Estimating breast height diameter and volume from stump diameter for three economically important species in Turkey

Özçelık, Ramazan; Brooks, John R.; Diamantopoulou, Maria J.; Wiant, Harry V.

doi:10.1080/02827580903280053

Cited by 19 publications

(11 citation statements)

References 24 publications

(24 reference statements)

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“…Equivalence test looks for similarities while the usual hypothesis test looks for differences. The conclusion of no statistically significant difference of the usual statistical test means that the current evidence is not strong enough to support that the examined treatments lead to different outcomes (Robinson et al, 2005;Özçelik et al, 2010). That is different from saying that the two outcomes are the same.…”

Section: Equivalence Testingmentioning

confidence: 70%

Evaluation of different modeling approaches for total tree-height estimation in Mediterranean Region of Turkey

Diamantopoulou

Özçelık

2012

For. syst.

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Efficient management of timber resources and wood utilization practices require accurate and versatile information about important characteristics of forest resources for evaluating the numerous management and utilization alternatives for timber resources. Tree height is considered one of the most useful variables along with stocking and diameter at breast height, in estimating forest stand wood volumes and productivity. Six nonlinear growth functions were fitted to tree height-diameter data of three major tree species in Western Mediterranean Region's forests of Turkey. The generalized regression neural network (GRNN) technique has been applied for tree height prediction, as well, due to its ability to fit complex nonlinear models. The performance of the models was compared and evaluated. Further, equivalence tests of the selected models were conducted. Validation showed the appropriatness of all models to predict tree height. According to the model performance criteria, the six nonlinear growth functions were able to capture the height-diameter relationships and fitted the data almost equally well, while the constructed generalized regression neural network (GRNN) models were found to be superior to all nonlinear regression models, in terms of their predictive ability.

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Section: Equivalence Testingmentioning

confidence: 70%

Evaluation of different modeling approaches for total tree-height estimation in Mediterranean Region of Turkey

Diamantopoulou

Özçelık

2012

For. syst.

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“…Previous studies have shown that tree crown diameter (Cd) is well correlated with tree bole diameter (Kigomo, 1991;Gering and May, 1995;Kigomo, 1998;Lockhart et al, 2005;Hemery et al, 2005). In the same vein, stump diameter (Dst) is highly correlated with diameter at breast height (Dbh), and as such have being used in place of Dbh to predict most tree growth variable especially in the case of illegal logging (Osho, 1983;Westfall, 2010;Özçelík et al, 2010;Shamaki and Akindele, 2013).…”

Section: Introductionmentioning

confidence: 99%

Crown-Stump Diameter Model for Parkia biglobosa Benth. Species in Makurdi, Benue State, Nigeria

Chukwu

Dau

Ezenwenyi

2017

JTFE

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The crown of tree is the centre of physiological activity which gives an indication of the potential photosynthetic capacity on a tree. Though, its measurement remains a challenge in forest inventory task. The ability to predict crown diameter from stump diameter provides an effective technique of obtaining its estimate. This helps in detecting the excessive tree felling than actual requirements and wildlife suitability.The main objective of this study was to develop and test crown diameter prediction models for silvicultural management of naturally grown Parkia biglobosa within the University of Agriculture, Makurdi. Nine 100 m x 100 m temporary sample plots were established using simple random sampling method. Crown diameter and stump diameter were measured in all living P. biglobosa trees with stump diameter ≥10.0 cm. Least square method was used to convert the counted stumps into harvested crown dimension. Three linear and three non-linear models using stump diameter as the exploratory variable were developed and evaluated using the adjusted coefficient of determination (Adj.R 2 ), standard error of estimate (SEE), prediction error sum of squares (PRESS) and Akaike information criterion (AIC). The crown-stump diameter relationship was best described by the double logarithmic function with . 2 = 65.1%, = 0.1729, = 262.9998 = 717.56.The result showed that Crown diameter estimation was feasible even when the only information available is stump diameter.The resulting equation was tested for validation with independent data obtained from additional plots and was found to be desirable for estimating the crown diameter for Parkia biglobosa in Makurdi,

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“…Estimating DBH of trees from stump dimension may help to reconstruct silvicultural practices and to assess harvested timber and wood, when pre-operation data are not available. Pre-operation data are surely not available in case of illegal cuttings, and estimating DBH is the only way to assess the loss, through a two-step procedure (Corral-Rivas et al 2007, Özçelík et al 2010, unless volume functions based on stump information are available. Another application of diameter prediction occurs when a harvest crosses ownership boundary (Chhetri et al 1996, Pond andFroese 2014).…”

Section: Introductionmentioning

confidence: 99%

Predicting Diameter at Breast Height from Stump Measurements of Removed Trees to Estimate Cuttings, Illegal Loggings and Natural Disturbances

Cosmo

Gasparini

2020

SEEFOR

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Predicting diameter at breast height (DBH) of trees from stump information may be necessary to reconstruct silvicultural practices, to assess harvested timber and wood, or to estimate forest products’ losses caused by illegal cuttings or natural disasters (disturbances). A model to predict DBH of felled trees was developed by the first Italian National Forest Inventory in 1985 (IFNI85). The model distinguished between the two broad groups of conifers and broadleaves and used stump diameter as the sole quantitative variable. Using an original dataset containing data from about 1200 trees of sixteen species recorded throughout Italy, we assessed the performance of that model. To improve the prediction of the DBH of removed trees over large areas and for multiple species, we developed new models using the same dataset. Performance of the new models was tested through indices computed on cross-validated data obtained through the leave-one-out method. A new model that performs better than the old one was finally selected. Compared to the old NFI model, the selected model improved DBH prediction for fourteen species up to 31.28%. This study proved that species specification and stump height are variables needed to improve the models’ performance and suggested that data collection should be continued to get enhanced models, accurate for different ecological and stand conditions.

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Estimating breast height diameter and volume from stump diameter for three economically important species in Turkey

Cited by 19 publications

References 24 publications

Evaluation of different modeling approaches for total tree-height estimation in Mediterranean Region of Turkey

Evaluation of different modeling approaches for total tree-height estimation in Mediterranean Region of Turkey

Crown-Stump Diameter Model for Parkia biglobosa Benth. Species in Makurdi, Benue State, Nigeria

Predicting Diameter at Breast Height from Stump Measurements of Removed Trees to Estimate Cuttings, Illegal Loggings and Natural Disturbances

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