The
effective management of forest resources is very important for the future of
the forest and to meet both ecological and economic needs. In this study, it is
aimed to contribute to the applicability of modeling in practice by identifying
regions that may be landslide in forest areas via different modeling
approaches. A total of six models were created by using four criteria
(elevation, slope, aspect and stream power index) and using Fuzzy Inference
System (FIS) and Modified-Analytic Hierarchy Process (M-AHP) approaches in this
study. The model’s performance was measured using the Receiver Operating
Characteristic (ROC) curve and Area Under Curve (AUC). According to the results
of study, the most successful model was determined as FIS Model 1 with the AUC
value of 82.1% and M-AHP Model 1 with the AUC value of 80.9%. This study
provides important outputs that indicates the potential benefits of using
landslide susceptibility mapping in the fields of forest harvesting, road
network planning and forest management.
Primary Language | English |
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Subjects | Engineering |
Journal Section | Research Articles |
Authors | |
Publication Date | December 21, 2019 |
Published in Issue | Year 2019 |
The works published in European Journal of Forest Engineering (EJFE) are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.