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

Abstract

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.

Development of ecoregion-based height–diameter models for 3 economically important tree species of southern Turkey

“…As indicated by Diamantopoulou and Özçelik (2012), knowledge of tree heights, such as total height, is fundamental for developing growth and yield models in forest stands. Precise tree height estimations are needed because height is an important variable in volume estimation and biomass calculation.…”

“…The 7 candidate models were selected from previous studies based on their appropriate mathematical features, possible biological interpretation of parameters, and satisfactory prediction for tree h-d relationship in the literature (Fang and Bailey, 1998;Huang et al, 2000;Peng et al, 2001;Yuancai and Parresol, 2001;Diamantopoulou and Özçelik, 2012). These models include the most flexible equations for h-d relationships (Zhang, 1997;Peng et al, 2001), the Bertalanffy-Richards (Bertalanffy, 1949;Richards, 1959), Weibull (Yang et al, 1978), and Schnute (Schnute, 1981) models:…”

Comparison of different non-linear models for prediction of the relationship between diameter and height of velvet maple trees in natural forests (Case study: Asalem Forests, Iran)

“…Tree height is fundamental for developing growth and yield models in forest stands and is also an important variable in volume estimation and biomass calculation (Diamantopoulou, Özçelik 2012). The development of simple and accurate height diameter models enables forest managers to make the reliable prediction of tree height in forests (Calama, Montero 2004).…”

“…For model validation, the k-fold cross validation method with k = 10 has been used. The k taking the value 10 has been the most common practice (Olson, Delen 2008;Diamantopoulou, Özçelik 2012). In this method the data is randomly partitioned into k equal subsamples, one of which is considered as the validation data for evaluating the model, and the other subsamples (k -1) are used for training.…”

HEIGHT-DIAMETER RELATIONSHIPS FOR Araucaria angustifolia (BERTOL.) KUNTZE IN SOUTHERN BRAZIL

“…Besides, the need to use distances and angles (CRECENTE-CAMPO et al, 2010) makes measuring individual trees much prone error, especially in forests with dense understories. A common solution used in forest inventories is to measure a subsample (DIAMANTOPOULOU; ÖZÇELIK, 2012) or no individual tree heights at all (ADAME et al, 2008), and use height-diameter (h-d) relationship models to estimate heights (TEWARI; KISHAN KUMAR, 2002;SHARMA;PARTON, 2007;BUDHATHOKI et al, 2008). The h-d models are usually asymptotic equations of growth models that explain height variation through diameter measurements.…”