Assessment of temporal changes in aboveground forest tree biomass using aerial photographs and allometric equations

Studies of forest biomass dynamics typically use long-term forest inventory data, available in only a few places around the world. We present a method that uses photogrammetric measurements from aerial photographs as an alternative to time-series field measurements. We used photogrammetric methods to measure tree height and crown diameter, using four aerial photographs of Yatir Forest, a semi-arid forest in southern Israel, taken between 1978 and 2003. Height and crown-diameter measurements were transformed to biomass using an allometric equation generated from 28 harvested Aleppo pine (Pinus halepensis Mill.) trees. Mean tree biomass increased from 6.37 kg in 1978 to 97.01 kg in 2003. Mean plot biomass in 2003 was 2.48 kg/m2 and aboveground primary productivity over the study period ranged between 0.14 and 0.21 kg/m2 per year. There was systematic overestimation of tree height and systematic underestimation of crown diameter, which was corrected for at all time points between 1978 and 2003. The estimated biomass was significantly related to field-measured biomass, with an R2 value of 0.78. This method may serve as an alternative to field sampling for studies of forest biomass dynamics, assuming that there is sufficient spatial and temporal coverage of the investigated area using high-quality aerial photography, and that the tree tops are distinguishable in the photographs.

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Tree height integrated into pantropical forest biomass estimates

Biogeosciences ◽

10.5194/bg-9-3381-2012 ◽

2012 ◽

Vol 9 (8) ◽

pp. 3381-3403 ◽

Cited By ~ 239

Author(s):

T. R. Feldpausch ◽

J. Lloyd ◽

S. L. Lewis ◽

R. J. W. Brienen ◽

M. Gloor ◽

...

Keyword(s):

East Africa ◽

Carbon Storage ◽

Stand Structure ◽

Forest Biomass ◽

Small Diameter ◽

Tree Height ◽

Total Biomass ◽

Guiana Shield ◽

Tree Biomass ◽

Continental Scale

Abstract. Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

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Removing the Scaling Error Caused by Allometric Modelling in Forest Biomass Estimation at Large Scales

Forests ◽

10.3390/f10070602 ◽

2019 ◽

Vol 10 (7) ◽

pp. 602

Author(s):

Carl Zhou ◽

Xiaolu Zhou

Keyword(s):

Large Scale ◽

Forest Ecosystems ◽

Forest Biomass ◽

Field Measurements ◽

Allometric Equation ◽

Biomass Estimation ◽

Allometric Relationships ◽

Data Errors ◽

Pinus Yunnanensis

To estimate the responses of forest ecosystems, most relationships in biological systems are described by allometric relationships, the parameters of which are determined based on field measurements. The use of existing observed data errors may occur during the scaling of fine-scale relationships to describe ecosystem properties at a larger ecosystem scale. Here, we analyzed the scaling error in the estimation of forest ecosystem biomass based on the measurement of plots (biomass or volume per hectare) using an improved allometric equation with a scaling error compensator. The efficiency of the compensator on reducing the scaling error was tested by simulating the forest stand populations using pseudo-observation. Our experiments indicate that, on average, approximately 94.8% of the scaling error can be reduced, and for a case study, an overestimation of 3.6% can be removed in practice from a large-scale estimation for the biomass of Pinus yunnanensis Franch.

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DERIVATION OF FOREST INVENTORY PARAMETERS FOR CARBON ESTIMATION USING TERRESTRIAL LIDAR

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b8-677-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 677-684

Author(s):

Om Prakash Prasad Kalwar ◽

Yousif A. Hussin ◽

Michael J. C. Weir ◽

Yogendra K. Karna

Keyword(s):

Forest Inventory ◽

Point Cloud ◽

Tree Height ◽

Field Measurements ◽

Allometric Equation ◽

Carbon Stocks ◽

Above Ground Biomass ◽

Terrestrial Lidar ◽

Average Value ◽

Tree Inventory

This research was conducted to derive forest sample plot inventory parameters from terrestrial LiDAR (T-LiDAR) for estimating above ground biomass (AGB)/carbon stocks in primary tropical rain forest. Inventory parameters of all sampled trees within circular plots of 500 m2 were collected from field observations while T-LiDAR data were acquired through multiple scanning using Reigl VZ-400 scanner. Pre-processing and registration of multiple scans were done in RSCAN PRO software. Point cloud constructing individual sampled tree was extracted and tree inventory parameters (diameter at breast height-DBH and tree height) were measured manually. AGB/carbon stocks were estimated using Chave et al., (2005) allometric equation. An average 80 % of sampled trees were detected from point cloud of the plots. The average of plots values of R2 and RMSE for manually measured DBHs were 0.95, 2.7 cm respectively. Similarly, the average of plots values of R2 and RMSE for manually measured trees heights were 0.77, 2.96 m respectively. The average value of AGB/carbon stocks estimated from field measurements and T-LiDAR manually derived DBHs and trees heights were 286 Mg ha-1 and 134 Mg ha−1; and 278 M ha-1 and 130 Mg ha−1 respectively. The R2 values for the estimated AGB and AGC were both 0.93 and corresponding RMSE values were 42.4 Mg ha−1 and 19.9 Mg  ha−1 respectively. AGB and AGC were estimated with 14.8 % accuracy.

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UAV-Based Canopy Height Modeling under Leaf-on and Leaf-off Conditions for Determining Tree Height and Crown Diameter (Case study: Hyrcanian mixed Forest)

Canadian Journal of Forest Research ◽

10.1139/cjfr-2020-0125 ◽

2021 ◽

Author(s):

Vahid Nasiri ◽

Ali.A. Darvishsefat ◽

Hossein Arefi ◽

Marc Pierrot-Deseilligny ◽

Manochehr Namiranian ◽

...

Keyword(s):

Mixed Forest ◽

Digital Terrain Model ◽

Local Maximum ◽

Tree Height ◽

Field Measurements ◽

Canopy Height ◽

Aerial Images ◽

Surface Model ◽

Individual Tree ◽

Crown Diameter

Tree height and crown diameter are two common individual tree attributes that can be estimated from Unmanned Aerial Vehicles (UAVs) images thanks to photogrammetry and structure from motion. This research investigates the potential of low-cost UAV aerial images to estimate tree height and crown diameter. Two successful flights were carried out in two different seasons corresponding to leaf-off and leaf-on conditions to generate Digital Terrain Model (DTM) and Digital Surface Model (DSM), which were further employed in calculation of a Canopy Height Model (CHM). The CHM was used to estimate tree height using low pass and local maximum filters, and crown diameter was estimated based on an Invert Watershed Segmentation (IWS) algorithm. UAV-based tree height and crown diameter estimates were validated against field measurements and resulted in 3.22 m (10.1%) and 0.81 m (7.02%) RMSE, respectively. The results showed high agreement between our estimates and field measurements, with R2=0.808 for tree height and R2=0.923 for crown diameter. Generally, the accuracy of the results was considered acceptable and confirmed the usefulness of this approach for estimating tree heights and crown diameter.

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Estimating ovendry mass of trembling aspen and white birch using measurements from aerial photographs

Canadian Journal of Forest Research ◽

10.1139/x86-030 ◽

1986 ◽

Vol 16 (1) ◽

pp. 163-165 ◽

Cited By ~ 4

Author(s):

I. S. Alemdag

Keyword(s):

Pilot Study ◽

Large Scale ◽

Tree Height ◽

Aerial Photographs ◽

Tree Biomass ◽

White Birch ◽

Crown Area ◽

Preliminary Results ◽

Total Tree ◽

Whole Tree

A pilot study tested the estimation of stem, crown, and whole-tree biomass of single trees from measurements of total tree height and crown area taken from large-scale aerial photographs. The results indicated the feasibility of this method, provided that time of photography is optimal. More extensive testing is required to confirm these encouraging preliminary results.

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Evaluation of a soft-copy photogrammetry system for tree-plot measurements

Canadian Journal of Forest Research ◽

10.1139/x93-225 ◽

1993 ◽

Vol 23 (9) ◽

pp. 1781-1785 ◽

Cited By ~ 8

Author(s):

P.A. Gagnon ◽

J.P. Agnard ◽

C. Nolette

Keyword(s):

Global Positioning System ◽

Large Scale ◽

Tree Height ◽

Aerial Photographs ◽

Positioning System ◽

Crown Diameter ◽

Forest Inventories ◽

Global Positioning ◽

Soft Copy

This article describes and evaluates the application of a soft-copy photogrammetry system to large-scale forest inventories. A specially designed software, developed by the authors, has been investigated in terms of accuracy and general operability. Tests based on 1:1100 color aerial photographs, taken with a 10-m cross-boom system and digitized at resolutions of 300, 450, and 600 dots per inch, confirmed the expected tree-height accuracies of 48, 32, and 24 cm, respectively. This indicates that a photographic scale of 1:800 and a scanning resolution of 800 dots per inch could produce a tree-height precision of the order of 10 cm. The tests have shown that model orientation takes about 15 min; for a tree plot of 24 trees, measurements (height and crown diameter) and observations (species and condition) also take about 15 min. As the important problem of positioning a helicopter over a tree plot has now been solved using global positioning system receivers, the results and information presented in this paper indicate that the existing technology can provide a rigorous and operational photogrammetric system for large-scale forest inventories and regeneration monitoring.

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Assessing tree crown volume—a review

Forestry An International Journal of Forest Research ◽

10.1093/forestry/cpaa037 ◽

2020 ◽

Author(s):

Zihui Zhu ◽

Christoph Kleinn ◽

Nils Nölke

Keyword(s):

Laser Scanning ◽

Forest Biomass ◽

Field Measurements ◽

Data Sources ◽

Aerial Photographs ◽

Pollution Reduction ◽

Tree Crown ◽

Crown Volume ◽

Geometric Solids ◽

Environmental Functions

Abstract Tree crown volume is a fundamental tree characteristic. It correlates to forest biomass production and most relevant ecosystem and environmental functions, such as carbon sequestration and air pollution reduction. When researching these relationships, it is necessary to clearly define and then quantify tree crown variables in a both accurate and operational manner. In this paper, we review the reported literature on the assessment of tree crown volume. First, we compile the varying definitions of crown volume and other tree crown variables that may be used as inputs to quantify crown volume. Then, we examine the data sources for quantifying these variables, including field measurements, terrestrial photographs, aerial photographs and laser scanning. Furthermore, we compare the published approaches on translating these crown variable measurements into tree crown volume. These approaches include the approximation of simple geometric solids, approaches of computational geometry and voxelization. We also compare the reported accuracies and major challenges of these approaches. From this literature review, the reader may craft a suitable approach for the assessment of crown volume.

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Tree height integrated into pan-tropical forest biomass estimates

Biogeosciences Discussions ◽

10.5194/bgd-9-2567-2012 ◽

2012 ◽

Vol 9 (3) ◽

pp. 2567-2622 ◽

Cited By ~ 27

Author(s):

T. R. Feldpausch ◽

J. Lloyd ◽

S. L. Lewis ◽

R. J. W. Brienen ◽

E. Gloor ◽

...

Keyword(s):

Tropical Forest ◽

Stand Structure ◽

Large Diameter ◽

Forest Biomass ◽

Tree Height ◽

Total Biomass ◽

Asymptotic Model ◽

Tree Biomass ◽

Geographic Scale ◽

Continental Scale

Abstract. Above-ground tropical tree biomass and carbon storage estimates commonly ignore tree height. We estimate the effect of incorporating height (H) on forest biomass estimates using 37 625 concomitant H and diameter measurements (n = 327 plots) and 1816 harvested trees (n = 21 plots) tropics-wide to answer the following questions: 1. For trees of known biomass (from destructive harvests) which H-model form and geographic scale (plot, region, and continent) most reduces biomass estimate uncertainty? 2. How much does including H relationship estimates derived in (1) reduce uncertainty in biomass estimates across 327 plots spanning four continents? 3. What effect does the inclusion of H in biomass estimates have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of the destructively harvested trees was half (mean 0.06) when including H, compared to excluding H (mean 0.13). The power- and Weibull-H asymptotic model provided the greatest reduction in uncertainty, with the regional Weibull-H model preferred because it reduces uncertainty in smaller-diameter classes that contain the bulk of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows errors are reduced from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0) when including $H$. For all plots, above-ground live biomass was 52.2±17.3 Mg ha−1 lower when including H estimates (13%), with the greatest reductions in estimated biomass in Brazilian Shield forests and relatively no change in the Guyana Shield, central Africa and southeast Asia. We show fundamentally different stand structure across the four forested tropical continents, which affects biomass reductions due to $H$. African forests store a greater portion of total biomass in large-diameter trees and trees are on average larger in diameter. This contrasts to forests on all other continents where smaller-diameter trees contain the greatest fractions of total biomass. After accounting for variation in $H$, total biomass per hectare is greatest in Australia, the Guyana Shield, and Asia and lowest in W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if closed canopy tropical forests span 1668 million km2 and store 285 Pg C, then the overestimate is 35 Pg C if H is ignored, and the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree $H$ is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of pantropical carbon stocks and emissions due to deforestation.

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The Relationship of Diameter at Breast Height and Crown Diameter for Four Species Groups in Hardin County, Tennessee

Southern Journal of Applied Forestry ◽

10.1093/sjaf/19.4.177 ◽

1995 ◽

Vol 19 (4) ◽

pp. 177-181 ◽

Cited By ~ 21

Author(s):

Lawrence R. Gering ◽

Dennis M. May

Keyword(s):

Field Measurements ◽

Aerial Photographs ◽

Linear Regression Models ◽

Individual Tree ◽

Diameter At Breast Height ◽

Crown Diameter ◽

Breast Height ◽

Forest Experiment Station ◽

Species Groups ◽

Time Required

Abstract A set of simple linear regression models for predicting diameter at breast height (dbh) from crown diameter and a set of similar models for predicting crown diameter from dbh were developed for four species groups in Hardin County, TN. Data were obtained from 557 trees measured during the 1989 USDA Southern Forest Experiment Station survey of the forests of Tennessee, with supplemental aerial photographic observations. Estimates of individual tree crown diameter were obtained from ground measurements and from measurements made on 9 X 9 in. color aerial photographs (with nominal scale of 1:4,800) taken during the fall color season. In practice, users of aerial photographs can estimate dbh by measuring crown diameter, converting it to feet using the photo scale, and applying the appropriate equation. Similarly, crown diameter can be estimated from a ground measurement of dbh. This procedure may be useful in reducing the time required for field measurements. It may also be used to calculate crown diameters for datasets that include dbh but no direct measurement of crown attributes. South. J. Appl. For. 19(4):177-181.

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A Comparative Study to Evaluate Accuracy on Canopy Height and Density Using UAV, ALS, and Fieldwork

Forests ◽

10.3390/f11020241 ◽

2020 ◽

Vol 11 (2) ◽

pp. 241 ◽

Cited By ~ 3

Author(s):

Cheonggil Jin ◽

Che-young Oh ◽

Sanghyun Shin ◽

Nkwain Wilfred Njungwi ◽

Chuluong Choi

Keyword(s):

Forest Canopy ◽

Forest Type ◽

Canopy Cover ◽

Tree Height ◽

Field Measurements ◽

Point Clouds ◽

Aerial Photographs ◽

Measurement Unit ◽

Maximum Height ◽

Cover Density

Accurate measurement of the tree height and canopy cover density is important for forest biomass and management. Recently, Light Detection and Ranging (LIDAR) and Unmanned Aerial Vehicle (UAV) images have been used to estimate the tree height and canopy cover density for a forest stands. More so, UAV systems with autopilot functions, affordable Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) have created new possibilities, aided by available photogrammetric programs. In this study, we investigated the possibility of data collection methods using an Aerial LIDAR Scanner (ALS) and an UAV together with a fieldworks to evaluate accurate the tree standard metrics in Singyeri, Gyeongjusi, and Gyeongsangbukdo province. The derived metrics via statistical analyses of the ALS and UAV data and validated by field measurements were compared to a published forest type map (scale 1:5000) by the Korea Forest Service; geared towards improving the forest attributes. We collected data and analyzed and compared them with existent the forest type map produced from an aerial photographs and a digital stereo plotter. The ALS data of around 19.5 points·m–2 were collected by an airplane, then processed and classified using the LAStools; while about 362 images of the UAV were processed via Structure from Motion algorithm in the Agisoft Metashape Pro. Thus, we calculated the metrics using the point clouds of both an ALS and an UAV, and then verified their similarity. The fieldwork was manually done on 110 sampled trees. Calculated heights of the UAV were 3.8~5.8 m greater than those for the ALS; and when correlated with the fieldwork, the UAV data overestimated, while the maximum height of the ALS data was more accurate. For the canopy cover, the ALS computed canopy cover was 10%~30% less than that of the UAV. However, the canopy cover above 2 m by an UAV was the best measurement for a forest canopy. Therefore, these results assert that the examined techniques are robust and can significantly complement methods of the conventional data acquisition for the forest type map.

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