimensional measurements and total tree biomass were developed for estimating carbon sequestered in native eucalypt woodlands. A total of 71 trees representing eight local native species from three genera were destructively sampled. Within this sample set, below ground measurements were included for 51 trees, enabling the development of allometric equations for total biomass applicable to small, medium, and large native trees. A diversity of tree dimensions were recorded and regressed against biomass, including stem diameter at 130 cm (DBH), stem diameter at ground level, stem diameter at 10 cm, stem diameter at 30 cm, total tree height, height of canopy break and mean canopy diameter. DBH was consistently highly correlated with above ground, below ground and total biomass. However, measurements of stem diameters at 0, 10 and 30 cm, and mean canopy diameter often displayed equivalent and at times greater correlation with tree biomass. Multi-species allometric equations were also developed, including ‘Mallee growth form’ and ‘all-eucalypt’ regressions. These equations were then applied to field inventory data collected from three locally dominant woodland types and eucalypt dominated environmental plantings to create robust relationships between biomass and stand basal area. This study contributes the predictive equations required to accurately quantify the carbon sequestered in native woodland ecosystems in the low rainfall region of south-western Australia.

scholarly journals Biomass functions applicable to European beech

2012 ◽  
Vol 51 (No. 4) ◽  
pp. 147-154 ◽  
Author(s):  
E. Cienciala ◽  
M. Černý ◽  
J. Apltauer ◽  
Z. Exnerová
Keyword(s):  
Tree Height ◽  
European Beech ◽  
Biomass Estimation ◽  
Managed Forests ◽  
Independent Variables ◽  
Breast Height ◽  
Allometric Functions ◽  
Branch Biomass ◽  
Independent Variable ◽  
Total Tree

This material describes parameterization of allometric functions applicable to biomass estimation of European beech trees. It is based on field data from destructive measurements of 20 full-grown trees with diameter at breast height (dbh) from 5.7 to 62.1 cm. The parameterization was performed for total tree aboveground biomass (AB; besides stump), stem and branch biomass, respectively. The allometric functions contained two or three parameters and used dbh either as a single independent variable or in combination with tree height (H). These functions explained 97 to 99% of the variability in the measured AB. The most successful equation was that using both dbh and H as independent variables in combination with three fitted parameters. H, as the second independent variable, had rather a small effect on improving the estimation: in the case of AB, H as independent variable improved prediction accuracy by 1&ndash;2% whereas in the case of branch biomass by about 5%. The parameterized biomass equations are applicable to tree specimens of European beech grown in typically managed forests.

scholarly journals Nonlinear yield models for young Tectona grandis L. f. stands in Nnamdi Azikiwe University Awka, Southeastern Nigeria

2020 ◽  
Vol 7 (3) ◽  
pp. 678-683
Author(s):  
Onyekachi Chukwu ◽  
◽  
Anabel A. Emebo ◽  
Keyword(s):  
Predictive Ability ◽  
Tree Height ◽  
Tectona Grandis ◽  
Information Criterion ◽  
Site Quality ◽  
Variable Model ◽  
Southeastern Nigeria ◽  
Individual Tree ◽  
The Mean ◽  
Non Destructive

Yield models are very important to forest management, especially for site quality assessment, subsequent inventories, timber valuation and assessment of stand growth. This study developed yield models for the young Tectona grandis stands in Nnamdi Azikiwe University Awka, Southeastern Nigeria. These models were necessary to the guide forest managers in timber valuation as well as monitoring growth of the stand. Data for this study was collected through complete enumeration method, tree height and stem diameters of the 295 Teak stands were measured. Non-destructive method (Newton’s formula) was used in computing individual tree volumes. The tree growth variables data were subjected to descriptive statistics and used for fitting five nonlinear regression functions. The mean stem height, diameter at breast height and volume were 10.6 m, 8.9 cm, 0.032 m3, respectively. Out of the five yield equations fitted; the generalized combined variable model had the best predictive ability; with the lowest root mean square error (0.0084 m3) and Akaike information criterion (-2809). Therefore, the generalized combined variable model was recommended for yield estimation of Tectona grandis.

Estimating Weights of Tree Components of Lodgepole Pine from Large-Scale Aerial Photographs

1971 ◽  
Vol 1 (3) ◽  
pp. 193-194
Author(s):  
A. D. Kiil
Keyword(s):  
Large Scale ◽  
Lodgepole Pine ◽  
Tree Height ◽  
Aerial Photographs ◽  
Precise Estimate ◽  
Independent Variables ◽  
Crown Width ◽  
Air Photo ◽  
Total Tree ◽  
Fuel Components

Sixty-three lodgepole pine (Pinuscontorta Dougl. var. latifolia Engelm.) trees were measured on the ground, felled, and their crowns and stems were weighed. The combined independent variables of tree height and crown width gave the most precise estimate of fuel components. No significant differences were found between ground and air photo measurements of total tree height and crown width. Hence, the weight of all branchwood, entire crown, and entire tree can be estimated by the use of large-scale aerial photographs.

scholarly journals Automatic Detection and Parameter Estimation of Ginkgo biloba in Urban Environment Based on RGB Images

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Kai Xia ◽  
Hao Wang ◽  
Yinhui Yang ◽  
Xiaochen Du ◽  
Hailin Feng
Keyword(s):  
Neural Network ◽  
Parameter Estimation ◽  
Inventory Management ◽  
Ginkgo Biloba ◽  
Tree Height ◽  
Urban Trees ◽  
Percentage Error ◽  
Individual Tree ◽  
Tree Crowns ◽  
Rgb Images

Individual tree crown detection and morphological parameter estimation can be used to quantify the social, ecological, and landscape value of urban trees, which play increasingly important roles in densely built cities. In this study, a novel architecture based on deep learning was developed to automatically detect tree crowns and estimate crown sizes and tree heights from a set of red-green-blue (RGB) images. The feasibility of the architecture was verified based on high-resolution unmanned aerial vehicle (UAV) images using a neural network called FPN-Faster R-CNN, which is a unified network combining a feature pyramid network (FPN) and a faster region-based convolutional neural network (Faster R-CNN). Among more than 400 tree crowns, including 213 crowns of Ginkgo biloba, in 7 complex test scenes, 174 ginkgo tree crowns were correctly identified, yielding a recall level of 0.82. The precision and F -score were 0.96 and 0.88, respectively. The mean absolute error (MAE) and mean absolute percentage error (MAPE) of crown width estimation were 0.37 m and 8.71%, respectively. The MAE and MAPE of tree height estimation were 0.68 m and 7.33%, respectively. The results showed that the architecture is practical and can be applied to many complex urban scenes to meet the needs of urban green space inventory management.

scholarly journals The Potential of Widespread Ready-Made UAVs in Quantifying Conifers and Delineating Their Crowns

2021 ◽  
Author(s):  
Jan Komárek ◽  
Petr Klápště ◽  
Karel Hrach ◽  
Tomáš Klouček
Keyword(s):  
Data Acquisition ◽  
Stand Structure ◽  
Low Cost ◽  
Tree Height ◽  
Ground Level ◽  
Absolute Error ◽  
Spectral Information ◽  
Individual Tree ◽  
Crown Delineation ◽  
The Individual

Abstract With the ever-improving Earth observation capabilities, variables such as tree health status, biomass storage, or stand structure are increasingly estimated through remote sensing. While many protocols of data acquisition and satellite data processing are in place, the still novel unmanned aerial vehicles (UAVs) face some challenges during data acquisition and processing. While tree height extraction seems to be a common practice, identifying individual trees and measuring their crowns is still quite tricky. We performed several flights with three different UAVs and four different popular sensors over two sites with coniferous forests of various ages at flight levels of 100–200 m above ground level (AGL) using custom settings preset by UAV solution suppliers. Considering the success rate of the individual tree identification, casual RGB cameras provided more consistent results at all flight levels (84 − 77% for Phantom 4), while the success of tree identification decreases with higher flight levels and smaller crowns in the case of multispectral cameras (77 − 54% for RedEdge-M). In general, RGB cameras yielded the best results at 150 m AGL while multispectral cameras at 100 m AGL. Regarding the accuracy of the measured crown diameters, most datasets tended to overestimate when using automatic crown delineation within the lidR package. Only RGB cameras yielded satisfactory results (Mean Absolute Error – MAE of 0.79–0.99 m and 0.88–1.16 m for Phantom 4 and Zenmuse X5S, respectively). Multispectral cameras overestimated more than RGB cameras, especially in the full-grown forest (MAE = 1.26–1.77 m); on the other hand, they offered, in addition to the structural, also spectral information. We conclude that widespread ready-made solutions mounted with low-cost RGB cameras yield very satisfactory results for describing the structural forest information at 150 m AGL. When (multi)spectral information is needed, we recommend reducing the flight level to 100 m AGL to acquire sufficient structural forest information.

scholarly journals New generalized height-diameter models for birch in European Russia

2020 ◽  
Vol 26 (2) ◽  
Author(s):  
Aleksandr Lebedev
Keyword(s):  
Forest Inventory ◽  
Tree Height ◽  
Information Criterion ◽  
Field Work ◽  
European Russia ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Sampling Effort ◽  
Birch Trees ◽  
Performance Statistics

Height and diameter at breast height are basic variables that are measured in a forest inventory. Generalized models do not require measuring tree heights or number of measurements is minimal. The purpose of this study was to obtain 24 new generalized height-diameter models based on simple basic models, compare them with 9 generalized models selected from other studies, and develop an appropriate height-diameter model for birch in the European Russia. To select models which better describe the relationship between the heights and diameters of the trees, six metrics were used – root mean square error (RMSE), mean absolute percentage error (MAPE), coefficient of determination (R2), adjusted coefficient of determination (R2-adj.), Akaike information criterion (AIC) and Bayesian information criterion (BIC). Results show that there are slight differences between all models. The performance statistics showed that model M24 is the most suitable and recommended for predicting the height-diameter relationships for birch trees in this study area. The predicting variables for applying developed generalized models to estimate total tree height require less sampling effort and are derived from conventional forest inventory data which allows to reduce costs and time consumption in field work.

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