Tree height and tropical forest biomass estimation

Abstract. Tropical forests account for approximately half of above-ground carbon stored in global vegetation. However, uncertainties in tropical forest carbon stocks remain high because it is costly and laborious to quantify standing carbon stocks. Carbon stocks of tropical forests are determined using allometric relations between tree stem diameter and height and biomass. Previous work has shown that the inclusion of height in biomass allometries, compared to the sole use of diameter, significantly improves biomass estimation accuracy. Here, we evaluate the effect of height measurement error on biomass estimation and we evaluate the accuracy of recently published diameter : height allometries at four sites within the Brazilian Amazon. As no destructive sample of biomass was available at these sites, reference biomass values were based on allometries. We found that the precision of individual tree height measurements ranged from 3 to 20% of total height. This imprecision resulted in a 5–6% uncertainty in biomass when scaled to 1 ha transects. Individual height measurement may be replaced with existing regional and global height allometries. However, we recommend caution when applying these relations. At Tapajós National Forest in the Brazilian state of Pará, using the pantropical and regional allometric relations for height resulted in site biomass 26% to 31% less than reference values. At the other three study sites, the pan-tropical equation resulted in errors of less that 2%, and the regional allometry produced errors of less than 12%. As an alternative to measuring all tree heights or to using regional and pantropical relations, we recommend measuring height for a well distributed sample of about 100 trees per site. Following this methodology, 95% confidence intervals of transect biomass were constrained to within 4.5% on average when compared to reference values.

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Tree height and tropical forest biomass estimation

Biogeosciences ◽

10.5194/bg-10-8385-2013 ◽

2013 ◽

Vol 10 (12) ◽

pp. 8385-8399 ◽

Cited By ~ 103

Author(s):

M. O. Hunter ◽

M. Keller ◽

D. Victoria ◽

D. C. Morton

Keyword(s):

Tropical Forest ◽

Tropical Forests ◽

Reference Values ◽

Tree Height ◽

Carbon Stocks ◽

Estimation Accuracy ◽

Biomass Estimation ◽

Height Measurement ◽

Individual Tree ◽

Allometric Relations

Abstract. Tropical forests account for approximately half of above-ground carbon stored in global vegetation. However, uncertainties in tropical forest carbon stocks remain high because it is costly and laborious to quantify standing carbon stocks. Carbon stocks of tropical forests are determined using allometric relations between tree stem diameter and height and biomass. Previous work has shown that the inclusion of height in biomass allometries, compared to the sole use of diameter, significantly improves biomass estimation accuracy. Here, we evaluate the effect of height measurement error on biomass estimation and we evaluate the accuracy of recently published diameter–height allometries at four areas within the Brazilian Amazon. As no destructive sample of biomass was available at these sites, reference biomass values were based on allometries. We found that the precision of individual tree height measurements ranged from 3 to 20% of total height. This imprecision resulted in a 5–6% uncertainty in biomass when scaled to 1 ha transects. Individual height measurement may be replaced with existing regional and global height allometries. However, we recommend caution when applying these relations. At Tapajos National Forest in the Brazilian state of Pará, using the pantropical and regional allometric relations for height resulted in site biomass 21% and 25% less than reference values. At the other three study sites, the pantropical equation resulted in errors of less that 2%, and the regional allometry produced errors of less than 12%. As an alternative to measuring all tree heights or to using regional and pantropical relations, we recommend measuring height for a well-distributed sample of about 100 trees per site. Following this methodology, 95% confidence intervals of transect biomass were constrained to within 4.5% on average when compared to reference values.

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Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Biogeosciences ◽

10.5194/bg-13-1571-2016 ◽

2016 ◽

Vol 13 (5) ◽

pp. 1571-1585 ◽

Cited By ~ 36

Author(s):

Pierre Ploton ◽

Nicolas Barbier ◽

Stéphane Takoudjou Momo ◽

Maxime Réjou-Méchain ◽

Faustin Boyemba Bosela ◽

...

Keyword(s):

Tropical Forest ◽

Reference Model ◽

Original Data ◽

Carbon Stocks ◽

Forest Carbon ◽

Biomass Estimation ◽

Systematic Bias ◽

Data Set ◽

Allometric Models ◽

Large Trees

Abstract. Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees ≥  45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

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Closing a gap in tropical forest biomass estimation: accounting for crown mass variation in pantropical allometries

Biogeosciences Discussions ◽

10.5194/bgd-12-19711-2015 ◽

2015 ◽

Vol 12 (23) ◽

pp. 19711-19750 ◽

Cited By ~ 5

Author(s):

P. Ploton ◽

N. Barbier ◽

S. T. Momo ◽

M. Réjou-Méchain ◽

F. Boyemba Bosela ◽

...

Keyword(s):

Tropical Forest ◽

Reference Model ◽

Central Africa ◽

Carbon Stocks ◽

Forest Carbon ◽

Biomass Estimation ◽

Systematic Bias ◽

Allometric Models ◽

Original Dataset ◽

Large Trees

Abstract. Accurately monitoring tropical forest carbon stocks is an outstanding challenge. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference in the coming years. However, this reference model shows a systematic bias for the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass dataset on 673 trees measured in five tropical countries (101 trees > 100 cm in diameter) and an original dataset of 130 forest plots (1 ha) from central Africa to quantify the error of biomass allometric models at the individual and plot levels when explicitly accounting or not accounting for crown mass variations. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees ≥ 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Accounting for a crown mass proxy in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error from −23–16 to 0–10 %. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by accounting for a crown mass proxy for the largest trees in a stand, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

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Deriving Individual-Tree Biomass from Effective Crown Data Generated by Terrestrial Laser Scanning

Remote Sensing ◽

10.3390/rs11232793 ◽

2019 ◽

Vol 11 (23) ◽

pp. 2793

Author(s):

Yujie Zheng ◽

Weiwei Jia ◽

Qiang Wang ◽

Xu Huang

Keyword(s):

Laser Scanning ◽

Three Dimensional ◽

Terrestrial Laser Scanning ◽

Tree Height ◽

Biomass Estimation ◽

Tree Biomass ◽

Crown Height ◽

Individual Tree ◽

Cloud Data ◽

Biomass Equations

Biomass reflects the state of forest management and is critical for assessing forest benefits and carbon storage. The effective crown is the region above the lower limit of the forest crown that includes the maximum vertical distribution density of branches and leaves; this component plays an important role in tree growth. Adding the effective crown to biomass equations can enhance the accuracy of the derived biomass. Six sample plots in a larch plantation (ranging in area from 0.06 ha to 0.12 ha and in number of trees from 63 to 96) at the Mengjiagang forest farm in Huanan County, Jiamusi City, Heilongjiang Province, China, were analyzed in this study. Terrestrial laser scanning (TLS) was used to obtain three-dimensional point cloud data on the trees, from which crown parameters at different heights were extracted. These parameters were used to determine the position of the effective crown. Moreover, effective crown parameters were added to biomass equations with tree height as the sole variable to improve the accuracy of the derived individual-tree biomass estimates. The results showed that the minimum crown contact height was very similar to the effective crown height, and an increase in model accuracy was apparent (with R a 2 increasing from 0.846 to 0.910 and root-mean-square error (RMSE) decreasing from 0.372 kg to 0.286 kg). The optimal model for deriving biomass included tree height, crown length from minimum contact height, crown height from minimum contact height, and crown surface area from minimum contact height. The novelty of the article is that it improves the fit of individual-tree biomass models by adding crown-related variables and investigates how the accuracy of biomass estimation can be enhanced by using remote sensing methods without obtaining diameter at breast height.

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Biomass and total carbon in oak forests of Southern Colombian Andes: contributions to the REDD+ project-wide approach.

Revista de Biología Tropical ◽

10.15517/rbt.v64i1.18221 ◽

2016 ◽

Vol 64 (1) ◽

pp. 399

Author(s):

Adriana Yepes ◽

Andrés Sierra ◽

Luz Milena Niño ◽

Manuel López ◽

César Garay ◽

...

Keyword(s):

Tropical Forests ◽

Aboveground Biomass ◽

Belowground Biomass ◽

Carbon Stocks ◽

Total Carbon ◽

Biomass Estimation ◽

Natural Forests ◽

Colombian Andes ◽

Greenhouse Emission

Carbon estimations in tropical forests are very important to understand the role of these ecosystems in the carbon cycle, and to support decisions and the formulation of mitigation and adaptive strategies to reduce the greenhouse emission gases (GHG). Nevertheless, detailed ground-based quantifications of total carbon stocks in tropical montane forests are limited, despite their high value in science and ecosystem management (e.g. REDD+). The objective was to identify the role of these ecosystems as carbon stocks, to evaluate the contribution of the pools analyzed (aboveground biomass, belowground biomass and necromass), and to make contributions to the REDD+ approach from the project scale. For this study, we established 44 plots in a heterogeneous landscape composed by old-grown forests located in the Southern Colombian Andes. In each plot, all trees, palms and ferns with diameter (D) ≥ 15 cm were measured. In the case of palms, the height was measured for 40 % of the individuals, following the Colombia National Protocol to estimate biomass and carbon in natural forests. National allometric equations were used to estimate aboveground biomass, and a global equation proposed by IPCC was used for belowground biomass estimation; besides, palms’ aboveground biomass was estimated using a local model. The necromass was estimated for dead standing trees and the gross debris. In the latter case, the length and diameters of the extremes in the pieces were measured. Samples for wood density estimations were collected in the field and analyzed in the laboratory. The mean total carbon stock was estimated as 545.9 ± 84.1 Mg/ha (± S.E.). The aboveground biomass contributed with 72.5 %, the belowground biomass with 13.6 %, and the necromass with 13.9 %. The main conclusion is that montane tropical forests store a huge amount of carbon, similar to low land tropical forests. In addition, the study found that the inclusion of other pools could contribute with more than 20 % to total carbon storage, indicating that estimates that only include the aboveground biomass, largely underestimate carbon stocks in tropical forest ecosystems. These results support the importance of including other carbon pools in REDD+ initiatives’ estimations.

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UAV-Based LiDAR Scanning for Individual Tree Detection and Height Measurement in Young Forest Permanent Trials

Remote Sensing ◽

10.3390/rs14010170 ◽

2021 ◽

Vol 14 (1) ◽

pp. 170

Author(s):

Francisco Rodríguez-Puerta ◽

Esteban Gómez-García ◽

Saray Martín-García ◽

Fernando Pérez-Rodríguez ◽

Eva Prada

Keyword(s):

Pinus Radiata ◽

Repeated Measures ◽

Pinus Pinaster ◽

Tree Height ◽

Cost Effective ◽

Permanent Plots ◽

Height Measurement ◽

Measured Variable ◽

Individual Tree ◽

Tree Detection

The installation of research or permanent plots is a very common task in growth and forest yield research. At young ages, tree height is the most commonly measured variable, so the location of individuals is necessary when repeated measures are taken and if spatial analysis is required. Identifying the coordinates of individual trees and re-measuring the height of all trees is difficult and particularly costly (in time and money). The data used comes from three Pinus pinaster Ait. and three Pinus radiata D. Don plantations of 0.8 ha, with an age ranging between 2 and 5 years and mean heights between 1 and 5 m. Five individual tree detection (ITD) methods are evaluated, based on the Canopy Height Model (CHM), where the height of each tree is identified, and its crown is segmented. Three CHM resolutions are used for each method. All algorithms used for individual tree detection (ITD) tend to underestimate the number of trees. The best results are obtained with the R package, ForestTools and rLiDAR. The best CHM resolution for identifying trees was always 10 cm. We did not detect any differences in the relative error (RE) between Pinus pinaster and Pinus radiata. We found a pattern in the ITD depending on the height of the trees to be detected: the accuracy is lower when detecting trees less than 1 m high than when detecting larger trees (RE close to 12% versus 1% for taller trees). Regarding the estimation of tree height, we can conclude that the use of the CHM to estimate height tends to underestimate its value, while the use of the point cloud presents practically unbiased results. The stakeout of forestry research plots and the re-measurement of individual tree heights is an operation that can be performed by UAV-based LiDAR scanning sensors. The individual geolocation of each tree and the measurement of heights versus pole and/or hypsometer measurement is highly accurate and cost-effective, especially when tree height reaches 1–1.5 m.

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Predicting tree heights for biomass estimates in tropical forests – a test from French Guiana

Biogeosciences ◽

10.5194/bg-11-3121-2014 ◽

2014 ◽

Vol 11 (12) ◽

pp. 3121-3130 ◽

Cited By ~ 27

Author(s):

Q. Molto ◽

B. Hérault ◽

J.-J. Boreux ◽

M. Daullet ◽

A. Rousteau ◽

...

Keyword(s):

Tropical Forests ◽

Forest Structure ◽

French Guiana ◽

Tree Height ◽

Biomass Estimation ◽

Forest Plot ◽

Model Parameters ◽

Forest Stands ◽

Forest Stand Structure ◽

Height Model

Abstract. The recent development of REDD+ mechanisms requires reliable estimation of carbon stocks, especially in tropical forests that are particularly threatened by global changes. Even though tree height is a crucial variable for computing aboveground forest biomass (AGB), it is rarely measured in large-scale forest censuses because it requires extra effort. Therefore, tree height has to be predicted with height models. The height and diameter of all trees over 10 cm in diameter were measured in 33 half-hectare plots and 9 one-hectare plots throughout northern French Guiana, an area with substantial climate and environmental gradients. We compared four different model shapes and found that the Michaelis–Menten shape was most appropriate for the tree biomass prediction. Model parameter values were significantly different from one forest plot to another, and this leads to large errors in biomass estimates. Variables from the forest stand structure explained a sufficient part of plot-to-plot variations of the height model parameters to improve the quality of the AGB predictions. In the forest stands dominated by small trees, the trees were found to have rapid height growth for small diameters. In forest stands dominated by larger trees, the trees were found to have the greatest heights for large diameters. The aboveground biomass estimation uncertainty of the forest plots was reduced by the use of the forest structure-based height model. It demonstrated the feasibility and the importance of height modeling in tropical forests for carbon mapping. When the tree heights are not measured in an inventory, they can be predicted with a height–diameter model and incorporating forest structure descriptors may improve the predictions.

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Automatic Delineation and Height Measurement of Regenerating Conifer Crowns under Leaf-Off Conditions Using UAV Imagery

Remote Sensing ◽

10.3390/rs12244104 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4104

Author(s):

Andrew J. Chadwick ◽

Tristan R. H. Goodbody ◽

Nicholas C. Coops ◽

Anne Hervieux ◽

Christopher W. Bater ◽

...

Keyword(s):

Spatial Resolution ◽

Picea Glauca ◽

Pinus Contorta ◽

Tree Height ◽

Point Clouds ◽

Strongly Correlated ◽

Tree Crown ◽

Height Measurement ◽

Individual Tree ◽

Fine Spatial Resolution

The increasing use of unmanned aerial vehicles (UAV) and high spatial resolution imagery from associated sensors necessitates the continued advancement of efficient means of image processing to ensure these tools are utilized effectively. This is exemplified in the field of forest management, where the extraction of individual tree crown information stands to benefit operational budgets. We explored training a region-based convolutional neural network (Mask R-CNN) to automatically delineate individual tree crown (ITC) polygons in regenerating forests (14 years after harvest) using true colour red-green-blue (RGB) imagery with an average ground sampling distance (GSD) of 3 cm. We predicted ITC polygons to extract height information using canopy height models generated from digital aerial photogrammetric (DAP) point clouds. Our approach yielded an average precision of 0.98, an average recall of 0.85, and an average F1 score of 0.91 for the delineation of ITC. Remote height measurements were strongly correlated with field height measurements (r2 = 0.93, RMSE = 0.34 m). The mean difference between DAP-derived and field-collected height measurements was −0.37 m and −0.24 m for white spruce (Picea glauca) and lodgepole pine (Pinus contorta), respectively. Our results show that accurate ITC delineation in young, regenerating stands is possible with fine-spatial resolution RGB imagery and that predicted ITC can be used in combination with DAP to estimate tree height.

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Field methods for sampling tree height for tropical forest biomass estimation

Methods in Ecology and Evolution ◽

10.1111/2041-210x.12962 ◽

2018 ◽

Vol 9 (5) ◽

pp. 1179-1189 ◽

Cited By ~ 37

Author(s):

Martin J. P. Sullivan ◽

Simon L. Lewis ◽

Wannes Hubau ◽

Lan Qie ◽

Timothy R. Baker ◽

...

Keyword(s):

Tropical Forest ◽

Forest Biomass ◽

Tree Height ◽

Biomass Estimation ◽

Field Methods

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Understanding the importance of primary tropical forest protection as a mitigation strategy

Mitigation and Adaptation Strategies for Global Change ◽

10.1007/s11027-019-09891-4 ◽

2020 ◽

Vol 25 (5) ◽

pp. 763-787 ◽

Cited By ~ 8

Author(s):

Brendan Mackey ◽

Cyril F. Kormos ◽

Heather Keith ◽

William R. Moomaw ◽

Richard A. Houghton ◽

...

Keyword(s):

Global Warming ◽

Tropical Forest ◽

Tropical Forests ◽

Carbon Dioxide Emissions ◽

Carbon Stocks ◽

Mitigation Strategies ◽

Primary Forest ◽

Published Data ◽

Forest Protection ◽

Ecosystem Carbon

Abstract Given the short time-frame to limit global warming, and the current emissions gap, it is critical to prioritise mitigation actions. To date, scant attention has been paid to the mitigation benefits of primary forest protection. We estimated tropical forest ecosystem carbon stocks and flows. The ecosystem carbon stock of primary tropical forests is estimated at 141–159 Pg C (billion tonnes of carbon) which is some 49–53% of all tropical forest carbon, the living biomass component of which alone is 91–103% of the remaining carbon budget to limit global warming to below 1.5 degrees above pre-industrial levels. Furthermore, tropical forests have ongoing sequestration rates 0.47–1.3 Pg C yr−1, equivalent to 8–13% of annual global anthropogenic CO2 (carbon dioxide) emissions. We examined three main forest-based strategies used in the land sector—halting deforestation, increasing forest restoration and improving the sustainable management of production forests. The mitigation benefits of primary forest protection are contingent upon how degradation is defined and accounted for, while those from restoration also depend on how restoration is understood and applied. Through proforestation, reduced carbon stocks in secondary forests can regrow to their natural carbon carrying capacity or primary forest state. We evaluated published data from studies comparing logged and unlogged forests. On average, primary forests store around 35% more carbon. While comparisons are confounded by a range of factors, reported biomass carbon recovery rates were from 40 to 100+ years. There is a substantive portfolio of forest-based mitigation actions and interventions available to policy and decision-makers, depending on national circumstances, in addition to SFM and plantation focused approaches, that can be grouped into four main strategies: protection; proforestation, reforestation and restoration; reform of guidelines, accounting rules and default values; landscape conservation planning. Given the emissions gap, mitigation strategies that merely reduce the rate of emissions against historic or projected reference levels are insufficient. Mitigation strategies are needed that explicitly avoid emissions where possible as well as enabling ongoing sequestration.

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