prilagođeno pretraživanje po punom tekstu

ŠUMARSKI LIST 7-8/2019 str. 41     <-- 41 -->        PDF

area is covered with forests. The most of the roads within the watershed are forest roads and there is a total of 321.4 km of roads as of the end of 2017. Forest roads are defined as B-type low volume roads with 6 m platform width.
Landslide Factors – Čimbenici razorenja
                Nine factors; elevation, slope, aspect, lithology, distance to faults, distance to streams, distance to roads, TWI, and SPI; were evaluated in developing models for LSM. The elevation is a negative factor in forest road planning since the cost of road construction increases as the elevation increases in the mountainous area. Elevation also negatively effects the periodic maintenance works. The slope is another important factor that directly affects the costs in forest road construction (Akay 2006; Akay et al. 2008; Hong et al. 2015). In this study, IUFRO (International Union of Forest Research Organizations) slope classes were utilized as in five different grades 0-5.71, 5.71-13.80, 13.80-21.88, 21.88-31.99 and > 32 degrees (Erdaş 2008). Aspect is also one of the topographical factors affects soil properties and thereby the growing habitat (Dehnavi et al. 2015). Aspect has been examined according to eight different directions in this study. Lithology is a factor which affects the cost of construction of forest roads as it reveals the bedrock characteristics (Conforti et al. 2014). The lithology was evaluated in six groups in this study. Distance to faults is one of the factors have a significant role in triggering the landslides (Vahidnia et al. 2010). In this study, distance to faults analysis was made by expressing 1 km zones. Distance to the streams is also one of the factors utilized commonly in LSM studies when the proximity relation is significant (Pourghasemi et al. 2014; Aghdam et al. 2016; Wang et al. 2016). The distances to the streams are expressed as zones with interval distance of 100 m in this study. One of the significant factors triggering the landslide is the distance to roads (Yalçın 2008). They have been expressed as zones with interval distance of 100, 300, 500, and 1000 m. TWI is utilized widely in order to determine the location and size of water-saturated areas at the topographic level (Moore et al. 1991; Goetz et al. 2015) (Equation 1):
As                  = Specific basin area (m2)/ Specifično područje bazena
b            = Incline of slope / Nagib nagiba
SPI is defined as the power of flowing water to erode the topography by taking the assumption that the current (q) is proportional to the specific basin area (Ace) (Moore et al., 1991; Akgün and Türk, 2010) (Equation 2):
                SPI = As ´ tanb      (2)
As                  = Specific basin area (m2) / Specifično područje bazena
Β            = Incline of slope / Nagib nagiba
Landslide Susceptibility Mapping – Mapiranje osjetljivosti
12 models were generated with different MCDM approaches including M-AHP, FIS, and LR for evaluation of the LSM. M-AHP approach, the first method in this study, was considered as the most preferred a multidisciplinary decision method in forestry studies. The M-AHP approach, not require expert opinion, has been developed, due to the fact that the analysis can be subjective in classical AHP method. Moreover, M-AHP normalizes the factors thereby making criteria comparison more successful at the decision phase. Another method utilized in the study was Fuzzy-Logic method (Mamdani) (FIS) which has been first expressed by Zadeh (1965). FIS is successful in solving complex problems. Fuzzy logic is one of the approaches which has a mathematical methodology in which the variable values are not only utilized as 0 or 1 but also the intermediate values are taken into consideration. The last method, Logistic Regression (LR) approach was preferred as it is used in such sensitivity analysis in many studies and it gives the chance to make comparisons.
In this study, NetCAD GIS 7.6 software was employed for evaluation of the factors  M-AHP, FIS and LR methods. For the validation of the models, information as regarding with the landslides, which have occurred in the past, was obtained from the General Directorate of Mineral Research and Explorations institution (Duman et al. 2011) and tested through Receiver Operating Characteristic (ROC) analysis and Area Under the Curve (AUC) value. Obtained model outputs were recorded as a raster data layers. The workflow of this study is provided in Figure 2.
The maps of landslide factors (i.e. elevation, slope, aspect, lithology, distance to faults, distance to stream, distance to roads, TWI, and SPI) are listed in Figure 3. It was found