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Original scientific paper

https://doi.org/10.31298/sl.143.7-8.4

Evaluation of forest road network planning in landslide sensitive areas by GIS-based multi-criteria decision making approaches in Ihsangazi watershed, Northern Turkey

Ender Bugday orcid id orcid.org/0000-0002-3054-1516 ; Çankin Karatekin University, Faculty of Forestry, Forest Engineering Department, Çankin, Turkey
Abdullah Emin Akay orcid id orcid.org/0000-0001-6558-9029 ; Bursa Technical University, Faculty of Forestry, Forest Engineering Department, Bursa, Turkey


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Abstract

Forest roads are one of the fundamental infrastructures in carrying out forestry activities and services. According to FAO, approximately 20 percent of the world’s forest lands are covered mountain forests. Since forests are generally located also in mountainous areas with steep slope in Turkey, difficulties experienced in these mountainous conditions render the provision of services difficult while increasing the costs. The aim of this study is to evaluate forest road planning alternatives which are to be developed in landslide sensitive mountainous areas based on the Landslide Susceptibility Mapping (LSM). For this purpose, a total of 12 models were generated with different multi-criteria decision making (MCDM) approaches including Modified Analytical Hierarchy Process (M-AHP), Fuzzy Inference System (FIS), and Logistic Regression (LR). As a result of the study, the best model was Model 3 obtained with LR approach (area under the curve (AUC)=76.6%) value followed by LR-Model 4 (AUC=75.7%) and FIS-Model 4 (AUC=73.4%). Model 3 (AUC=71%) was the most successful M-AHP approach. Consequently, the application of these methods will provide an advantage in making more accurate and more rational decisions during road network planning in landslide sensitive forest areas.

Keywords

landslide susceptibility; forest roads; modified-AHP; fuzzy inference system; logistic regression

Hrčak ID:

225323

URI

https://hrcak.srce.hr/225323

Publication date:

31.8.2019.

Article data in other languages: croatian

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