prilagođeno pretraživanje po punom tekstu

ŠUMARSKI LIST 7-8/2019 str. 39     <-- 39 -->        PDF

Evaluation of forest road network planning in landslide sensitive areas by GIS-based multi-criteria decision making approaches in Ihsangazi watershed, Northern Turkey
Planiranje mreže šumskih prometnica u područjima podložnim klizištima koristeći višekriterijski pristup odlučivanja temeljen na GIS-u u slivu Ihsangazi u Sjevernoj Turskoj
Ender Bugday, Abdullah Emin Akay
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.
Key words: Landslide susceptibility, forest roads, modified-AHP, fuzzy inference system, logistic regression
According to World Bank’s report (Dilley et al. 2005), Landslide has been occurred in an area of approximately in 3.5 million square km every year owing to increasing of population, climate change and the other factors. Besides, 820,000 km square areas have been determined to have the highest landslide risk, and 300 million people are under landslide risk, and also 60 million people live in high-risk