Calibrating fixed- and mixed-effects taper equations

Accurate and affordable measurements of upper-stem diameters are now possible thanks to recent advances in laser technology. Measurement of the midpoint upper-stem diameter can be employed to improve the accuracy of diameter predictions along the tree bole. Felled-tree data from a loblolly pine (Pinus taeda L.) plantation was used to evaluate two approaches: (1) calibrating a segmented taper equation by constraining a parameter, and (2) localizing the taper model by predicting the random effects for each tree. The calibration technique is much simpler and produced less-biased prediction of diameters and is therefore recommended. Calibration results were similar for both fixed- and mixed-effects taper models, even though a slight gain in accuracy and precision was attained with the mixed-effects model.     

A flexible regression model for diameter prediction

We present a functional regression model for diameter prediction. Usually stem form is estimated from a regression model using dbh and height of the sample tree as predictor. With our model additional diameter observations measured at arbitrary locations within the sample tree can be incorporated in the estimation in order to calibrate a standard prediction based on dbh and height. For this purpose, the stem form of a sample tree is modelled as a smooth random function. The observed diameters are assumed as independent realizations from a sample of possible trajectories of the stem contour. The population average of the stem form within a given dbh and height class is estimated with the taper curves applied in the national forest inventory in Germany. Tree deviation from the population average is modelled with the help of a Karhunen–Loève expansion for the random part of the trajectory. Eigenfunctions and scores of the Karhunen–Loève expansion are estimated through conditional expectations within the methodological framework of functional principal component analysis (FPCA). In addition to a calibrated estimation of the stem form, FPCA provides asymptotic pointwise or simultaneous confidence intervals for the calibrated diameter predictions. For the application of functional principal component analysis modelling the covariance function of the random process is crucial. The main features of the functional regression model are discussed informally and demonstrated by means of practical examples.     

COMPATIBLE STEM TAPER AND VOLUME RATIO EQUATION FOR KOREAN PINE

INTRODUCTIONWiththedevelopl11entofecono111yandoPeninghn1berInarket.thehlnbersizeiscaredaboutmorea11dl11ol'e.otl1ermse,l11uIhpleproductinventonesrequlresaccurateeshmatesofproductsizes(dial11eteral1dlengths)andvolume.Koreanpine(PinIisko1nIensisSib.etZucc.)isararehn1bersPeciesil1Heilol1roial1gProvince.ItisnecessarynotonlytopredicttI1evolumebasedonvolumetablebutalsotoas-sesstheassotheent.Accordingtothenahol1alhmbercritenonandthewoodqt1ality,thestandqualityisdetenl1i11ed.ThemainPOintofco…     

Long-term effects of superphosphate fertilization on stem form, taper and stem volume estimation of Pinus radiata

The long term effects of superphosphate fertilization on stem form, taper and stem volume estimation of Pinus radiata on a phosphorus-deficient site was examined using data from a fertilizer experiment which had been maintained for 30 years. The application of superphosphate resulted in long term and statistically significant changes in stem form. Mean cylindrical form factor ranged from 0.33 for the control trees up to 0.40 for trees fertilized with 100 kg P ha⁻¹. Stem form was also examined through taper curves which provided detailed depiction of average relative stem profiles. The increase in cylindrical form factor of fertilized trees was largely attributed to a significantly broader profile of the lower third of the stem. In comparison with the control trees, the fertilized trees also had a broader, although not statistically significant, profile of upper and middle stem which could also contribute to the increase in their cylindrical form factor. With increased form factor a greater proportion of the stem became merchantable because of increased log length to tree height ratio. Mean average taper of trees did not show a consistent trend with increasing lelevels of superphosphate application. It largely reflected the differential response of DBH and height growth to the treatments. The volume equation based on control trees underestimated the underbark stem volume of fertilized trees by 5–12% on average. Developing separate volume equations for the fertilized trees is warranted.     

基于距离相关系数和KNN回归模型的森林蓄积量估测研究

【目的】探究Landsat8 OLI数据和KNN算法在森林蓄积量估测中的潜力。【方法】以湖南省湘潭县为研究区,采用Landsat8 OLI数据和同时期的二类调查数据,通过距离相关系数筛选特征,分别采用线性回归模型(MLR)、K-近邻模型(KNN)、距离加权KNN模型(DW-KNN)和优化欧式KNN模型(FW-KNN)对森林蓄积量进行估测。使用十折交叉方法进行精度检验,对检验结果进行对比分析。【结果】3种KNN模型的估测结果均高于传统的线性模型,并且在3种KNN模型中,FW-KNN算法效果最好,决定系数达到0.69,为3种模型中最高;3种KNN模型中,本研究优化欧氏距离KNN模型的估测精度最高,其均方根误差为30.3%,相比于传统KNN模型的均方根误差降低了5.1%,相比于DW-KNN模型降低了3.3%。【结论】采用DW-KNN蓄积量估测结果明显优于其他两种模型,说明通过特征与蓄积量的相关性优化样本间的距离是一种可行的KNN优化方法。     

Compatible stem volume and taper equations for Brutian pine, Cedar of Lebanon, and Cilicica fir in Turkey

Compatible segmented taper and volume functions were developed for Brutian pine, Cedar of Lebanon, and Cilicica fir in Turkey. The proposed models generally performed better for the whole tree, especially for Cilicica fir. Average diameter prediction error was less than 2.2 cm and average volume error was less than 0.009 m³. The proposed models provide needed merchantable stem volume and diameter estimates to any point in the bole based on the 10 relative height classes examined for the three species. Model estimates compared well to existing volume tables currently employed for these three important commercial species.     

A simple stem taper model with mixed effects for boreal black spruce

We simplified Kozak’s taper model by setting the inflection point at 1.3 m (dbh) without losing accuracy and precision. The simplification was required to facilitate the estimation of the covariance parameters when using a mixed-effects method. This method was necessary to take into account the correlation among multiple diameter measurements on an individual stem. The simple stem taper model was fitted to an extended data set collected across the province of Quebec, Canada. Comparison of the predicted stem taper and the derived stem volume with those obtained using existing models showed a comparable predictive power for the simple model. Including a prediction of the tree random effects based on supplementary diameter measurements of the bole improves the predictive ability of the model around the extra diameter observation. This model offers welcome simplicity as a means of predicting tree taper at coarse resolution for planning tree harvesting.     

利用计算机进行刀切法估算树干材积的实践

利用落叶松实际调查材料 ,阐述了刀切法估计树干材积的过程 ,认为刀切法估计树干材积是可行的 ,并得出了比一元材积表计算材积精度高 13%的满意结果     

Comparison of model forms for estimating stem taper and volume in the primary conifer species of the North American Acadian Region

? The performance of ten commonly used taper equations for predicting both stem form and volume in balsam fir [Abies balsamea (L.) Mill], red spruce[Picea rubens (Sarg.)], and white pine[Pinus strobus (L.)] in the Acadian Region of North America was investigated.

? Results show that the Kozak (2004) and Bi (2000) equations were superior to the other equations in predicting diameter inside bark for red spruce and white pine, while the Valentine and Gregoire (2001) equation performed slightly better for balsam fir.

? For stem volume, the Clark et al. (1991) equation provided the best predictions across all species when upper stem diameter measurements were available, while the Kozak (2004) and compatible taper equation of Fang et al. (2000) performed well when those measurements were unavailable.

? The incorporation of crown variables substantially improved stem volume predictions (mean absolute bias reduction of 7–15%; root mean square error reduction of 10–15%) for all three species, but had little impact on stem form predictions.

? The best taper equation reduced the predicted root mean square error by 16, 39, and 45% compared to estimates from the widely used Honer (1965) regional stem volume equations for balsam fir, red spruce, and white pine, respectively.

? When multiple taper equations exist for a certain species, the use of the geometric mean of all predictions is an attractive alternative to selecting the “best” equation.

     

基于气象因子深度学习的森林火灾预测方法

森林火灾一旦发生将对生态系统造成严重的破坏,间接导致气候的变化和极端天气频发。对森林火灾的发生进行准确预测可提前采取有效的防控措施,具有重要意义。传统林火预测模型多为数学方法和浅层神经网络,当数据量增大时易出现建模困难以及预测精度降低等问题。深度学习模型在处理大量非线性数据上具有一定的优势,其模型具有多层网络结构,通过训练大量数据可提取出具有代表性的特征值,发现数据间的隐含关系,达到准确分类预测的目的。因此,本研究提出一种基于深度学习的林火预测方法,将深度信念网络(deep belief network,DBN)作为预测模型,气象因子作为输入数据,以解决传统林火预测模型在面对大量数据时预测效果不佳的问题;同时结合过采样SMOTE(synthetic minority oversampling technique)算法,平衡林火数据集和增加训练数据量,提升了森林火灾的预测准确度。结果表明,在面对更大的数据量时,该模型预测精度明显优于其他传统林火预测模型,证明了将深度学习应用在林火预测的优越性。该研究可为深度学习在林业领域的应用提供参考。     

Compatible volume and taper models for economically important tree species of Turkey

• Introduction  

The accurate estimation of stem taper and volume are crucial for the efficient management of the forest resources. Compatible segmented polynomial taper and volume equations were developed for Brutian pine (Pinus brutia Ten.), Lebanon cedar (Cedrus libani A. Rich.), Cilicica fir (Abies cilicica Carr.), Scots pine (Pinus sylvestris L.), and Black pine (Pinus nigra Arnold.).     

A new taper index based on form-factor: application to three bamboo species (Phyllostachys spp.)

European Journal of Forest Research - The form-factor for the stem surface area is directly proportional to the square root of the form-factor for the stem volume, i.e., the square root law of the...     

A flexible modeling of irregular diameter structure for the volume estimation of forest stands

Simple distribution models (SDMs) have deficiencies in portraying irregular forest diameter structure. This paper introduces mixture distribution models (MDMs) to improve the estimation accuracy of stand volume of Siberian larch (Larix sibirica Ledeb.) forests. Stand volume was estimated by combining the suitable diameter mixture model and diameter–height model. Appropriate mixture models are derived by integrating multiple SDMs of Burr III and XII, Johnson S_B, Weibull or lognormal probability density functions (pdf) that satisfied the criteria of goodness of fit tests. Results showed that the average bias of volume estimation for all of the study plots using SDM and MDM approaches are underestimated by 6.93 and 2.42 m³, respectively. Each of the estimates is equivalent to an estimation error of 25.59 ± 18.18 and 7.08 ± 2.97 %. This suggests that the MDM approach is a more flexible and suitable modeling technique for forest volume estimation, in particular for forests that have been frequently disturbed by natural events.     

基于改进ResNet-UNet的立木图像分割方法

[目的]针对现有图像处理方法分割立木精度低的问题,提出一种基于改进ResNet-UNet的立木图像分割方法,实现对图像中立木的精确分割.[方法]将拍摄得到的立木图像输入ResNet-UNet深度学习融合网络模型,初步得到较精确的立木分割图;结合自制的后期处理方法对该分割图进行优化处理,准确分割出立木形状.ResNet-...     

A model for the relationship between form-factors for stem volume and those for stem surface area in coniferous species

A model that describes the relationship between the form-factors for stem volume and those for stem surface area in coniferous species is proposed. The model is derived assuming that the stem form of a tree can be expressed by Kunze's equation. The model indicated that the form-factor for stem surface area was directly proportional to the square root of the form-factor for stem surface volume, independent of the stem position. The proposed model expressed the relationship of the form-factors for Japanese cedar (Cryptomeria japonica D. Don) and Japanese cypress (Chamaecyparis obtusa Endl.) trees well. Therefore, the form-factors for stem surface area could be estimated from those for stem volume. No significant difference in the coefficient was found between Japanese cedar and Japanese cypress trees, indicating that the proportional coefficient would be common between the two species. Many studies have shown that the form-factors for stem volume at 0.7 and 0.5 in relative height were, respectively, almost steady at 0.7 and 1.0, independent of species, district, density control, and growth stage. Substituting these universal values into the proposed model, the form-factors for stem surface area at 0.7 and 0.5 in relative height were estimated to be 0.730 and 0.873, respectively. The estimated values of the form-factors for stem surface area would be universal for coniferous species. The proposed model also showed that the breast height form-factor for stem surface area decreased sharply with the increase in total tree height, when the height was less than 10 m. However, after the tree attained the total height of 10 m, the breast height form-factor gradually decreased with the total tree height approaching its asymptotic value of 0.605. In conclusion, the model proposed here can be used to describe the relationship between form-factors for stem volume and those for stem surface area successfully.     

Modeling dominant height growth based on nonlinear mixed-effects model: a clonal Eucalyptus plantation case study

Eucalyptus is the most valuable cultivated forest genus in Brazil nowadays. Modeling eucalypts growth has been a challenge for foresters in recent years due to the strong site and genetic variations, management regimes and multiple products generated from those plantations. Because the forest height growth is directly related with the site characteristics and with forest productivity, the improvement on the height growth representation implies in better productivity estimation. A nonlinear mixed-effects model was developed to represent the height growth pattern of eucalypts clonal stands from the Brazilian coastal region. Likewise in other scientific fields, this type of modeling methodology showed to be flexible, precise and accurate, generating multimorphic growth curves for different sites and clones.     

Representation of tree stem taper curves and their dynamic, using a linear model and the centroaffine transformation

One main task of forestry is a reliable estimation of the stem form and its development applied in calculating total and log volume. As long as process-oriented models are not available for this practical use, empirical models must serve instead. Taper curve data of trees within stands normally show a rank maintenance,i.e., a tree which has a greater diameter than another one at a certain height, is most probably bigger at any other height, too. This property also applies to the analysed tree species, sugi (Cryptomeria japonica) and hinoki (Chamaecyparis obtusa), and will be well-represented by a linear model formulation. As model parameter sets of single stands have a very limited time validity, two approaches for future stem form prediction are discussed. The one, the centroaffine transformation of a linear taper curve function, is not suitable for representing the time-depending change of the stem form. However, this can be done by a linear unit taper curve model, the parameters of which are based on sample trees of stands of several age classes. Temporary unit parameter sets are derived for sugi and hinoki and the estimated stand volumes are compared to the real ones to evaluate the model performance, which turned out to be very good. We would like to express our gratitude to the Japan Science and Technology Corporation for the financial promotion, which enabled this research work.     

A method for estimating tree composition and volume using harvester data

This research article introduces a method that can be used to estimate tree composition and volume of arbitrary subdivisions of a logged stand. The method uses spatial data that is generated with a harvester to simulate individual tree locations. The simulation uses two probability density functions: the distance and the angle from the harvester at which the tree is cut. The average estimated volume root mean squared error varied from 4% for 0.4 ha subregions to 29% for 0.03 ha subregions. The stand subdivision method affected the accuracy of volume estimation only in the smallest subregions. Compared with the use of harvester data as such, i.e. without tree location simulation, the improvement in total and species-wise volume estimates varied between 5 and 35%. The data produced by the method can be used as a field data source for remote sensing methods as well as a verification data set for field inventories. However, a question remains over the generality of the model parameters used.     

Modeling stem profile of Lebanon cedar,Brutian pine,and Cilicica fir in Southern Turkey using nonlinear mixed-effects models

The Max and Burkhart segmented taper model was fitted using nonlinear mixed-effects modeling techniques to account for within- and between-individual stem profile variation for Lebanon cedar (Cedrus libani A. Rich.), brutian pine (Pinus brutia Ten.), and cilicica fir (Abies cilicica Carr.) in Turkey. About 75% of the trees were randomly selected for model development, with the remainder used for model validation. Diameter measurements from various heights were evaluated for tree-specific calibrations by predicting random-effects parameters using an approximate Bayesian estimator. The procedure was tested with a validation dataset. Predictive accuracy of the model was improved by including random-effects parameters for a new tree based on upper stem diameter measurements. Prediction in stem diameter was less biased and more precise across the all sections of bole when compared to predictions based only on fixed-effects parameters. In the future, the proposed mixed models can be applied to region wide three species stands by fitting the model to a larger data set that more closely represents regional variation.     

Autologistic regression and multicriteria evaluation models for the prediction of forest expansion

Land use changes are complex ecological processes driven by the interaction of biophysical and human related factors. The prediction of forest land use changes is important for sustainable forest management and biodiversity conservation. This study investigates the modelling process of the spatial dynamics of a forest ecosystem in north eastern Greece. For the prediction of forest expansion, based on land use data of the study area, a deterministic approach using logistic regression and heuristic methods of multi-criteria evaluation is adopted. The set of factors driving forest expansion are: the slope, the distance to roads, the distance to urban areas, the distance to forest, the soil depth, the soil erosion and the influence from the land uses of the neighbourhood. The spatial autocorrelation of driving factors is addressed using an autologistic regression model. The multicriteria evaluation approach is developed using weighted linear combination (WLC) and ordered weighted averaging (OWA) methods. In WLC method the relative importance of each factor was estimated using the analytical hierarchy process. In the OWA method, decision strategies are generated using a selection of relative linguistic quantifiers, which allow different Risk in decisions. The accuracy of the models produced was tested with real data for the year 2001 using the ROC validation method. All the methods produced satisfactory results. Autologistic regression showed slightly better performance than multicriteria evaluation methods due to higher degree of objectivity in defining the importance of driving factors for forest expansion.