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ŠUMARSKI LIST 3-4/2022 str. 44     <-- 44 -->        PDF

avalanches, landslides, and areas with high erosion sensitivity. They should prevent the filling of dams, lakes and river beds, and its adverse effect on the environmental health of settlements (GDF 1984). Forest road construction falls under the category of construction works that can harm the environment (Boston, 2016); harm that is mostly the result of defective planning (Gumus et al. 2008; Bugday 2018).
In order to prevent further damage to protection forests in areas with topographical and spatial challenges (Hayati et al. 2012; Akay et al. 2014), it is important to carefully plan and implement those plans in a manner that minimizes the destructive environmental effects of forest road construction.
Geographic Information Systems (GIS) software has proved advantageous in decision-making and planning processes (Phua and Minowa 2005). Multicriteria analysis, which informs GIS-based decisions in spatial and temporal contexts for both national and international studies, can be highly accurate and time-efficient by leveraging computers (Tan et al. 2021), and various modeling approaches can be used to generate GIS-based LSMs. Some of these approaches include: Fuzzy Logic (Stanley and Kirschbaum, 2017), Support Vector Machine (Kavzoglu et al. 2015), Frequency Ratio (Yilmaz and Keskin 2009), Logistic Regression (Zhou et al. 2021), Weights of Evidence (Pradhan et al. 2010), Adaptive Neuro-Fuzzy Inference System (Bui et al. 2012), Decision Tree (Arabameri et al. 2021), Machine Learning (Kavzoglu et al. 2019), Analytic Hierarchy Process (Laschi et al. 2016; Kadi et al. 2019) Artificial Neural Network (Jesudasan and Saravanan 2021). In addition, although there is no settled understanding in LSM modeling studies, generally aspect (Yan et al. 2019), slope (Sun et al. 2020), elevation (Du et al. 2017), curvature (Wang et al. 2020), distance to fault (Demir 2018) - road (Tang et al. 2021) - stream (Kalantar et al. 2018), land-use (Nohani et al. 2019), lithology (Paryani et al. 2020), NDVI (Pourghasemi et al. 2020), Stream Power Index (SPI) (Hong et al. 2018), Topographic Position Index (TPI) (Xie et al. 2021), and Topographic Wetness Index (TWI) (Gheshlaghi et al. 2021) etc. factors are widely used.
Forest roads include not only the basic facilities but also the structures required for the execution of forestry activities (Demir 2007). Forest roads should be well designed (Akay et al. 2019), because they can negatively affect underground (Haskell, 2000) and aboveground (Fallahchai et al. 2018) elements. As such, it is vital, both in terms of ecological and nature-friendly engineering, that plans for roads in protection forests with high landslide susceptibility and topographically negative features are detailed and provide alternatives in order to ensure roads are built in line with their purpose.
The aim of this study is to generate LSMs that can be used during planning phases as the basis for the determination of forest road routes in protection forests and establish a