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Paper Information

Journal:   IRANIAN JOURNAL OF FOREST AND POPLAR RESEARCH   2015 , Volume 23 , Number 3; Page(s) 573 To 582.
 
Paper: 

EVALUATION OF SLOPE FAILURE POTENTIAL IN FOREST ROADS (CASE STUDY: 46TH WATERSHED, NORTH OF IRAN)

 
 
Author(s):  AZIZI Z.*, HOSSEINI A.
 
* FACULTY OF NATURAL RESOURCES AND EARTH SCIENCE, SHAHREKORD UNIVERSITY, SHAHREKORD, IRAN
 
Abstract: 

Forest road networks are the essential bases of modern and sustainable production within Hyrcanian forests of Iran. In most mountainous areas, the slope failures are often caused by the construction of forest road on steep terrains. Therefore, it is crucial to locate forest roads on stable slopes. It should be additionally noted that high-structured forest roads constructed on steep terrain often end up with failure during cut and fill operations. In this study, a model was developed using the Artificial Neural Network to evaluate potential failure of cut and fill in forest. Probability of slope failure was classified in four categories, including no, low, medium and high slope failures. The overall result showed that low slope failure category (with a probability of 39.8%) has high occurrences, whereas high slope failure category (with probability of 13.3%) was associated with fewer occurrences. As modelled by ANN, lowest and highest accuracies for classified slope failure were 92.6% (in no slope failure category) and 78.6% (in medium slope failure category) respectively. Based on importance indices, gradient of trench, natural slope of area and the height of the trench were associated with the greatest influences on the slope failure, while the soil type and number of trees turned out to be of least effect on the slope failure occurrence.

 
Keyword(s): FOREST ROAD, SLOPE FAILURE, ARTIFICIAL NEURAL NETWORK
 
References: 
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