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http://dx.doi.org/10.14578/jkfs.2016.105.4.429

Assessment of Slope Failures Potential in Forest Roads using a Logistic Regression Model  

Baek, Seung-An (Forest Practice Research Center, National Institute of Forest Science)
Cho, Koo-Hyun (Forest Practice Research Center, National Institute of Forest Science)
Hwang, Jin-Sung (Forest Practice Research Center, National Institute of Forest Science)
Jung, Do-Hyun (Forest Practice Research Center, National Institute of Forest Science)
Park, Jin-Woo (Division of Forest Science, Kangwon National University)
Choi, Byoungkoo (Division of Forest Science, Kangwon National University)
Cha, Du-Song (Division of Forest Science, Kangwon National University)
Publication Information
Journal of Korean Society of Forest Science / v.105, no.4, 2016 , pp. 429-434 More about this Journal
Abstract
Slope failures in forest roads often result in social and economic loss as well as environmental damage. This study was carried out to assess susceptibility of slope failures of forest roads in Hongcheon-gun, Gangwon-do where many slope failures occurred after heavy rainfall in 2013 using GIS and logistic regression analysis. The results showed that sandy soil (6.616) in soil texture type had the highest susceptibility to slope failures while medium class (-3.282) in tree diameter showed the lowest susceptibility. A error matrix for both slope failure and non-slope failure area was made and a model was developed showing a classification accuracy of 74.6%. Non-slope failures area in the forest roads were classified mostly in the range of >0.7 which was higher values than the classification criteria (0.5) used by the logistic regression model. It is suggested that considering forest environment and site factors related to forest road failures would improve the accuracy in predicting susceptibility of slope failures.
Keywords
forest road; logistic regression model; GIS; slope failure;
Citations & Related Records
Times Cited By KSCI : 11  (Citation Analysis)
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