Tree Diameter At Breast Height Research Articles

Quantification of Individual Tree Competition Index Taking Chinese-Fir Plantations in Subtropical Low Hilly Area as an Example

Competition among trees is a fundamental interaction process within plant community, which is the theoretical basis of thinning. Plant competitive intensity is generally measured using a competition index (CI) that can be classified into two major categories: distance-independent and distance-dependent. The current study used Cunninghamia lanceolata (Lamb.) Hook as the test subject and used Hegyi's CI (distance-dependent), to quantify individual CI and their relationship with tree diameter at breast height (DBH). Five different criteria were used to select potential competitors for the calculation of CI. Seven basic linear and nonlinear mathematical functions were used to test and quantify the relationships between DBH of the target tree and the individual CI. Results showed that individual CI was negatively correlated with target tree DBH: as DBH increased, competition intensity weakened. The adjusted R2 with five different criteria of selection competitors simulated by seven functions ranged from 0.30 to 0.82. Considering the root mean square error (RMSE), P-value, and adjusted-R2, our results suggested that the best model to simulate the relationship between individual CI and focal tree DBH was power function (CI = 43.98 × DBH-1.08, adjusted R2 = 0.81) and with the Voronoi diagram method as the criteria for selecting competitors. These results can demonstrate a clearer understanding of the spatial structure of forests, and can be used to guide the selection of thinning trees in the process of thinning practice.

Generalized Nonlinear Mixed-Effects Individual Tree Diameter Increment Models for Beech Forests in Slovakia

Individual tree growth and yield models precisely describe tree growth irrespective of stand complexity and are capable of simulating various silvicultural alternatives in the stands with diverse structure, species composition, and management history. We developed both age dependent and age independent diameter increment models using long-term research sample plot data collected from both monospecific and mixed stands of European beech (Fagus sylvatica L.) in the Slovak Republic. We used diameter at breast height (DBH) as a main predictor and other characteristics describing site quality (site index), stand development stage (dominant height and stand age), stand density or competition (ratio of individual tree DBH to quadratic mean diameter), species mixture (basal area proportion of a species of interest), and dummy variable describing stand management regimes as covariate predictors to develop the models. We evaluated eight versatile growth functions in the first stage using DBH as a single predictor and selected the most suitable one, i.e., Chapman-Richards function for further analysis through the inclusion of covariate predictors. We introduced the random components describing sample plot-level random effects and stochastic variations on the diameter increment, into the models through the mixed-effects modelling. The autocorrelation caused by hierarchical data-structure, which is assumed to be partially reduced by mixed-effects modelling, was removed through the inclusion of the parameter accounting for the autoregressive error-structures. The models described about two-third parts of a total variation in the diameter increment without significant trends in the residuals. Compared to the age independent mixed-effects model (conditional coefficient of determination, R c 2 = 0.6566; root mean square error, RMSE = 0.1196), the age dependent model described a significantly larger proportion of the variations in diameter increment ( R c 2 = 0.6796, RMSE = 0.1141). Diameter increment was significantly influenced differently by covariate predictors included into the models. Diameter increment decreased with the advancement of stand development stage (increased dominant height and stand age), increasing intraspecific competition (increased basal area proportion of European beech per sample plot), and diameter increment increased with increasing site quality (increased site index) and decreased competition (increased ratio of DBH to quadratic mean diameter). Our mixed-effects models, which can be easily localized with the random effects estimated from prior measurement of diameter increments of four randomly selected trees per sample plot, will provide high prediction accuracies. Our models may be used for simulating growth of European beech irrespective of its stand structural complexity, as these models have included various covariate variables describing both tree-and stand-level characteristics, thinning regimes, except the climate characteristics. Together with other forest models, our models will be used as inputs to the growth simulator to be developed in the future, which is important for decision-making in forestry.

Global patterns of tree stem growth and stand aboveground wood production in mangrove forests

Mangrove forests provide important ecological and economic services including carbon sequestration and storage. The conservation and restoration of mangroves are expected to play an important role in mitigating climate change, and understanding the factors influencing mangrove stem growth and wood production are important in predicting and improving mangrove carbon sequestration and responses to environmental change. In this study, we collected data of individual diameter at breast height (DBH) growth rate and stand level aboveground wood production in both non-plantation (commonly termed as natural) mangroves and mangrove plantations across the world. Climatic factors, proxies of edaphic factors, as well as biological factors (e.g. mangrove species) were included as explanatory variables in the analyses to determine factors influencing the global patterns of tree growth rate and stand wood production of mangroves. Using hierarchical Classification and Regression Tree (CART) analysis we found interactions among environmental and biological factors in controlling mangrove tree growth rate and stand wood production. We also found different global patterns of tree growth rate and stand wood production between non-plantation mangroves and plantations. Climatic conditions (precipitation of driest season, precipitation seasonality) were the most important factors influencing the global pattern of tree DBH growth rate in non-plantation mangroves, with edaphic and biological characteristics also playing a role under specific climatic conditions. The global pattern of stand wood production in non-plantation mangroves was primarily determined by stand mean DBH growth rate of individual trees. However, in mangrove plantations management measures, specifically species selection and planting density, were the most important factors influencing the global patterns of tree growth rate and stand wood production. Our study provides parameters for a global estimation of long-term carbon sequestration in both non-plantation mangroves and mangrove plantations. In addition, our results help us better predict the dynamics of tree growth and carbon sequestration of non-plantation mangroves under changing climate.

Estimating the heights and diameters at breast height of trees in an urban park and along a street using mobile LiDAR

Because trees can positively influence local environments in urban ecosystems, it is important to measure their morphological characteristics, such as height and diameter at breast height (DBH). However, measuring these data for each individual tree is a time-consuming process that requires a great deal of manpower. In this study, we investigated the feasibility of using mobile LiDAR to estimate tree height and DBH along urban streets and in urban parks. We compared measurements from a mobile LiDAR unit with field measurements of tree height and DBH in urban parks and streets. The height-above-ground and Pratt circle fit methods were applied to calculate tree height and DBH, respectively. The LiDAR-estimated tree heights were highly accurate albeit slightly underestimated, with a root mean square error of 0.359 m for the street trees and 0.462 m for the park trees. On the other hand, the estimated DBHs were moderately accurate and overestimated, with a root mean square error of 3.77 cm for the street trees and 8.95 cm for the park trees. Densely planted trees in the park and obstacles in urban areas result in “shadows” (areas with no data), reducing accuracy. Irregular trunk shapes and scanned data that did not include full data point coverage of every trunk were the reasons for the errors. Despite these errors, this study highlights the potential of tree measurements obtained with mobile terrestrial LiDAR platforms to be scaled up from point-based locations to neighborhood-scale and city-scale inventories.

Determinants of Piper (Piperaceae) climber composition in a lowland tropical rainforest in New Guinea

Climbing plants form a substantial component of tropical forest diversity. Climbers are a diverse group comprising various ecological strategies dependent on tree support and are affected by biotic and abiotic forest conditions. In a lowland primary tropical rainforest in Papua New Guinea, we studied the distribution of root climbers from genus Piper in relation to topography (slope, convexity, altitude) and properties of vegetation and of individual host trees (basal area of trees, and host tree size, abundance and species identity). In total, 1,058 Piper climber individuals belonging to 8 species occupied 13.7% of tree trunks with a diameter at breast height (DBH) > 1 cm. All Piper species generally avoided similar habitat conditions – higher altitude, steeper slopes, more closed canopy layer and bigger total basal area of host vegetation. The preferences of Piper climbers for some tree species are primarily determined by properties of host trees, mainly their DBH. Therefore, the probability of Piper presence on a tree increased with individual host tree DBH. Piper species were more frequently found on rare than common tree species. However, this relationship might be also explained by their affinity for higher tree DBH. Our findings point to non-random association between climbers and their host trees, in a complicated interplay with local environmental conditions. These interactions have very probably consequences for forest vegetation dynamics and maintenance of diversity.

Scots pine Pinus sylvestris mortality after surface fire in oligotrophic pine forest Peucedano-Pinetum in Kampinos National Park

Abstract Pines are generally fire-resistant trees. There is a shortage of research on the behaviour of Scots pine after surface fire in older stands. The aim of the work was to describe the effect of the surface fire intensity on the mortality of pines of various diameter at breast height (DBH), including older trees. The research was conducted in Peucedano-Pinetum oligotrophic Scots-pine forest in Kampinos National Park (KPN, central Poland) on the area of two adjacent surface fire sites originated in spring 2015 in 60- to 200-year-old stands (site area: 10,92 ha). There were 45 (28 burned and 17 control) permanent plots established after the fire. The share of not burned, superficially burned and completely burnout organic horizon of the soil was determined within all of them. DBH and location of pine trees were measured within all of the plots on the area of 200 m2. For all of the trees for which full information about soil organic horizon damage was mapped, the prevailing type of disturbance in their close neighbourhoods with radii of 1 and 2 m was assessed. The mortality of trees was assessed after each vegetation period up to 2017, basing on the presence of green needles on the trees. The influence of fire intensity on the survival of trees was examined on whole permanent plot level as well as on individual tree level. Strong linear correlation was observed between Scots pine mortality and the share of plots area with damaged organic layer, especially at the end of the third vegetation period after fire. Logistic regression models constructed for individual trees suggest that bigger tree diameter (hence, thicker bark) diminished the odds of mortality only after two vegetation periods from the fire. After the third vegetation period, only the intensity of surface fire in the close neighbourhood of trees influenced (negatively) the chance on survival. The size of trees did no matter in this case. Nearly all of the trees that were located within burnout organic matter areas died. The results did not support the commonly known mechanism of enhancement of bigger Scots pine tree survival after surface fire because of thicker bark responsible for heat protection. Probably, the main cause of observed mortality was not overheating of cambium but it was rather connected to massive fine root loses. Scots pines growing on oligotrophic arid sites modify their root system to explore topsoil layers with higher proportion of shallow roots, growing even in organic litter layer. This corresponds with massive (regardless of size) pine mortality within sites characterised by complete burnout of organic matter layer and very high survival in those ones with only surfacely burned litter layer. The results can improve the assessment of surface fires consequences in managed Scots pine stands growing in oligotrophic conditions.

Ecological Sustainability of Detar (<i>Detarium senegalense</i> J. F. Gmel) in Togo (West Africa)

Detarium senegalense J. F. Gmel., of the family of Fabaceae is one of the most exploited tree species in Togo. However, there are only few scientific studies on the distribution of this specie. This study is a contribution to the promotion of multi-purpose tree species in Togo with particular emphasis on a better knowledge of Detarium senegalense. It provides data on the ecology of the specie and his state of regeneration. The data on the specie are based on sample plots in the areas identified as hosts of the specie in Togo. A total of 77 circular plots of 1000 m2 (17.8 m radius) were established in ecological zones II, IV and V of Togo. The dendrometric parameters identified are: the total height and diameter at breast height (DBH) of Detarium senegalense and of all species found in each plot. Detarium senegalense trees of DBH Detarium senegalense is more abundant in zones IV (forest area), followed by zone II. In zone V, Detarium senegalense is located only in the forest of “Have”. The structure of Detarium senegalense has a bell-shaped distribution with predominance of trees with large and intermediate diameters ranging between 30 and 70 cm. Trees of small DBH (Detarium senegalense occurs. This indicates a low regeneration rate of the specie. However, the structure of all species inventoried has a negative exponential distribution with predominance of small diameter trees. The sustainable management of Detarium senegalense in the forest can only be secured through a sustainable harvesting of seeds and actives promotion of natural regeneration.

A basal area increment model for individual trees in mixed continuous cover forests in Iranian Caspian forests

The aim of this study was to develop and test a new basal area growth model in mixed species continuous cover forests in northern Iran. We analyzed 421 core samples from 6 main species in the forest area to develop our growth model. In each plot, we measured variables such as total tree height (m), diameter at breast height (DBH) (cm) and basal area of larger trees as cumulative basal areas of trees (GCUM) of DBH > 5 cm. The empirical data were analyzed using regression analysis. There was a statistically significant nonlinear function between the annual basal area increment, as the dependent variable, and the basal area of the individual trees and competition as explanatory variables. Reference area from the largest trees, was circular plot with area of 0.1 ha. GCUM was estimated for trees of DBH > 5 cm. Furthermore, we investigated the dependencies of diameter growth of different species on stand density at different levels of competition, and diameter development of individual trees through time. The results indicate that competition caused by larger neighborhood trees has a negative effect on growth. In addition, the maximum diameter increment is affected by competition level. Therefore, the maximum diameter increment of species occurs when the trees are about 35–40 cm in dense-forest (40 to 0 m2 per ha) and when the trees are about 60 to 70 cm in very dense forest (60 to 0 m2 per ha) which is more likely to Caspian natural forests with high level density due to uneven-aged composition of stands.

Estimating Tree Position, Diameter at Breast Height, and Tree Height in Real-Time Using a Mobile Phone with RGB-D SLAM

Accurate estimation of tree position, diameter at breast height (DBH), and tree height measurements is an important task in forest inventory. Mobile Laser Scanning (MLS) is an important solution. However, the poor global navigation satellite system (GNSS) coverage under the canopy makes the MLS system unable to provide globally-consistent point cloud data, and thus, it cannot accurately estimate the forest attributes. SLAM could be an alternative for solutions dependent on GNSS. In this paper, a mobile phone with RGB-D SLAM was used to estimate tree position, DBH, and tree height in real-time. The main aims of this paper include (1) designing an algorithm to estimate the DBH and position of the tree using the point cloud from the time-of-flight (TOF) camera and camera pose; (2) designing an algorithm to measure tree height using the perspective projection principle of a camera and the camera pose; and (3) showing the measurement results to the observer using augmented reality (AR) technology to allow the observer to intuitively judge the accuracy of the measurement results and re-estimate the measurement results if needed. The device was tested in nine square plots with 12 m sides. The tree position estimations were unbiased and had a root mean square error (RMSE) of 0.12 m in both the x-axis and y-axis directions; the DBH estimations had a 0.33 cm (1.78%) BIAS and a 1.26 cm (6.39%) root mean square error (RMSE); the tree height estimations had a 0.15 m (1.08%) BIAS and a 1.11 m (7.43%) RMSE. The results showed that the mobile phone with RGB-D SLAM is a potential tool for obtaining accurate measurements of tree position, DBH, and tree height.

Can forest structural diversity be a response to anthropogenic stress? A case study in old-growth fir Abies alba Mill. stands

Key messageFrom 1973 to 1991, Polish SO2emissions above 3250 Gg/year resulted in a decline of firAbies albaMill. After stresses connected with these emissions, five main diameter at breast height (DBH) structural types were described. This type of heterogeneous forest structure is supposed to increase forest resistance and resilience to abiotic, biotic and anthropogenic disturbances.ContextThe analyses of forest structure are important under the current scenario of global change, since heterogeneous structures allow for better responses to disturbances. Forests with more complex structures should present greater vitality.AimsThe main hypotheses were as follows: (1) the temporal changes of atmospheric SO2 emissions caused (a) the abrupt changes in the tree DBH radial increment and (b) the death of fir trees; and (2) atmospheric SO2 emissions and related fir decline and recovery processes ultimately result in the development of stands characterised by diverse DBH structures.MethodsRadial growth trends of 49 and 215 fir trees in the older and younger generations, respectively, and 85 dead fir trees were evaluated. Using data collected in 32 stands, the DBH structural types were identified, and the shapes of these types were illustrated.ResultsThe structural diversification of forest patches may influence forest resistance and resilience to disturbances; five main structural types were identified: ML1 and ML2 represent DBH distributions of multi-layered stands, and OS, TS1 and TS2 represent DBH distributions of one- and two-storied stands.ConclusionStructural diversity of forests was a response to SO2 emissions; fir trees had the ability to increase their radial growth, although there were still high SO2 emissions.

Evaluating Carbon Sequestration and PM2.5 Removal of Urban Street Trees Using Mobile Laser Scanning Data

Street trees are an important part of urban facilities, and they can provide both aesthetic benefits and ecological benefits for urban environments. Ecological benefits of street trees now are attracting more attention because of environmental deterioration in cities. Conventional methods of evaluating ecological benefits require a lot of labor and time, and establishing an efficient and effective evaluating method is challenging. In this study, we investigated the feasibility to use mobile laser scanning (MLS) data to evaluate carbon sequestration and fine particulate matter (PM2.5) removal of street trees. We explored the approach to extract individual street trees from MLS data, and street trees of three streets in Nantong City were extracted. The correctness rates and completeness rates of extraction results were both over 92%. Morphological parameters, including tree height, crown width, and diameter at breast height (DBH), were measured for extracted street trees, and parameters derived from MLS data were in a good agreement with field-measured parameters. Necessary information about street trees, including tree height, DBH, and tree species, meteorological data and PM2.5 deposition velocities were imported into i-Tree Eco model to estimate carbon sequestration and PM2.5 removal. The estimation results indicated that ecological benefits generated by different tree species were considerably varied and the differences for trees of the same species were mainly caused by the differences in morphological parameters (tree height and DBH). This study succeeds in estimating the amount of carbon sequestration and PM2.5 removal of individual street trees with MLS data, and provides researchers with a novel and efficient way to investigate ecological benefits of urban street trees or urban forests.

Tree DBH measurement method based on smartphone and machine vision technology.

Aiming at the problems of high labor intensity and low efficiency, complicated operation and high cost of advanced equipment in the measurement of DBH in existing traditional forest resources, and proposing a method for measuring diameter at breast height (DBH) based on smartphone and machine vision technology, and combining with camera calibration, 3D reconstruction, machine vision, close-range photogrammetry, and other technologies. First, The original image is obtained by smartphone, and the visual saliency map of the preprocessed image is processing by using the lab color space model and 3×3 operator to convolving with image. Combining with the H component of the HSV (Hue, Saturation, Value) color model to enhance the color contrast part of the tree trunk in the image. The image segmentation algorithm is used to identify and obtain the target tree's contour in a natural environment. Then, an improved camera calibration model with nonlinear distortion terms is used to calibrate the camera's internal and external parameters. Finally, achieving reconstruction of a 3D world with camera parameters and two-dimensional image information is carried out to measure DBH at a height of 1.3 m. Experimental results indicated that within a certain range, the relative error of the DBH measurements was lower than 2.50%. This method has a high measurement accuracy, meeting the accuracy requirement of DBH measurement in forest resources investigation and could be applied in forestry resource surveys.

Climate and soils determine aboveground biomass indirectly via species diversity and stand structural complexity in tropical forests

Theoretical and empirical studies have suggested that climate and soils are the main drivers of biodiversity, stand structure and aboveground biomass in natural forests. Yet, the direct effects of climate and soils on aboveground biomass versus the indirect effects mediated by species diversity and stand structural complexity remain unclear in forest ecosystems across large-scale ecological gradients. Here, we hypothesized that (1) climate and soils would influence aboveground biomass through strong indirect effects; (2) stand structural complexity rather than species diversity would strongly mediate the response of aboveground biomass to climate and soils; and (3) species diversity and stand structural complexity would promote each other under the niche differentiation and facilitation effects, and that stand structural complexity would have positive effects on aboveground biomass across large-scale ecological gradients. To test these hypotheses, we quantified climatic water availability, soil total exchangeable bases, species diversity, stand structural complexity including tree DBH (diameter at breast height) diversity and height diversity, and aboveground biomass across 907 plots in tropical forests of Hainan Island, Southern China. We tested 126 structural equation models to examine the direct and indirect effects of climate and soils on aboveground biomass via species diversity and stand structural complexity. Climatic water availability and soil fertility did not affect aboveground biomass directly but did affect indirectly via increasing stand structural complexity rather than species diversity. Species diversity and stand structural complexity promoted each other, and both increased with increasing climatic water availability. Stand structural complexity increased aboveground biomass directly, whereas species diversity increased it indirectly via increasing stand structural complexity. The total effects of climatic water availability, soil fertility, stand structural complexity and species diversity on aboveground biomass were significantly positive. This study shows that climatic water availability exerts a strong direct effect on stand structural complexity, indicating that any decrease in climatic water availability (i.e. increasing atmospheric drought) may directly diminish stand structural complexity and hence indirectly reduce aboveground biomass and carbon storage. This study suggests that maintaining high stand structural complexity can enhance aboveground biomass under favourable climate and soils while maintaining the benefits of species diversity on stand structural complexity for better ecosystem services such as carbon storage.

Allometric Equations for Estimating Silk Oak (Grevillea robusta) Biomass in Agricultural Landscapes of Maragua Subcounty, Kenya

Grevillea robusta is widely interplanted with crops in Maragua subcounty, a practice that enhances biomass quantities in farmlands. However, quick tools for estimating biomass of such trees are lacking resulting in undervaluation of the farm product. This study sought to develop allometric equations for estimating tree biomass using diameter at breast height (DBH) and tree height as predictor variables. Tree biomass was computed using thirty-three (33) trees randomly selected from 12 one hectare plots established in each of the four agroecological zones (AEZs). DBH of all Grevillea robusta trees per plot was measured and three trees were selected for destructive sampling to cover the variety of tree sizes. Regression analysis was used to develop equations relating DBH/tree height to biomass based on linear, exponential, power, and polynomial functions. The polynomial and the power equations had the highest R2, lowest SEE, and MRE values, while DBH was the most suitable parameter for estimating tree biomass. The tree stem, branches, foliage, and roots biomass comprised 56.89%, 14.11%, 6.67%, and 22.32% of the total tree biomass, respectively. The mean tree biomass density (12.430±1.84 ton ha−1) showed no significant difference (p=0.09) across AEZs implying no difference in G. robusta agroforestry stocks across the AEZ. The allometric equations will support marketing of tree products by farmers and therefore better conservation and management of the tree resource.

Abundance and distribution of cavity trees and the effect of topography on cavity presence in a tropical rainforest, southwestern China

Cavity trees play a crucial role in maintaining biodiversity in forest ecosystems as they host numerous birds, mammals, and other cavity-dependent organisms. However, studies on the abundance and distribution of cavity trees in tropical forests are much less common than those in temperate forests. Also, how tree characteristics and topographic variables affect cavity presence is less clear in tropical forests. We surveyed 27 745 living trees from 386 species using ground-based observations in a tropical rainforest in southwestern China. The density of cavity trees was 86.3 trees·ha–1, which dramatically exceeded that in temperate forests. The number of cavity trees showed a left-skewed distribution with a peak at 10–20 cm diameter at breast height (DBH). The probability of cavity presence in a tree increased with DBH, although the patterns varied across species and crown positions. Moreover, cavity presence, which is influenced by topography in this tropical forest, decreased from valleys (concave terrain and low elevation) to ridges (convex terrain and high elevation). The results prove for the first time that topography is a good predictor of cavity presence, in addition to tree DBH. Our results demonstrate that the patterns determined for cavity presence in tropical forests of other regions also apply to Asian tropical forests. This study provides guidance on predicting the occurrence of cavity trees in the tropics.

Estimating Individual Tree Height and Diameter at Breast Height (DBH) from Terrestrial Laser Scanning (TLS) Data at Plot Level

Abundant and refined structural information under forest canopy can be obtained by using terrestrial laser scanning (TLS) technology. This study explores the methods of using TLS to obtain point cloud data and estimate individual tree height and diameter at breast height (DBH) at plot level in regions with complex terrain. Octree segmentation, connected component labeling and random Hough transform (RHT) are comprehensively used to identify trunks and extract DBH of trees in sample plots, and tree height is extracted based on the growth direction of the trees. The results show that the topography, undergrowth shrubs, and forest density influence the scanning range of the plots and the accuracy of feature extraction. There are differences in the accuracy of the results for different morphological forest species. The extraction accuracy of Yunnan pine forest is the highest (DBH: Root Mean Square Error (RMSE) = 1.17 cm, Tree Height: RMSE = 0.54 m), and that of Quercus semecarpifolia Sm. forest is the lowest (DBH: RMSE = 1.22 cm, Tree Height: RMSE = 1.23 m). At plot scale, with the increase of the mean DBH or tree height in plots, the estimation errors show slight increases, and both DBH and height tend to be underestimated.

A New Algorithm for MLS-Based DBH Mensuration and Its Preliminary Validation in an Urban Boreal Forest: Aiming at One Cornerstone of Allometry-Based Forest Biometrics

This study aimed to improve one basic circle of allometry-based forest biometrics—diameter at breast height (DBH) mensuration. To address its common shortage of low efficiency in field measurement, this study attempted mobile laser scanning (MLS) as an efficient alternative and proposed a new MLS-based DBH mensuration algorithm to further exclude the effect of stem bending. That is, prior to the procedure of cone-based geometric modeling of a tree stem, an operation of Aligning the local stem axis series that is calculated by the Successive Cone-based Fitting of those continuously equi-height-layered laser points on the stem (ASCF) is appended. In the case of an urban boreal forest, tests showed that the proposed algorithm worked better (the coefficient of determination, R2 = 0.81 and root mean square error, RMSE = 52.1 mm) than the circle- (0.16 and 189.4 mm), cylinder- (0.77 and 58.7 mm), and cone-based (0.77 and 56.7 mm) geometric modeling algorithms. From a methodological viewpoint, the new ASCF algorithm was preliminarily validated for MLS-based tree DBH mensuration, with the “cornerstone-rebuilding” significance for allometry-based forest biometrics. With the development of MLS variants available for complex forest environments, this study will contribute fundamental implications for advancements in forestry.

A comparison of two methods of data collection for modelling productivity of harvesters: manual time study and follow-up study using on-board-computer stem records

Productivity of a mechanized P. patula cut-to-length harvesting operation was estimated and modelled using two methods of data collection: manual time study and follow-up study using StanForD stem files. The objective of the study was to compare the productivity models derived using these two methods to test for equivalence. Manual time studies were completed on four different machines and their operators. Two Ponsse Bear harvesters fitted with H8 heads, and two Ponsse Beaver harvesters, fitted with H6 heads, were included. All machines were equipped with Ponsse Opti2 information system. All four operators had approximately 1 year of experience working with their respective machines. The four machines worked in separate four-tree-wide harvesting corridors, and they each harvested 200 trees. Individual tree diameter at breast height (DBH), and height measurements were made manually. Subsequently, data on the trees in each study were extracted from the StanForD stem reports from each of the harvesters. Cycle times in the stem reports were determined based on the difference between consecutive harvest timestamps. The two methods were compared in terms of their abilities to estimate equivalent measures for tree DBH, volume, and productivity. In all four cases, significant differences were found between the DBH and volume measures derived using the two methods. Subsequently, the volume measures from the manual methods were used as the basis for productivity calculations. Results of the productivity comparisons found no significant differences between the models developed from the two methods. These results suggest that equivalent productivity models can be developed in terms of time using either method, however volume discrepancies indicate a need to reconcile bark and volume functions with the high variability experienced in the country.

Comparing Terrestrial Laser Scanning (TLS) and Wearable Laser Scanning (WLS) for Individual Tree Modeling at Plot Level

This study presents a comparison between the use of wearable laser scanning (WLS) and terrestrial laser scanning (TLS) devices for automatic tree detection with an estimation of two dendrometric variables: diameter at breast height (DBH) and total tree height (TH). Operative processes for data collection and automatic forest inventory are described in detail. The approach used is based on the clustering of points belonging to each individual tree, the isolation of the trunks, the iterative fitting of circles for the DBH calculation and the computation of the TH of each tree. TLS and WLS point clouds were compared by the statistical analysis of both estimated forest dendrometric parameters and the possible presence of bias. Results show that the apparent differences in point density and relative precision between both 3D forest models do not affect tree detection and DBH estimation. Nevertheless, tree height estimation using WLS appears to be affected by the limited scanning range of the WLS used in this study. TH estimations for trees below a certain height are equivalent using WLS or TLS, whereas TH of taller trees is clearly underestimated using WLS.

A new approach to evaluate the MODIS annual NPP product (MOD17A3) using forest field data from Turkey

ABSTRACTIn this study, we present the first evaluation of the MODIS (Moderate Resolution Imaging Spectroradiometer) annual net primary production (NPP) for Turkey’s forest ecosystems using field measurements. Due to lack of country scale field measurements (i.e. flux tower for forest ecosystems), tree DBH (diameter at breast height) data set provided by Ministry of Forest and Water Affairs (MFWA) of Turkey is used to calculate NPP of Turkey’s forest ecosystems. The lack of a reliable NPP data set leads the researchers to use global NPP models such as MODIS annual NPP product. The MODIS MOD17A3 product of vegetation NPP is one of the most highly used data sources for studies of global carbon cycle. However, it is still necessary to test its predictions in multiple biomes, especially for heterogeneous areas in terms of its accuracy and potential bias. Here, we studied a new approach to evaluate coarse scale NPP estimates from the MODIS NPP-MOD17A3 data product, using 2008–2013 field measurements of tree growth throughout Turkey. Three different methods were used to calculate field NPP, including standardized growth coefficients (ministry coefficients [MC]), growth coefficients from North America (Jenkins coefficients [JC]), and annual expected increment (AEI). The average NPP values for all the country is calculated as 2.06 kgC m–1/5 years (0.412 kgC m–2 year–1) (SD = 1.15 kgC m–1/5 years) from MOD17A3, 0.90 kgC m–1/5 years (0.18 kgC m–2 year–1) (SD = 0.57 kgC m–1/5 years) with MC, 0.63 kgC m–1/5 years (0.126 kgC m–2 year–1) (SD = 0.37 kgC m–1/5 years) with JC and 0.58 kgC m–2 year–1 (SD = 0.29 kgC m–1/5 years) with AEI for the studied plots. We found that the MODIS NPP product has a clear relation with both the NPP estimates obtained by using MC (R2 = 0.34, root mean square error (RMSE) = 1.51 kgC m–1/5 years) and JC (R2 = 0.32, RMSE = 1.73 kgC m–1/5 years). In addition to that, the relation between MOD17A3 product and AEI-derived NPP is relatively strong (R2 = 0.48, RMSE = 0.26 kgC m–2 year–1). We discuss possible reasons for these trade-offs among different methods. This study lays out a new approach to validate coarse scale MODIS product using field data directly, including for highly heterogeneous areas.