Aim of study: To develop and evaluate the forest’s wind-risk model, dedicated for stand damage level.Area of study: Model was tested in the northeastern Poland.Material and methods: A risk model referring to the damage of forest stands by wind specifies, for every stand in a selected forest district, the risk factor within the range of 0 to 3. The higher value of the factor, the greater risk of damage, if wind occurs. The model was based on 11 features: average size of a tree stand, mean diameter breast high in the specified features’ ratio, species composition, degree of stand density, age of stand, forest site type, amount of damage caused by wind in the last 10-year period, location of forest district in the region of Poland, and three f...
This paper tested the ability of machine learning techniques, namely artificial neural networks and ...
This paper tested the ability of machine learning techniques, namely artificial neural networks and ...
This paper tested the ability of machine learning techniques, namely artificial neural networks and ...
Aim of study: To develop and evaluate the forest’s wind-risk model, dedicated for stand damage level...
Aim of study: To develop and evaluate the forest’s wind-risk model, dedicated for stand damage level...
In June 2016, a hurricane damaged the forests of the Regional Directorate of the State Forests in Bi...
On August 11−12, 2017, a hurricane passed from south to north of Poland causing considerable damage ...
The study presents a risk model for stand damage caused by wind. It is associated with the following...
A dynamic process of mortality of Norway spruce stands in south−west Poland, mainly in the Sudety Mt...
Predicting the probability of wind damage in both natural and managed forests is important for under...
AbstractPredicting the probability of wind damage in both natural and managed forests is important f...
Maritime pine (Pinus pinaster Ait.) forests in the Aquitaine region, south-west France, suffered cata...
Maritime pine (Pinus pinaster Ait.) forests in the Aquitaine region, south-west France, suffered cata...
International audienceAbstract• ContextAmong natural disturbances, wind storms cause the greatest da...
Since the December 1999 storms, which caused extensive damage in Western Europe, the need for better...
This paper tested the ability of machine learning techniques, namely artificial neural networks and ...
This paper tested the ability of machine learning techniques, namely artificial neural networks and ...
This paper tested the ability of machine learning techniques, namely artificial neural networks and ...
Aim of study: To develop and evaluate the forest’s wind-risk model, dedicated for stand damage level...
Aim of study: To develop and evaluate the forest’s wind-risk model, dedicated for stand damage level...
In June 2016, a hurricane damaged the forests of the Regional Directorate of the State Forests in Bi...
On August 11−12, 2017, a hurricane passed from south to north of Poland causing considerable damage ...
The study presents a risk model for stand damage caused by wind. It is associated with the following...
A dynamic process of mortality of Norway spruce stands in south−west Poland, mainly in the Sudety Mt...
Predicting the probability of wind damage in both natural and managed forests is important for under...
AbstractPredicting the probability of wind damage in both natural and managed forests is important f...
Maritime pine (Pinus pinaster Ait.) forests in the Aquitaine region, south-west France, suffered cata...
Maritime pine (Pinus pinaster Ait.) forests in the Aquitaine region, south-west France, suffered cata...
International audienceAbstract• ContextAmong natural disturbances, wind storms cause the greatest da...
Since the December 1999 storms, which caused extensive damage in Western Europe, the need for better...
This paper tested the ability of machine learning techniques, namely artificial neural networks and ...
This paper tested the ability of machine learning techniques, namely artificial neural networks and ...
This paper tested the ability of machine learning techniques, namely artificial neural networks and ...