scholarly journals Individual tree measurements by means of digital aerial photogrammetry

2004 ◽  
Vol 2004 (3) ◽  
Author(s):  
Ilkka Korpela

This study explores the plausibility of the use of multi-scale, CIR aerial photographs to conduct forest inventory at the individual tree level. Multiple digitised aerial photographs are used for manual and semi-automatic 3D positioning of tree tops, for species classification, and for measurements on tree height and crown width. A new tree top positioning algorithm is presented and tested. It incorporates template matching in a 3D search space. Also, a new method is presented for tree species classification. In it, a partition of the image space according to the continuously varying image-object-sun geometry of aerial views is performed. Discernibility of trees in aerial images is studied. The measurement accuracy and overall measurability of crown width by using manual image measurements is investigated. A simulation study is used to examine the combined effects of discernibility and photogrammetric measurement errors on stand variables. The study material contained large-scale colour and CIR image material and 7708 trees from 24 fully mapped plots in Southern Finland. The results of the discernibility analysis suggest that 88–100% of the total stem volume is measurable when using multiple aerial photographs. The structure and density of the forest were found to affect discernibility. The best hit-rates when using the semi-automatic tree top positioning algorithm ranged from 77 to 100% of the visually discernible trees. Systematic underestimation of the crown width was observed and the measurability of crown width was best near the image nadir. Species classification was tested in mixed stands of Scots pine, Norway spruce, and silver birch. The Kappa-coefficients ranged from 0.71 to 0.86. The results of the simulation suggest that very high accuracy at the individual tree level cannot be expected. However, if the photogrammetric measurements are unbiased, the aggregate stand variables can be very accurate. An accurate species recognition method is needed in the mixed stands in order to achieve unbiased estimates for the small strata.

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 639
Author(s):  
Shah Rukh ◽  
Werner Poschenrieder ◽  
Michael Heym ◽  
Hans Pretzsch

Frequency of drought years is expected to increase through climate warming. Mixed stands have often shown to be more productive than monospecific stands in terms of yield and of resistance against windthrows and bark beetle attacks. Mixture of beech and spruce is of particular interest. However, little is known about its growth reaction to drought. Therefore, we investigated the drought reaction of beech and spruce in mixed vs. monospecific stands along an ecological gradient. In particular, we sought evidence for mixture-related resilience on the individual tree level. Therefore, we quantified the response of tree ring width to drought. Moreover, we attempted to explain the relevance of individual tree response on the stand level by quantifying the stand level loss of volume growth after drought. At the individual tree level, beech was found to be more resilient and resistant in pure vs. mixed stands. Spruce, in contrast, was favored by mixture, and this was especially evident on drier sites. Along the gradient, growth losses at stand level increased in both mixed and pure stands in 2015, with growth gains on the drier sites observed in the same drought year, in accordance with the Stress Gradient Hypothesis. However, the stand level difference of growth loss between mixed and pure stands was not statistically significant. Mitigating mixture effects on the level of the individual tree thus did not become evident on the level of the whole stand.


2011 ◽  
Vol 26 (2) ◽  
pp. 82-90 ◽  
Author(s):  
Richard D. Kabzems ◽  
George Harper ◽  
Peter Fielder

Abstract Managing boreal mixed stands of trembling aspen (Populus tremuloides Michx.) and white spruce (Picea glauca [Moench] Voss) is more likely to sustain a diversity of values and has the potential to increase productivity at both the site and landscape levels compared with pure broadleaf or conifer management. In this study, we examine growth of white spruce and aspen after 11 growing seasons over a range of aspen densities created by spot and broadcast treatment of broadleaves using manual and chemical means, aspen spacing, and an untreated control. Results indicate that survival and growth of both spruce and aspen were similar across the range of treatments. Spruce groundline diameter was greater, and height to groundline diameter ratio was lower, for the treatments in which aspen was chemically controlled or uniformly spaced compared with the control. Light measurements at the individual tree level suggested that increased light availability improved white spruce diameter growth. Spruce height growth did not vary by treatment. The status of these experimental mixedwoods was compared with current conifer and mixedwood regeneration evaluations, as well as the preharvest composition of the original stand. After 11 growing seasons, growth of aspen and white spruce indicated that opportunities exist to further modify aspen density to enhance treatment longevity and effectiveness to produce a greater range of boreal mixedwood stand types.


2016 ◽  
Vol 46 (5) ◽  
pp. 706-715 ◽  
Author(s):  
Michael Shettles ◽  
Thomas Hilker ◽  
Hailemariam Temesgen

In estimating aboveground forest biomass (AGB), three sources of error that interact and propagate include (i) measurement error, the quality of the tree-level measurement data used as inputs for the individual-tree equations; (ii) model error, the uncertainty about the equations of the individual trees; and (iii) sampling error, the uncertainty due to having obtained a probabilistic or purposive sample, rather than a census, of the trees on a given area of forest land. Monte Carlo simulations were used to examine measurement, model, and sampling errors and to compare total uncertainty between models and between a phase-based terrestrial laser scanner (TLS) and traditional forest inventory instruments. Input variables for the equations were diameter at breast height, total tree height (defined the height from the uphill side of the tree to the tree top), and height to crown base; these were extracted from the terrestrial LiDAR data. Relative contributions for measurement, model, and sampling errors were 5%, 70%, and 25%, respectively, when using TLS, and 11%, 66%, and 23%, respectively, when using the traditional inventory measurements as inputs into the models. We conclude that the use of TLS can reduce measurement errors of AGB compared with traditional inventory measurements.


2020 ◽  
Vol 28 ◽  
pp. 192-201
Author(s):  
Rodrigo Freitas Silva ◽  
Marcelo Otone Aguiar ◽  
Mayra Luiza Marques Da Silva ◽  
Gilson Fernandes Da Silva ◽  
Adriano Ribeiro De Mendonça

A continuously competitive forest market and tied to the demands for wood products promotes the study and development of applications that increase the revenue of the forest enterprises. At harvesting, the cutting pattern (forest assortment) in which the trees are traced is traditionally determined by the experience of the chainsaw operator without using any optimization technique, which may result in economic losses in relation to the commercialized products. In general, there are numerous distinct assortments that can be chosen and hardly processed by a brute-force algorithm. This is the forest assortment problem at the individual tree level with the objetice of maximizing the commercial values of the felled trees. stem-level bucking optimization problem. The aim is to maximize the sales value of harvested trees. Dynamic Programming (DP) is an efficient optimization technique to determine the optimum bucking tree as it significantly reduces the number of calculations to be made. Thus, the objective of this work was to develop a modern and intuitive computational system that is able to find the optimum tree stem bucking through DP to help companies over the bole tracing, therefore, characterizing itself as a tool that supports decision making. After the execution of the system, the optimum assortment is shown by sequentially detailing all products that should be removed from the analyzed bole as well as their respective volumes and revenue.


Silva Fennica ◽  
2020 ◽  
Vol 54 (5) ◽  
Author(s):  
Petteri Seppänen ◽  
Antti Mäkinen

The purpose of this study was to prepare a comprehensive, computerized teak ( L.f) plantation yield model system that can be used to describe the forest dynamics, predict growth and yield and support forest planning and decision-making. Extensive individual tree and permanent sample plot data were used to develop tree-level volume models, taper curve models and stand-level yield models for teak plantations in Panama. Tree volume models were satisfactorily validated against independent measurement data and other published models. Tree height as input parameter improved the stem volume model marginally. Stand level yield models produced comparable harvest volumes with models published in the literature. Stand level volume product outputs were found like actual harvests with an exception that the models marginally underestimate the share of logs in very large diameter classes. The kind of comprehensive model developed in this study and implemented in an easy to use software package provides a very powerful decision support tool. Optimal forest management regimes can be found by simulating different planting densities, thinning regimes and final harvest ages. Forest practitioners can apply growth and yield models in the appropriate stand level inventory data and perform long term harvest scheduling at property level or even at an entire timberland portfolio level. Harvest schedules can be optimized using the applicable financial parameters (silviculture costs, harvesting costs, wood prices and discount rates) and constraints (market size and operational capacity).Tectona grandis


Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 871 ◽  
Author(s):  
Qiu ◽  
Wang ◽  
Zou ◽  
Yang ◽  
Xie ◽  
...  

To estimate mangrove biomass at finer resolution, such as at an individual tree or clump level, there is a crucial need for elaborate management of mangrove forest in a local area. However, there are few studies estimating mangrove biomass at finer resolution partly due to the limitation of remote sensing data. Using WorldView-2 imagery, unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) data, and field survey datasets, we proposed a novel method for the estimation of mangrove aboveground biomass (AGB) at individual tree level, i.e., individual tree-based inference method. The performance of the individual tree-based inference method was compared with the grid-based random forest model method, which directly links the field samples with the UAV LiDAR metrics. We discussed the feasibility of the individual tree-based inference method and the influence of diameter at breast height (DBH) on individual segmentation accuracy. The results indicated that (1) The overall classification accuracy of six mangrove species at individual tree level was 86.08%. (2) The position and number matching accuracies of individual tree segmentation were 87.43% and 51.11%, respectively. The number matching accuracy of individual tree segmentation was relatively satisfying within 8 cm ≤ DBH ≤ 30 cm. (3) The individual tree-based inference method produced lower accuracy than the grid-based RF model method with R2 of 0.49 vs. 0.67 and RMSE of 48.42 Mg ha–1 vs. 38.95 Mg ha–1. However, the individual tree-based inference method can show more detail of spatial distribution of mangrove AGB. The resultant AGB maps of this method are more beneficial to the fine and differentiated management of mangrove forests.


Forests ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 114 ◽  
Author(s):  
Rafael Buchacher ◽  
Thomas Ledermann

Crown width is a functional trait that is commonly used to improve the estimation of above-ground biomass of forests and is often included as a predictor variable in forest growth models. Most of the existing crown width models reflect the relationship between crown width, tree size and competition variables, but do not consider the effect of species mixture. In this study, we developed crown width models for individual-tree of the major tree species growing in Austria. Because these models should be applicable for mixed and pure stands and should also take into account the characteristics of different sites, the relationship between crown width, site variables and species composition was investigated. For that purpose, we used data from a sub-sample of the Austrian National Forest Inventory, which comprises crown width measurements of about 8900 trees from 1508 sample plots. Because of the hierarchical structure of the data set (i.e., trees nested within the plot) which destroys the independencies between observations, linear mixed-effects models were used. The species composition of the stand was included via the species-specific relative proportions of basal area. To describe the interregional variability of crown width, dummy variables were introduced, which account for region-specific differences. Site characteristics were incorporated through the altitude, slope and aspect of the site. For Norway spruce, silver fir, Scots pine, European larch, European beech, oak species and ash/maple species it was possible to develop crown width models, which reflect the effects of site characteristics and species composition of the stand. The crown widths of shade-tolerant species reacted mainly positively to admixture, whereas light-demanding species reacted with decreasing crown widths. Coniferous species were not as strongly affected by mixture as broadleaf species.


2019 ◽  
Vol 49 (3) ◽  
pp. 228-236 ◽  
Author(s):  
Tomi Karjalainen ◽  
Lauri Korhonen ◽  
Petteri Packalen ◽  
Matti Maltamo

In this paper, we examine the transferability of airborne laser scanning (ALS) based models for individual-tree detection (ITD) from one ALS inventory area (A1) to two other areas (A2 and A3). All areas were located in eastern Finland less than 100 km from each other and were scanned using different ALS devices and parameters. The tree attributes of interest were diameter at breast height (Dbh), height (H), crown base height (Cbh), stem volume (V), and theoretical sawlog volume (Vlog) of Scots pine (Pinus sylvestris L.) with Dbh ≥ 16 cm. All trees were first segmented from the canopy height models, and various ALS metrics were derived for each segment. Then only the segments covering correctly detected pines were chosen for further inspection. The tree attributes were predicted using the k-nearest neighbor (k-NN) imputation. The results showed that the relative root mean square error (RMSE%) values increased for each attribute after the transfers. The RMSE% values were, for A1, A2, and A3, respectively: Dbh, 13.5%, 14.8%, and 18.1%; H, 3.2%, 5.9%, and 6.2%; Cbh, 13.3%, 15.3%, and 18.3%; V, 29.3%, 35.4%, and 39.1%; and Vlog, 38.2%, 54.4% and 51.8%. The observed values indicate that it may be possible to employ ALS-based tree-level k-NN models over different inventory areas without excessive reduction in accuracy, assuming that the tree species are known to be similar.


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