scholarly journals Crown Area as a Parameter for Biomass Estimation of Croton sonderianus Müll. Arg.

2019 ◽  
Vol 26 (4) ◽  
Author(s):  
Jeferson Luiz Dallabona Dombroski ◽  
José Rivanildo de Souza Pinto
Keyword(s):  
Plant Height ◽  
Plant Biomass ◽  
Remote Sensing Data ◽  
Biomass Estimation ◽  
Tree Biomass ◽  
Basal Diameter ◽  
Crown Area ◽  
Breast Height ◽  
Multiple Stems ◽  
Non Destructive

ABSTRACT Current tree biomass estimation techniques generally use remote sensing data and allometric models for validation, which relate non-destructive parameters to plant biomass, usually employing diameter at the plant base or breast height and plant height. In the Caatinga Biome, many plants present multiple stems, thus making it difficult to measure the plant diameter, and lost branches, which are difficult to correct for. Hence, there is a need for suitable models for Caatinga plants, as well as studies on the possibility of using other parameters. For this study, plant and branch basal diameter, plant height, and crown area of Croton sonderianus plants were measured, and plants were also collected and weighed. Several classic models and their variations were tested. The best models were variations of Naslund (R2 = 0.92; rmse = 1,221) and Schumacher & Hall (R2 = 0.92; rmse = 1,217). Plant height and crown area enables a better biomass estimation than using plant or branch basal diameter.

scholarly journals Aboveground Biomass Estimation for Three Common Woody Species in the Post Oak Savannah of Texas

2010 ◽  
Vol 34 (2) ◽  
pp. 91-94 ◽  
Author(s):  
Brian P. Oswald ◽  
R. R. Botting ◽  
Dean W. Coble ◽  
Ken W. Farrish
Keyword(s):  
Fire Behavior ◽  
Dry Weight ◽  
Biomass Estimation ◽  
Juniperus Virginiana ◽  
Eastern Redcedar ◽  
Variable Model ◽  
Basal Diameter ◽  
Crown Area ◽  
Logarithmic Model ◽  
Post Oak

Abstract The post oak savannah of Texas contains many shrubs and trees species that lack standing biomass estimation. Nondestructive biomass prediction equations for dry weight (g) and fuel size classes (to accurately assess fuels hazards and potential fire behavior) were determined for post oak (Quercus stellata Wangenh.), eastern redcedar (Juniperus virginiana L.), and gum bumelia (Sideroxylon lanuginosum Michx. subsp. oblongifolium [Nutt] T.D. Penn) using basal diameter, height, and crown area. Five models (full model, full log model, combined variable model, logarithmic model, and combined variable model with crown area) were performed and compared. The logarithmic model provided the best results for predicting dry weight. The logarithmic model was the only one that performed well for any fuel size parameter (post oak foliage and eastern redcedar 1 hour fuel size).

scholarly journals Terrestrial laser scanning for plant height measurement and biomass estimation of maize

2014 ◽  
Vol XL-7 ◽  
pp. 181-187 ◽  
Author(s):  
N. Tilly ◽  
D. Hoffmeister ◽  
H. Schiedung ◽  
C. Hütt ◽  
J. Brands ◽  
...  
Keyword(s):  
Plant Height ◽  
Precision Agriculture ◽  
Laser Scanning ◽  
Point Clouds ◽  
Time Frame ◽  
Coefficient Of Determination ◽  
Biomass Estimation ◽  
Height Measurement ◽  
Growing Period ◽  
Non Destructive

Over the last decades, the role of remote sensing gained in importance for monitoring applications in precision agriculture. A key factor for assessing the development of crops during the growing period is the actual biomass. As non-destructive methods of directly measuring biomass do not exist, parameters like plant height are considered as estimators. In this contribution, first results of multitemporal surveys on a maize field with a terrestrial laser scanner are shown. The achieved point clouds are interpolated to generate Crop Surface Models (CSM) that represent the top canopy. These CSMs are used for visualizing the spatial distribution of plant height differences within the field and calculating plant height above ground with a high resolution of 1 cm. In addition, manual measurements of plant height were carried out corresponding to each TLS campaign to verify the results. The high coefficient of determination (R² = 0.93) between both measurement methods shows the applicability of the presented approach. The established regression model between CSM-derived plant height and destructively measured biomass shows a varying performance depending on the considered time frame during the growing period. This study shows that TLS is a suitable and promising method for measuring plant height of maize. Moreover, it shows the potential of plant height as a non-destructive estimator for biomass in the early growing period. However, challenges are the non-linear development of plant height and biomass over the whole growing period.

Comparison of linear and mixed-effect regression models and a k-nearest neighbour approach for estimation of single-tree biomass

2008 ◽  
Vol 38 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Lutz Fehrmann ◽  
Aleksi Lehtonen ◽  
Christoph Kleinn ◽  
Erkki Tomppo
Keyword(s):  
Mixed Models ◽  
Regression Models ◽  
Tree Height ◽  
Biomass Estimation ◽  
Data Sets ◽  
Tree Biomass ◽  
Mixed Effect ◽  
Single Tree ◽  
Breast Height ◽  
Effect Regression

Allometric biomass models for individual trees are typically specific to site conditions and species. They are often based on a low number of easily measured independent variables, such as diameter in breast height and tree height. A prevalence of small data sets and few study sites limit their application domain. One challenge in the context of the actual climate change discussion is to find more general approaches for reliable biomass estimation. Therefore, nonparametric approaches can be seen as an alternative to commonly used regression models. In this pilot study, we compare a nonparametric instance-based k-nearest neighbour (k-NN) approach to estimate single-tree biomass with predictions from linear mixed-effect regression models and subsidiary linear models using data sets of Norway spruce ( Picea abies (L.) Karst.) and Scots pine ( Pinus sylvestris L.) from the National Forest Inventory of Finland. For all trees, the predictor variables diameter at breast height and tree height are known. The data sets were split randomly into a modelling and a test subset for each species. The test subsets were not considered for the estimation of regression coefficients nor as training data for the k-NN imputation. The relative root mean square errors of linear mixed models and k-NN estimations are slightly lower than those of an ordinary least squares regression model. Relative prediction errors of the k-NN approach are 16.4% for spruce and 14.5% for pine. Errors of the linear mixed models are 17.4% for spruce and 15.0% for pine. Our results show that nonparametric methods are suitable in the context of single-tree biomass estimation.

Individual tree biomass estimation equations for plantation-grown white spruce in northern Minnesota

1985 ◽  
Vol 15 (4) ◽  
pp. 738-739 ◽  
Author(s):  
R. B. Harding ◽  
D. F. Grigal
Keyword(s):  
Stand Structure ◽  
White Spruce ◽  
Biomass Estimation ◽  
Prediction Equations ◽  
Tree Biomass ◽  
Eastern Canada ◽  
Individual Tree ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
Estimation Equations

Prediction equations for biomass of white spruce (Piceaglauca (Moench) Voss) were developed for 115 sample trees using the allometric models Y = ADB and Y = ADBHC, where Y is mass, D is diameter at breast height, and H is total height. The addition of height to the model reduced the Sy•x for all estimates except that for biomass of branches and needles. Comparison of results to other estimation equations developed in eastern Canada showed that biomass estimates were variable. Variations in stand structure and age between natural and plantation-grown trees are possible reasons for these differences.

scholarly journals Estimation of Genetic Parameters and Wood Yield Selection Index in a Clonal Trial of Korean Pine (Pinus koraiensis) in Northeastern China

2021 ◽  
Vol 13 (8) ◽  
pp. 4167
Author(s):  
David Kombi Kaviriri ◽  
Huan-Zhen Liu ◽  
Xi-Yang Zhao
Keyword(s):  
Selection Index ◽  
Tree Height ◽  
Stem Volume ◽  
Korean Pine ◽  
Branch Number ◽  
Basal Diameter ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
Stem Straightness ◽  
Clonal Trial

In order to determine suitable traits for selecting high-wood-yield Korean pine materials, eleven morphological characteristics (tree height, basal diameter, diameter at breast height, diameter at 3 meter height, stem straightness degree, crown breadth, crown height, branch angle, branch number per node, bark thickness, and stem volume) were investigated in a 38-year-old Korean pine clonal trial at Naozhi orchard. A statistical approach combining variance and regression analysis was used to extract appropriate traits for selecting elite clones. Results of variance analysis showed significant difference in variance sources in most of the traits, except for the stem straightness degree, which had a p-value of 0.94. Moderate to high coefficients of variation and clonal repeatability ranged from 10.73% to 35.45% and from 0.06% to 0.78%, respectively. Strong significant correlations on the phenotypic and genotypic levels were observed between the straightness traits and tree volume, but crown breadth was weakly correlated to the volume. Four principal components retaining up to 80% of the total variation were extracted, and stem volume, basal diameter, diameter at breast height, diameter at 3 meter height, tree height, and crown height displayed high correlation to these components (r ranged from 0.76 to 0.98). Based on the Type III sum of squares, tree height, diameter at breast height, and branch number showed significant information to explain the clonal variability based on stem volume. Using the extracted characteristics as the selection index, six clones (PK105, PK59, PK104, PK36, PK28, and K101) displayed the highest Qi values, with a selection rate of 5% corresponding to the genetic gain of 42.96% in stem volume. This study provides beneficial information for the selection of multiple traits for genetically improved genotypes of Korean pine.

scholarly journals Rapid Evaluation and Validation Method of Above Ground Forest Biomass Estimation Using Optical Remote Sensing in Tundi Reserved Forest Area, India

2021 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Praveen Kumar ◽  
Akhouri P. Krishna ◽  
Thorkild M. Rasmussen ◽  
Mahendra K. Pal
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Test Site ◽  
Forest Area ◽  
Relational Model ◽  
Biomass Estimation ◽  
Optical Remote Sensing ◽  
Ground Sample ◽  
Sensing Data

Optical remote sensing data are freely available on a global scale. However, the satellite image processing and analysis for quick, accurate, and precise forest above ground biomass (AGB) evaluation are still challenging and difficult. This paper is aimed to develop a novel method for precise, accurate, and quick evaluation of the forest AGB from optical remote sensing data. Typically, the ground forest AGB was calculated using an empirical model from ground data for biophysical parameters such as tree density, height, and diameter at breast height (DBH) collected from the field at different elevation strata. The ground fraction of vegetation cover (FVC) in each ground sample location was calculated. Then, the fraction of vegetation cover (FVC) from optical remote sensing imagery was calculated. In the first stage of method implementation, the relation model between the ground FVC and ground forest AGB was developed. In the second stage, the relational model was established between image FVC and ground FVC. Finally, both models were fused to derive the relational model between image FVC and forest AGB. The validation of the developed method was demonstrated utilizing Sentinel-2 imagery as test data and the Tundi reserved forest area located in the Dhanbad district of Jharkhand state in eastern India was used as the test site. The result from the developed model was ground validated and also compared with the result from a previously developed crown projected area (CPA)-based forest AGB estimation approach. The results from the developed approach demonstrated superior capabilities in precision compared to the CPA-based method. The average forest AGB estimation of the test site obtained by this approach revealed 463 tons per hectare, which matches the previous estimate from this test site.

Using photography to estimate above-ground biomass of small trees

2020 ◽  
pp. 1-7
Author(s):  
Brandon R. Hays ◽  
Corinna Riginos ◽  
Todd M. Palmer ◽  
Benard C. Gituku ◽  
Jacob R. Goheen
Keyword(s):  
Cost Effective ◽  
Allometric Equation ◽  
Biomass Estimation ◽  
Above Ground Biomass ◽  
Tree Biomass ◽  
East African ◽  
Ground Biomass ◽  
Herbivore Exclusion ◽  
Significant Difference ◽  
Allometric Relation

Abstract Quantifying tree biomass is an important research and management goal across many disciplines. For species that exhibit predictable relationships between structural metrics (e.g. diameter, height, crown breadth) and total weight, allometric calculations produce accurate estimates of above-ground biomass. However, such methods may be insufficient where inter-individual variation is large relative to individual biomass and is itself of interest (for example, variation due to herbivory). In an East African savanna bushland, we analysed photographs of small (<5 m) trees from perpendicular angles and fixed distances to estimate above-ground biomass. Pixel area of trees in photos and diameter were more strongly related to measured, above-ground biomass of destructively sampled trees than biomass estimated using a published allometric relation based on diameter alone (R2 = 0.86 versus R2 = 0.68). When tested on trees in herbivore-exclusion plots versus unfenced (open) plots, our predictive equation based on photos confirmed higher above-ground biomass in the exclusion plots than in unfenced (open) plots (P < 0.001), in contrast to no significant difference based on the allometric equation (P = 0.43). As such, our new technique based on photographs offers an accurate and cost-effective complement to existing methods for tree biomass estimation at small scales with potential application across a wide variety of settings.

scholarly journals Effects of Photosynthetic Activity Radiation (PAR) on Green Mustard Plant Growth (Brassica rapa var. parachinensis L.)

2019 ◽  
Vol 20 (1) ◽  
pp. 19
Author(s):  
Ni Nyoman Ratini ◽  
I Wayan Supardi ◽  
Yuli Nurfadhillah
Keyword(s):  
Growth Rate ◽  
Light Intensity ◽  
Plant Height ◽  
Photosynthetic Activity ◽  
Plant Biomass ◽  
Vegetative Phase ◽  
Active Radiation ◽  
Blue Filter ◽  
Mustard Plant ◽  
Number Of Leaves

A research on the effect of photosynthetic active radiation (PAR) on the growth of green mustard plants has been conducted. The radiation source used is sunlight. Samples have been grouped as a sample which treated by red filter (P1), by orange filter (P2), by purple filter (P3), by green filter (P4), by blue filter (P5) and a sample without filter as a control (P0). Each sample consisted of four plants. The planting was carried out using polybags with compost media. Observations were made from the nursery phase to the slow vegetative phase (day 3rd, when all plants had grown shoots until day 63rd of the harvest). Parameters measured include light intensity, plant height and number of leaves. Measurement is done every three days. Also it measured plant biomass on the last day of observation (63rd day). The results showed that the intensity of each sample had an impact on the harvest. The best growth rate is obtained in P2, both in the nursery phase and fast vegetative phase i.e. 0.119 cm/day and 0.194 cm/day, respectively. While the highest growth rate was obtained in the P3 sample, namely the slow vegetative phase (0.035 cm/day). Overall the best planting results were obtained in P2 samples with plant height of 23.18 cm, number of leaves of 12 strands and plant biomass of 33.56 g.

scholarly journals Contribution of some Acacia Species on Carbon Sequestration in Blue Nile State, Sudan

2021 ◽  
pp. 97-105
Keyword(s):  
Carbon Sequestration ◽  
Wood Density ◽  
Carbon Stock ◽  
Tree Height ◽  
Biomass Estimation ◽  
Expansion Factor ◽  
Wood Volume ◽  
Crown Diameter ◽  
Breast Height ◽  
Acacia Seyal

Background: The current challenge is to reduce the uncertainties in obtaining accurate and reliable data of carbon stock changes and emission factors essential for reporting national inventories. Improvements in above ground biomass estimation can also help account for changes in carbon stock in forest areas that may potentially participate in the Reducing emissions from deforestation and forest degradation and other initiatives. Current objectives for such estimates need a unified approach which can be measurable, reportable, and verifiable. This might result to a geographically referenced biomass density database for Sudanese forests that would reduce uncertainties in estimating forest aboveground biomass. The main objective: of this study is to assess potential of some selected forest variables for modeling carbon sequestration for Acacia seyal, vr. Seyal, Acacia seyal, vr. fistula, Acacia Senegal. The specific objectives include development of empirical allometric models for forest biomass estimation, estimation of carbon sequestration for these tree species, estimation of carbon sequestration per hectare and comparing the amount with that reported to the region. A total of 10 sample trees for biomass and carbon determination were selected for each of the three species from El Nour Natural Forest Reserve of the Blue Nile State, Sudan. Data of diameter at breast height, total tree height, tree crown diameter, crown height, and upper stem diameters were measured. Then sample trees were felled and sectioned to their components, and weighed. Subsamples were selected from each component for oven drying at 105 ˚C. Finally allometric models were developed and the aboveground dry weight (dwt) and carbon sequestered per hector were calculated. The results: presents biomass equations, biomass expansion factor and wood density that developed for the trees. In case of inventoried wood volume, corrections for biomass expansion factor and wood density value were done, and new values are suggested for use to convert wood volume to biomass estimates. The results also, indicate that diameter at breast height, crown diameter and tree height are good predictors for estimation of tree dwt and carbon stock. Conclusion: The developed allometric equations in this study gave better estimation of dwt than default value. The average carbon stock was found to be 22.57 t/ha.

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