Forest Tree Mortality Simulation in Uneven-Aged Stands Using Connectionist Networks
نویسندگان
چکیده
We describe the application of neural networks adhering to the unsupervised learning paradigm to individual tree mortality prediction within forest growth modeling. The data set used for this study originates from permanent sample plots in uneven-aged Norway spruce (Picea abies L. Karst) stands in Austria. In addition we use the same data set and param-eterise a LOGIT model which represents the conventional statistical approach for predicting individual tree mortality. Finally, we evaluate the mortality predictions using an independent data set and compare the ndings with observed mortality rates. The encouraging results indicate that neural networks perform slightly better than the conventional LOGIT approach.
منابع مشابه
Evaluating of Different Height-Diameter Nonlinear Models for Hornbeam in Uneven-Aged Stands (Case Study: Golestan Rezaeian Forest)
Projection of stand development over time relies on accurate height-diameter functions. In this study, we evaluated the capability of 43 nonlinear models to estimate hornbeam heights in a portion Rezaeian experimental forest in Gorgan, Golestan province. We applied a systematic random sampling method to collect field data within a 150×200 meter network (3.33% intensity). It resulted in 200 circ...
متن کاملEstimating Long-Term Carbon Sequestration Patterns in Even- and Uneven-Aged Southern Pine Stands
Carbon (C) sequestration has become an increasingly important consideration for forest management in North America, and has particular potential in pine-dominated forests of the southern United States. Using existing literature on plantations and long-term studies of naturally regenerated loblolly (Pinus taeda) and shortleaf (Pinus echinata) pine-dominated stands on the Crossett Experimental Fo...
متن کاملA Survival Model for Shortleaf Pine Trees Growing in Uneven-aged Stands’
A survival model for shortleaf pine (Pinus echinata Mill.) trees growing in uneven-aged stands was developed using data from permanently established plots maintained by an industrial forestry company in western Arkansas. Parameters were fitted to a logistic regression model with a Bernoulli dependent variable in which ‘1” represented individual tree survival and “0” represented individual tree ...
متن کاملUsing Neural Networks to Predict Individual Tree Mortality
Within forest growth modeling it is customary to employ LOGIT models to predict individual tree mortality. In this paper we use Learning Vector Quantization and the self-organizing map as diierent formalisms to predict individual tree mortality. The data set for this study came from permanent sample plots in uneven-aged Norway spruce (Picea abies L. Karst) stands in Austria. After parameterizin...
متن کاملLong-Term Susceptibility of Even- and Uneven-Aged Northern Hardwood Stands to Partial Windthrow
While uneven-aged silviculture may appear preferable to even-aged silviculture in terms of stand susceptibility to windthrow (major wind damage), the scientific evidence is equivocal on this issue, because the two systems do not operate over the same time frame. The goal of this study was to evaluate the windthrow susceptibility of evenand uneven-aged stands over a 100-year period. Susceptibili...
متن کامل