Tree Height Measurements Research Articles

Estimation of Genetic Parameters and Selection of Superior Genotypes in a 12-Year-Old Clonal Norway Spruce Field Trial after Phenotypic Assessment Using a UAV

Height is a key trait in the indices applied when selecting genotypes for use in both tree breeding populations and production populations in seed orchards. Thus, measurement of tree height is an important activity in the Swedish Norway spruce breeding program. However, traditional measurement techniques are time-consuming, expensive, and often involve work in bad weather, so automatization of the data acquisition would be beneficial. Possibilities for such automatization have been opened by advances in unmanned aerial vehicle (UAV) technology. Therefore, to test its applicability in breeding programs, images acquired by a consumer-level UAV (DJI Phantom 4 Pro V2.0) system were used to predict the height and breast height diameter of Norway spruce trees in a 12-year-old genetic field trial established with 2.0 × 2.0 m initial spacing. The tree heights were also measured in the field using an ultrasonic system. Three additive regression models with different numbers of predictor variables were used to estimate heights of individual trees. On stand level, the average height estimate derived from UAV data was 2% higher than the field-measured average. The estimation of family means was very accurate, but the genotype-level accuracy, which is crucial for selection in the Norway spruce breeding program, was not high enough. There was just ca. 60% matching of genotypes in groups selected using actual and estimated heights. In addition, heritability values calculated from the predicted values were underestimated and overestimated for height and diameter, respectively, with deviations from measurement-based estimates ranging between −19% and +12%. However, the use of more sophisticated UAV and camera equipment could significantly improve the results and enable automatic individual tree detection.

An accuracy analysis of mangrove tree height mensuration using forestry techniques, hypsometers and UAVs

Tree height is a fundamental measurement in forest inventory studies and a critical variable for the assessment of tree biomass, carbon stock and site productivity. However, measuring tree height is often a challenging task and may generate errors. This study provides an accuracy analysis of tree heights measured through different methods ranging from traditional techniques (thumb rule and stick method) to trigonometric equipment (clinometer, laser rangefinder, altimeter), and advanced technologies (Unmanned Aerial Vehicle or UAV and distometer). Along with scientific insights for the in situ application of these methods, the factors generating errors in tree height mensuration and its impact on forest biomass estimation were determined. Our results showed that the amount of error varies from one method to another. The amount of error was highest with the thumb rule and stick method (15%) while the range of error was similar for the clinometer (7.7%), laser rangefinder (7.1%) and altimeter (7.5%). Parameters such as tree form, the status of tree (i.e., if a tree was either isolated or within a canopy) and height of tree were found to significantly affect error generation during tree height measurements. Information on the extent to which biomass estimation is influenced by tree height errors associated with the use of different methods and instruments and the direction of error impact (overestimation or underestimation of biomass) are discussed. Finally, we recommend that the choice of method for tree heights in field inventory depends on certain factors such as cost, available time and manpower, required skills, site of observation and amount of error generated by each of the methods.

Performance of terrestrial laser scanning to characterize managed Scots pine (Pinus sylvestris L.) stands is dependent on forest structural variation

There is a limited understanding of how forest structure affects the performance of methods based on terrestrial laser scanning (TLS) in characterizing trees and forest environments. We aim to improve this understanding by studying how different forest management activities that shape tree size distributions affect the TLS-based forest characterization accuracy in managed Scots pine (Pinus sylvestris L.) stands. For that purpose, we investigated 27 sample plots consisting of three different thinning types, two thinning intensities as well as control plots without any treatments. Multi-scan TLS point clouds were collected from the sample plots, and a point cloud processing algorithm was used to segment individual trees and classify the segmented point clouds into stem and crown points. The classified point clouds were further used to estimate tree and forest structural attributes. With the TLS-based forest characterization, almost 100% completeness in tree detection, 0.7 cm (3.4%) root-mean-square-error (RMSE) in diameter-at-breast-height measurements, 0.9–1.4 m (4.5–7.3%) RMSE in tree height measurements, and <6% relative RMSE in the estimates of forest structural attributes (i.e. mean basal area, number of trees per hectare, mean volume, basal area-weighted mean diameter and height) were obtained depending on the applied thinning type. Thinnings decreased variation in horizontal and vertical forest structure, which especially favoured the TLS-based tree detection and tree height measurements, enabling reliable estimates for forest structural attributes. A considerably lower performance was recorded for the control plots. Thinning intensity was noticed to affect more on the accuracy of TLS-based forest characterization than thinning type. The number of trees per hectare and the proportion of suppressed trees were recognized as the main factors affecting the accuracy of TLS-based forest characterization. The more variation there was in the tree size distribution, the more challenging it was for the TLS-based method to capture all the trees and derive the tree and forest structural attributes. In general, consistent accuracy and reliability in the estimates of tree and forest attributes can be expected when using TLS for characterizing managed boreal forests.

Use of UAV photogrammetric data in forest genetic trials: measuring tree height, growth, and phenology in Norway spruce (Picea abies L. Karst.)

ABSTRACT Phenotyping of genetic resources that are used for development of new improved and adapted forest reproductive materials is costly. Therefore, high-throughput-phenotyping from a standard equipped unmanned aerial vehicle (UAV) with a RGB (red, green, blue) camera was used to develop a canopy height model (CHM) of a dense field trial of 15-year-old trees of Norway spruce. The site represents a typical situation of genetic testing on abandoned farm field land, where spacing between trees often are around 1-1.5 m. The CHM was used to estimate total height, intra-annual height growth and phenology of individual trees. The estimates were based on individual tree grid cells assigned according to the original planting grid. Intra-annual growth and phenology could not be estimated accurately, whereas total tree height to the uppermost whorl was accurately estimated provided that the trees were correctly identified. However, the apices of suppressed trees were often misidentified due to overhanging branches from more dominating neighboring trees. The method represents a cost and time efficient alternative to manual height measurements of the intermediate and dominating trees in closed stands. The accuracy is sufficiently high for most breeding purposes when total tree height is the target trait.

A generalized nonlinear mixed-effects height–diameter model for Norway spruce in mixed-uneven aged stands

Tree height measurements are laborious and require more time and effort compared to tree diameter measurements. That being the case, height-diameter (H-D) models are usually used to predict individual tree heights, which are necessary for estimating the tree volume and the site index, as well as for projecting the stand development over time. Using a permanent sampling network (400x400m) from Retezat National Park in Romania, twenty-one (H-D) functions were evaluated for their fit performance, sensitivity to outliers and prediction ability for Norway spruce in mixed uneven aged stands. A set of twenty-three stand variables, both spatial and non-spatial, were used to describe the stand structure, species inter-mingling and competition, in order to be used as stand predictors in a generalized H-D model. Nonlinear mixed effects model was used in modelling the H-D relationship of Norway spruce. We developed the first generalized height-diameter model in Romania using three stand predictors as measures of the stand vertical structure, density and competition. Random and fixed effects calibration techniques were compared, testing various sampling designs in order to improve the height prediction accuracy of the model on a new dataset. Measuring six trees around the median and the thickest tree gave the best result in calibrating both fixed and random effects. On average, the best calibration design increased the accuracy of the prediction by 50 cm compared to the fixed effects prediction. The use of the estimated coefficients and the calibration design will significantly decrease the amount of work done by forest management planners, while ensuring high accuracy and reducing costs.

The legacy of climate variability over the last century on populations' phenotypic variation in tree height

Phenotypic plasticity and local adaptation are the two main processes underlying trait variability. Under rapid environmental change, phenotypic plasticity, if adaptive, could increase the odds for organisms to persist. However, little is known on how environmental variation has shaped plasticity across species ranges over time. Here, we assess whether the portion of phenotypic variation of tree populations linked to the environment is related to the inter-annual climate variability of the last century and how it varies among populations across species ranges and age. To this aim, we used 372,647 individual tree height measurements of three pine species found in low elevation forests in Europe: Pinus nigra Arnold, P. pinaster Aiton and P. pinea L. Measurements were taken in a network of 38 common gardens established in Europe and North Africa with 315 populations covering the distribution range of the species. We fitted linear mixed-effect models of tree height as a function of age, population, climate and competition effects. Models allowed us to estimate tree height response curves at the population level and indexes of populations' phenotypic variation, as a proxy of phenotypic plasticity, at 4, 8 and 16 years old, and relate these indexes to the inter-annual climate variability of the last century. We found that phenotypic variation in tree height was higher in young trees than in older ones. We also found that P. pinea showed the highest phenotypic variation in tree height compared with P. pinaster and P. nigra. Finally, phenotypic variation in tree height may be partly adaptive, and differently across species, as climate variability during the last century at the origin of the populations explained between 51 and 69% of the current phenotypic variation of P. nigra and P. pinea, almost twice of the levels of P. pinaster. Main conclusionsPopulations' phenotypic variation in tree height is largely explained by the climate variability that the populations experienced during the last century, which we attribute to the genetic diversity among populations.

Potensi Biomassa Dan Karbon Tersimpan Tegakan di Ruang Terbuka Hijau Kota Polewali, Sulawesi Barat

Global warming is one of the major environmental issues of this century. Carbon dioxide (CO2) emissions are the main cause of global warming. Green open space (RTH) such as urban parks, urban forests and green lines play an important role in mitigating global warming and climate change in urban areas because it is able to reduce CO2 from the atmosphere. This study aims to determine the potential of biomass and carbon stored in the Green Open Green Space of Polewali, West Sulawesi. Data collection for stored biomass and carbon is carried out at three green space locations including; Urban forest and city park and green lane each made three plots measuring 20 m x 20 m, and three plots on the Green Line measuring 1200 m. Retrieval of data by measuring tree height and diameter, analysis to obtain the dry volume, biomass and carbon stored for each tree species contained in the Polewali green space. Biomass is obtained by the formula M = BJ x Vk x BEF, the stored carbon value is obtained from the product of biomass by 0.47. The magnitude of the relationship of volume with biomass and carbon uses a regression equation (Ŷ=a+bX). The results show there are types of Glodokan (Polyalthia longifolia), Johar (Senna siamea), Mahogany (Swetenia sp) and Trambesi (Samanea saman) which are spread in the Polewali open green space. Trambesi is a type that has dominant biomass and stored carbon of 381.95 (tons / ha) and 179.52 (ton/ha). Green lane is the type of green space that has the most stored carbon and is currently 440.94 (ton/ha) and 207.24 (ton/ha). The overall green space biomass is 571.83 (ton/ha) and stored carbon is 268.76 (ton/ha) found in urban forests, urban gardens and green belt. The relationship of volume with biomass and stored carbon shows a very strong relationship with the coefficient of determination (R2) of 0.96.

Can regional aerial images from orthophoto surveys produce high quality photogrammetric Canopy Height Model? A single tree approach in Western Europe

Forest monitoring tools are needed to promote effective and data driven forest management and forest policies. Remote sensing techniques can increase the speed and the cost-efficiency of the forest monitoring as well as large scale mapping of forest attribute (wall-to-wall approach). Digital Aerial Photogrammetry (DAP) is a common cost-effective alternative to airborne laser scanning (ALS) which can be based on aerial photos routinely acquired for general base maps. DAP based on such pre-existing dataset can be a cost effective source of large scale 3D data. In the context of forest characterization, when a quality Digital Terrain Model (DTM) is available, DAP can produce photogrammetric Canopy Height Model (pCHM) which describes the tree canopy height. While this potential seems pretty obvious, few studies have investigated the quality of regional pCHM based on aerial stereo images acquired by standard official aerial surveys. Our study proposes to evaluate the quality of pCHM individual tree height estimates based on raw images acquired following such protocol using a reference filed-measured tree height database. To further ensure the replicability of the approach, the pCHM tree height estimates benchmarking only relied on public forest inventory (FI) information and the photogrammetric protocol was based on low-cost and widely used photogrammetric software. Moreover, our study investigates the relationship between the pCHM tree height estimates based on the neighboring forest parameter provided by the FI program.Our results highlight the good agreement of tree height estimates provided by pCHM using DAP with both field measured and ALS tree height data. In terms of tree height modeling, our pCHM approach reached similar results than the same modeling strategy applied to ALS tree height estimates. Our study also identified some of the drivers of the pCHM tree height estimate error and found forest parameters like tree size (diameter at breast height) and tree type (evergreenness/deciduousness) as well as the terrain topography (slope) to be of higher importance than image survey parameters like the variation of the overlap or the sunlight condition in our dataset. In combination with the pCHM tree height estimate, the terrain slope, the Diameter at Breast Height (DBH) and the evergreenness factor were used to fit a multivariate model predicting the field measured tree height. This model presented better performance than the model linking the pCHM estimates to the field tree height estimates in terms of r² (0.90 VS 0.87) and root mean square error (RMSE, 1.78 VS 2.01 m). Such aspects are poorly addressed in literature and further research should focus on how pCHM approaches could integrate them to improve forest characterization using DAP and pCHM. Our promising results can be used to encourage the use of regional aerial orthophoto surveys archive to produce large scale quality tree height data at very low additional costs, notably in the context of updating national forest inventory programs.

Comparing terrestrial laser scanners’ ability to measure tree height and diameter in a managed forest environment

ABSTRACT Terrestrial laser scanning (TLS) instruments like the Zebedee (including the Zeb-1 and its derivatives) and Dual-Wavelength Echidna LiDAR (DWEL) can usefully measure tree diameter, height and annual height growth for trees up to at least 10 m tall in a forest plantation setting. In a case study at the National Arboretum Canberra, these two types of scanner were compared with traditional methods (diameter tape and height stick) in the measurement of tree diameter, height and growth rate. The TLS instruments were accurate with height measurement correlations of not different to 1:1 and with r 2 = 0.99 and 0.98 (Zeb-1 and DWEL, respectively), whereas comparing measurements of height growth over a two-year period, the TLS instruments displayed an agreement of 83% and 93%, respectively. The Zebedee instruments also correlated significantly with diameter at breast height (DBH; r 2 = 0.97), although limited tests with the DWEL collected at a single point in inventory plots did not find a significant correlation. The additional detail provided by TLS instruments such as Zeb-1and DWEL has the potential to substantially improve data collected about the spatial distribution, canopy dimensions and trunk parameters of numerous trees in an operational inventory of a forest stand. However, there may be difficulties in developing and testing new reference definitions of these parameters, especially ‘diameter’, that would allow historical comparisons and improved future use for foresters and ecologists.

Structural variability of Aleppo pine stands in two forests in northeastern Algeria

Abstract. Rached-Kanouni M, Hani I, Bousba R, Beldjazia A, Khammar H. 2020. Structural variability of Aleppo pine stands in two forests in northeastern Algeria. Biodiversitas 21: 2848-2853. The layout of the stand can be described as the width of the trees, their reciprocal locations, diametric distinction and height. The goal of this study is to recognize changes in the Pinus halepensis spatial and demographic systems in two Beni Oudjana and Chettaba Forests, located in northeast Algeria. An inventory of trees in these forest formations with P. halepensis dominance was carried out based on dendrometric parameters such as total height, tree diameter at dbh ≥ 5 cm, basal area, total volume, etc., as well as the number of trees in the forest. Tree diameter and height measurements were made on 12 rectangular plots (20 m × 20 m), located in both forests. The results obtained show that the mean stand density, mean diameter, basal area and total volume are higher in Chettaba Forest, the values attributed to these parameters are respectively (422 trees/ha, 27.07 cm, 26, 86 m2, 251.63 m3); while the total height and regeneration rate show significantly higher values in Beni Oudjana Forest (18.97 m, 607 individuals/ha). The structure in diameter and height of the species is bell-shaped to asymmetrically positive with a predominance of small diameter individuals in the Chettaba forest. On the other hand, in the Beni Oudjana Forest, the structure is ‘L’ shaped, showing a predominance of very small diameter individuals. These results indicate that the low regeneration rate of P. halepensis in the Chettaba Forest is due to anthropogenic pressures that favor the degradation of this forest.

Estimating Tree Height and Volume Using Unmanned Aerial Vehicle Photography and SfM Technology, with Verification of Result Accuracy

This study aimed to investigate the effects of differences in shooting and flight conditions for an unmanned aerial vehicle (UAV) on the processing method and estimated results of aerial images. Forest images were acquired under 80 different conditions, combining various aerial photography methods and flight conditions. We verified errors in values measured by the UAV and the measurement accuracy with respect to tree height and volume. Our results showed that aerial images could be processed under all the studied flight conditions. However, although tree height and crown were decipherable in the created 3D model in 64 conditions, they were undecipherable in 16. The standard deviation (SD) in crown area values for each target tree was 0.08 to 0.68 m2. UAV measurements of tree height tended to be lower than the actual values, and the RMSE (root mean square error) was high (5.2 to 7.1 m) through all the 64 modeled conditions. With the estimated volume being lower than the actual volume, the RMSE volume measurements for each flight condition were from 0.31 to 0.4 m3. Therefore, irrespective of flight conditions for UAV measurements, accuracy was low with respect to the actual values.

Evaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada

Red spruce (Picea rubens Sarg.) is an important tree species in northeastern North America. The impact of climate change on this tree species is expected to vary regionally, but may be negative within Canada’s eastern Acadian Forest Region as temperatures there are expected to rise by 2–6 °C by 2100 under the business-as-usual Representative Concentration Pathway (RCP) 8.5 climate forcing scenario. In this study, we use one series of historic provenance trials from northeastern North America to evaluate the capacity of red spruce to persist under climate change by analyzing measurements of tree height and diameter at breast height (DBH) in relation to differences between provenance origin climate and test site climate (i.e., climate differentials).Within the range of climate differentials tested, warming (i.e., when the test site was warmer than provenance origin) did not appear to have a deleterious effect on red spruce growth, but cooling (i.e., moving provenances to colder, more northerly sites) did negatively affect growth by reducing height and diameter. Indeed, warmer temperatures, relative to provenance origin, increased tree size, especially for the most northern provenances, suggesting red spruce at the northern extent of its geographical range in northeastern North America is currently cold suppressed and located in non-optimal climates. However, our capacity to test warming effects on more southerly provenances was limited in this study by lack of available test sites south of red spruce’s climatic range. Among the eight climate variables tested, changes in frost free period and mean annual temperature had the most significant impact on tree size. In general, temperature-related climate variables had stronger effects than moisture-related variables. Overall, our results provide important insight for foresters when considering the future management of red spruce in the Acadian Forest Region and the selection of climate adapted seed source.

Progeny performance and selection of superior trees within families in Larix olgensis

Larix olgensis is one of the most important timber species in Northeast China. Although L. olgensis seed orchards have been established for many years and some progeny tests have been conducted, studies of progeny performance and the selection of superior families are still lacking. These tests are important for upgrading and improvement of seed orchards. Here, we estimate the genetic variation for major economic traits between families to provide selection materials for the establishment of a second-generation seed orchard. This study examined 71 half-sib families and 2 control families of L. olgensis in the Xiyang forest seed orchard in Yongji County, Northeast China. We measured tree height, diameter at breast height, volume, branch angle, stem straightness degree and crown width of 4-year-old progeny. Genetic parameters for the studied traits were determined, and comprehensive analyses of multiple traits and breeding values were used for selection of superior families and individual trees within families. The results show that all these traits are significantly different (P < 0.01) among families where family variance was greater than environmental variance. The phenotypic and genotypic coefficients of variation ranged from 9.01% to 78.22% and from 1.81% to 39.20%, respectively. The heritability values of families and individual trees ranged from 0.663 to 0.959 and 0.034 to 0.983, respectively. There was a significant positive correlation between investigated traits. Using the multiple-traits comprehensive evaluation method, seven families and 56 superior individual trees were selected. Selection of superior parents using breeding values for timber yield, stem quality and crown width as a proxy for planting density again resulted in the selection of seven superior families. We determined that the comprehensive multiple-traits evaluation approach is effective for selecting superior families and individual trees for the establishment of advanced second generation seed orchards. Families selected based on breeding value may be used as preferred parents for future hybridization breeding.

Measuring Individual Tree Diameter and Height Using GatorEye High-Density UAV-Lidar in an Integrated Crop-Livestock-Forest System

Accurate forest parameters are essential for forest inventory. Traditionally, parameters such as diameter at breast height (DBH) and total height are measured in the field by level gauges and hypsometers. However, field inventories are usually based on sample plots, which, despite providing valuable and necessary information, are laborious, expensive, and spatially limited. Most of the work developed for remote measurement of DBH has used terrestrial laser scanning (TLS), which has high density point clouds, being an advantage for the accurate forest inventory. However, TLS still has a spatial limitation to application because it needs to be manually carried to reach the area of interest, requires sometimes challenging field access, and often requires a field team. UAV-borne (unmanned aerial vehicle) lidar has great potential to measure DBH as it provides much higher density point cloud data as compared to aircraft-borne systems. Here, we explore the potential of a UAV-lidar system (GatorEye) to measure individual-tree DBH and total height using an automatic approach in an integrated crop-livestock-forest system with seminal forest plantations of Eucalyptus benthamii. A total of 63 trees were georeferenced and had their DBH and total height measured in the field. In the high-density (&gt;1400 points per meter squared) UAV-lidar point cloud, we applied algorithms (usually used for TLS) for individual tree detection and direct measurement of tree height and DBH. The correlation coefficients (r) between the field-observed and UAV lidar-derived measurements were 0.77 and 0.91 for DBH and total tree height, respectively. The corresponding root mean square errors (RMSE) were 11.3% and 7.9%, respectively. UAV-lidar systems have the potential for measuring relatively broad-scale (thousands of hectares) forest plantations, reducing field effort, and providing an important tool to aid decision making for efficient forest management. We recommend that this potential be explored in other tree plantations and forest environments.

Inter-comparison of remote sensing platforms for height estimation of mango and avocado tree crowns

To support the adoption of precision agricultural practices in horticultural tree crops, prior research has investigated the relationship between crop vigour (height, canopy density, health) as measured by remote sensing technologies, to fruit quality, yield and pruning requirements. However, few studies have compared the accuracy of different remote sensing technologies for the estimation of tree height. In this study, we evaluated the accuracy, flexibility, aerial coverage and limitations of five techniques to measure the height of two types of horticultural tree crops, mango and avocado trees. Canopy height estimates from Terrestrial Laser Scanning (TLS) were used as a reference dataset against height estimates from Airborne Laser Scanning (ALS) data, WorldView-3 (WV-3) stereo imagery, Unmanned Aerial Vehicle (UAV) based RGB and multi-spectral imagery, and field measurements. Overall, imagery obtained from the UAV platform were found to provide tree height measurement comparable to that from the TLS (R2 = 0.89, RMSE = 0.19 m and rRMSE = 5.37 % for mango trees; R2 = 0.81, RMSE = 0.42 m and rRMSE = 4.75 % for avocado trees), although coverage area is limited to 1–10 km2 due to battery life and line-of-sight flight regulations. The ALS data also achieved reasonable accuracy for both mango and avocado trees (R2 = 0.67, RMSE = 0.24 m and rRMSE = 7.39 % for mango trees; R2 = 0.63, RMSE = 0.43 m and rRMSE = 5.04 % for avocado trees), providing both optimal point density and flight altitude, and therefore offers an effective platform for large areas (10 km2–100 km2). However, cost and availability of ALS data is a consideration. WV-3 stereo imagery produced the lowest accuracies for both tree crops (R2 = 0.50, RMSE = 0.84 m and rRMSE = 32.64 % for mango trees; R2 = 0.45, RMSE = 0.74 m and rRMSE = 8.51 % for avocado trees) when compared to other remote sensing platforms, but may still present a viable option due to cost and commercial availability when large area coverage is required. This research provides industries and growers with valuable information on how to select the most appropriate approach and the optimal parameters for each remote sensing platform to assess canopy height for mango and avocado trees.

Comparing Individual Tree Height Information Derived from Field Surveys, LiDAR and UAV-DAP for High-Value Timber Species in Northern Japan

High-value timber species such as monarch birch (Betula maximowicziana Regel), castor aralia (Kalopanax septemlobus (Thunb.) Koidz), and Japanese oak (Quercus crispula Blume) play important ecological and economic roles in forest management in the cool temperate mixed forests in northern Japan. The accurate measurement of their tree height is necessary for both practical management and scientific reasons such as estimation of biomass and site index. In this study, we investigated the similarity of individual tree heights derived from conventional field survey, digital aerial photographs derived from unmanned aerial vehicle (UAV-DAP) data and light detection and ranging (LiDAR) data. We aimed to assess the applicability of UAV-DAP in obtaining individual tree height information for large-sized high-value broadleaf species. The spatial position, tree height, and diameter at breast height (DBH) were measured in the field for 178 trees of high-value broadleaf species. In addition, we manually derived individual tree height information from UAV-DAP and LiDAR data with the aid of spatial position data and high resolution orthophotographs. Tree heights from three different sources were cross-compared statistically through paired sample t-test, correlation coefficient, and height-diameter model. We found that UAV-DAP derived tree heights were highly correlated with LiDAR tree height and field measured tree height. The performance of individual tree height measurement using traditional field survey is likely to be influenced by individual species. Overall mean height difference between LiDAR and UAV-DAP derived tree height indicates that UAV-DAP could underestimate individual tree height for target high-value timber species. The height-diameter models revealed that tree height derived from LiDAR and UAV-DAP could be better explained by DBH with lower prediction errors than field measured tree height. We confirmed the applicability of UAV-DAP data for obtaining the individual tree height of large-size high-value broadleaf species with comparable accuracy to LiDAR and field survey. The result of this study will be useful for the species-specific forest management of economically high-value timber species.

Evaluation of total tree height subsampling strategies for estimating volume in loblolly pine plantations

Assessing current conditions and projecting future forest productivity are primary objectives in designing forest inventory for forest management planning. Stand net volume, expressed as sum of all standing trees’ volume on a per-unit area basis, has been widely applied to quantify forest productivity. Total tree height is a principal predictor commonly used to estimate tree volume, weight and biomass. However, measuring tree heights in the field is time consuming and labor intensive. Measuring a small portion of trees on the sample plots, denoted as subsampling heights, is a relatively efficient alternative in many assessments of forest cover. In this study, sampling plans with different levels of subsampling intensity were evaluated. Four 37.63-ha loblolly pine plantations with varying degrees of spatial heterogeneity at four inventory entry points (ages 10, 15, 20 and 25) were simulated. The impact of tree height measurement error was assessed using data from 210 standing and felled trees measurements across southeastern US and incorporated in the simulations.Results indicate that sampling intensity, stand age, and spatial heterogeneity have greater influence on the reliability for total volume estimation than height subsampling intensity and measurement error. Precision of the total volume estimates decreased with increasing degrees of spatial heterogeneity and stand age. Adding sample plots is a more effective way to reduce error for total volume estimation than adding measurement trees on plots. The plantations and repeated samples simulated in this study provide important information about the behavior of total volume and related estimates under various scenarios, which provides guidance for ecologists and resource managers to design efficient subsampling strategies for height measurements.

English

Parkland agroforestry woody species are prominent features in many landscapes worldwide, and their ecological, social and economic importance is widely acknowledged. It is the traditional agroforestry systems from different countries and is almost a universal occurrence in Ethiopia. This study was conducted in Gindeberet District, West Shoa Zone, Oromia Regional State, Ethiopia to assess the parkland agroforestry woody species composition, diversity, structure and biomass carbon. Woody species inventory was carried out on 103 plots (each, 50 m x10 0m) in the crop field laid along 7 transects. For woody species &ge; 5 cm DBH, measurements of DBH and tree height were taken. A total of 61 woody species belonging to 35 families were recorded. The study indicated that the woody species Shannon and Simpson diversity indices were higher at lowland than midland agro-ecology. The species richness was significantly different between the two agro-ecological zones (X2 = 8.5,&nbsp;&nbsp; p = 0.003). This study showed low carbon storage potential in living biomass of woody species; it is recommended to develop a policy on the woody species management, conservation and regeneration to increase the carbon storage potential in living biomass of woody species. &nbsp; Key words: Parkland agroforestry, woody species, latitude, diversity index, biomass carbon.

Improving mangrove above-ground biomass estimates using LiDAR

Tree height is a key parameter to accurately quantify above ground biomass (AGB) of trees. Approaches that integrate airborne light detection and ranging (LiDAR) with mapped extents of forests may improve estimation of mangrove heights by providing considerably more measurements of mangrove tree heights than can be achieved using field-based measurements alone. In this study, we present a validated method for quantifying mangrove AGB that was demonstrated for a mangrove forest at Guarás Island, Brazil. The application of LiDAR to estimate mangrove height was confirmed by correlating 89 tree heights measured in the field with LiDAR-derived mangrove heights, resulting in highly robust relationships for Avicennia germinans, Laguncularia racemosa and Rhizophora mangle (R2 = 0.90–0.97, RMSE of 1.24–0.67 m and RMSE% of 11.26%–25.97%). These relationships were used to calibrate a LiDAR-derived canopy height model (CHM) and develop robust relationships between the calibrated-CHM and field-based estimates of AGB (R2 = 0.85–0.92, RMSE of 3.1 kg–42.53 kg, RMSE% of 20.66%–43.81%). This relationship was then applied to the CHM whilst accounting for tree density to estimate mangrove AGB. Total mangrove AGB per hectare was estimated to be 246.90 t ha−1, corresponding closely with previous mangrove AGB measurements within the region. This study found that mangrove height and AGB are statistically related and these relationships can be applied to allometric equations for specific species to improve mangrove AGB estimates. This study demonstrates the capacity for LiDAR-derived tree heights to replace traditional approaches to estimating AGB and improving estimates of mangrove blue carbon storage. Application of LiDAR to determine tree heights will be particularly useful where mangrove is extensive and/or remote.

Estimating Mangrove Tree Biomass and Carbon Content: A Comparison of Forest Inventory Techniques and Drone Imagery

Mangroves provide many ecosystem services including a considerable capacity to sequester and store large amounts of carbon, both in the sediment and in the above-ground biomass. Assessment of mangrove above-ground carbon stock relies on accurate measurement of tree biomass, which traditionally involves collecting direct measurements from trees and relating these to biomass using allometric relationships. We investigated the potential to predict tree biomass using measurements derived from unmanned aerial vehicle (UAV), or drone, imagery. This approach has the potential to dramatically reduce time-consuming fieldwork, providing greater spatial survey coverage and return for effort, and may enable data to be collected in otherwise hazardous or inaccessible areas. We imaged a mangrove stand using an RGB camera mounted on a UAV. The imaged trees were subsequently felled, enabling physical measurements to be taken for traditional biomass estimation techniques, as well as direct measurements of biomass and tissue carbon content. UAV image-based tree height measurements were highly accurate (R2 = 0.98). However, the variables that could be measured from the UAV imagery (tree height and canopy area) were poor predictors of tree biomass. Using the physical measurement data, we identified that trunk diameter is a key predictor of A. marina biomass. Unfortunately, trunk diameter cannot be directly measured from the UAV imagery, but it can be predicted (with some error) using models that incorporate other UAV image-based measurements, such as tree height and canopy area. However, reliance on second-order estimates of trunk diameter led to increased uncertainty in the subsequent predictions of A. marina biomass, compared to using physical measurements of trunk diameter taken directly from the trees. Our study demonstrates that there is potential to use UAV-based imagery to measure mangrove A. marina tree structural characteristics and biomass. However, further refinement of the relationship between UAV image-based measurements and tree diameter is needed to reduce error in biomass predictions. UAV image-based estimates can be made far more quickly and over extensive areas when compared to traditional data collection techniques and, with improved accuracy through further model-calibration, have the potential to be a powerful tool for mangrove biomass and carbon storage estimation.