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ŠUMARSKI LIST 7-8/2019 str. 47     <-- 47 -->        PDF

areas. Points for lithology factor was assigned as 9 to Sandstone-Mudstone areas, 5 point to Phyllite areas, 3 point to Schist areas and other areas were scored as 1 point. Distance to faults factor is grouped in five classes as 1-2 km, 2-5 km, 5-10 km and 10-20 km zones and the nearest distance is 9 points and the longest distance is 1 points. Distance to streams factor is grouped in four classes as 2 km, 4 km, 8 km and 20 km zones and the shortest distance is 9 points and the longest distance is 1 points. Distance to roads factor is grouped in four classes as 200 m, 500 m, 1000 m and 2000 m zones and the nearest distance is 9 points and the longest distance is 1 points. The TWI and SPI factor was evaluated in five different groups and the scores were the highest 9 point and the lowest 1 point. 
The FIS method was implemented via the toolbar found in the software GIS 7.6. Three different membership functions, low, medium and high, were assigned for the configuration of desired range values. The last method, LR, was obtained by joining the raster of each factor via the toolbar in the software and then joining them subsequently. The models in this study and the validation values of the models were provided in Figure 4-9.
The LSM index value in the models generated in line with the M-AHP method was between 0.087 as the lowest value and 0.700 as the highest value. Models’ successes were found to be AUC-Model 1M-AHP = 70.4%, AUC-Model 2M-AHP = 68.6%, AUC-Model 3M-AHP = 71.0%, AUC-Model 4M-AHP = 63.3%, respectively, according to the M-AHP method (Figure 5). 
The LSM index value in the models developed in line with the FIS method was between 0.249 as the lowest value and 0.792 as the highest value (Figure 6). Models’ successes were found to be AUC-Model 1FIS = 73.2%, AUC-Model 2FIS = 73.2%, AUC-Model 3FIS = 72.2%, AUC-Model 4FIS = 73.4%, respectively, according to the FIS method (Figure 7).
The LSM index value in the models generated in line with the LR method was between 0.001 as the lowest value and 0.999 as the highest value (Figure 8). Models’ successes were found to be AUC-Model 1LR = 64.6%, AUC-Model 2LR = 65.1%, AUC-Model 3LR = 76.6%, AUC-Model 4LR = 75.7%, respectively, according to the LR method (Figure 9).
The general road density of the study area is 14.7 m.ha-1.  It was determined that the landslide risk was high in the southern part of İhsangazi Watershed as a result of the approaches utilized in the study (i.e. M-AHP, FIS and LR). As such, the density of the roads (i.e. all of the forest roads) located in the south of the watershed was computed again and found to be 14.6 m.ha-1 (Figure 10). This computed value is much below the 25 m.ha-1 value (Erdaş 1997), which is the road density value desired to be reached. However, it should be taken into consideration that the average road density should not be increased in terms of not triggering the landslide formation as the foregoing area is close to the fault line and located in very susceptible areas to landslide in LSM models.
DISCUSSION AND CONCLUSION
RASPRAVA I ZAKLJUČAK
It has great importance to determine areas susceptible to landslide in advance by virtue of GIS techniques and to integrate them into planning stages made for such areas. Plans can be more rational when evaluated in this respect. 12 models have been established according to three different approaches (M-AHP, FIS and LR) by using nine factors which can be used in practice and can help to decide the determination of alternative routes. The validations of the models were calculated by comparing the data of the previous landslide areas and the results of the models. All the model successes ranged from 64.6% to AUC and 76.6% to AUC in this study. In previous studies, Yalçın et al.  (2011) determined the AUC value of 42.58 % based on seven factors while Shahabi et al. (2014) reported the AUC value of 89.41% considering the eight factors. In most recent studies, Eker and Aydın (2016) found the AUC value of 85% based on eight factors and Jacobs et al. (2018) reported the AUC value of 78% according to seven factors. Comparing with the results from the similar studies, the successes of the models revealed in this study were at acceptable levels. In addition to number and combination of factors in LSM studies,