**4.5 DEM**

Elevation is a secondary factor often used in landslide risk mapping. The risk mapping in DEM model depends upon the no of landslides occurring within a particular

**147**

**Figure 7.** *Geology.*

**Figure 6.** *Geomorphology.*

*Comparative Evaluation of Various Statistical Models and Its Accuracy for Landslide Risk…*

Hence these particular elevations are assigned higher risk values (**Figure 8**).

elevation height. In the current study area most of the landslide occurs between 1400 to 2100 mts (**Table 8**) above the mean sea level compared to other elevation heights.

*DOI: http://dx.doi.org/10.5772/intechopen.94347*

*Comparative Evaluation of Various Statistical Models and Its Accuracy for Landslide Risk… DOI: http://dx.doi.org/10.5772/intechopen.94347*

elevation height. In the current study area most of the landslide occurs between 1400 to 2100 mts (**Table 8**) above the mean sea level compared to other elevation heights. Hence these particular elevations are assigned higher risk values (**Figure 8**).

**Figure 6.** *Geomorphology.*

*Slope Engineering*

**146**

**4.5 DEM**

**4.4 Geology**

**Table 6.**

2 Undifferentiated Hill

3 Undifferentiated

Side Slope

Mountain Side Slope

*Geomorphology with WOM and fuzzy overlay values.*

**Figure 5.** *Soil.*

Geology plays a key role in groundwater recharge as the types rocks present in an area could hugely affect the amount of water entering into the groundwater table. The study area is covered three major classes namely Schist, Slate and Habitation (**Figure 7**) in which mainly dominated by two types of rock formation namely Slate and Schist that comprises 95.9% and 2.1% (**Table 7**) of the study area. These rocks vary from Moderate to strong in nature in the GSI index. Waters can percolate through the cracks within the rocks or even between them. Fractures and joints formed along the rock surface act as perfect carriers for Rainwater into the groundwater table. Habitation accounts for only 1.90% and these areas mostly comprised of settlements they are placed in the high risk factor for mass movements initiation.

368 100.00%

1 Habitation 6 1.63% 4 0.8

**coverage (%)**

2 0.54% 3 0.5

360 97.83% 3 0.5

**Weighted overlay model** **Fuzzy logic**

**Sl.no Soil class Area (sq.km) Percent** 

Elevation is a secondary factor often used in landslide risk mapping. The risk mapping in DEM model depends upon the no of landslides occurring within a particular


### **Table 7.**

*Geology with WOM and fuzzy overlay values.*


#### **Table 8.**

*DEM with WOM and fuzzy overlay values.*

**Figure 8.** *Digital elevation model.*

#### **4.6 Slope**

Slope aspect plays a crucial in highly dissected mountainous regions for landslide movements. The steeper the angle of the slopes the higher the possibility of the mass movements. In the research SRTM DEM data has been used for deriving slope parameters (**Figure 9**). The slopes has been classified into five ranging from very gentle to very steep (**Table 9**) in nature.

**149**

**4.7 Landslide risk mapping**

*Slope with WOM and fuzzy overlay values.*

and low risk areas (**Figure 10**).

*4.7.1 Fuzzy logic model*

**Figure 9.** *Slope.*

**Table 9.**

*Comparative Evaluation of Various Statistical Models and Its Accuracy for Landslide Risk…*

For the current study two statistical models were employed "Fuzzy logic and Weighted Overlay model (WOM)" for landslide risk mapping. Factor including LULC, Geology, Geomorphology, Soil, slope (**Table 10**) were used as factoring parameters for risk mapping. Each causative factors were assigned a value of 0 to 1 based on it degree of association between causative factors. The factors are then processed in the GIS environment to derive fuzzy logic based landslide risk mapping. Based on the results it can be concluded that most of the study area falls under very low risk with a total coverage of 67.34%. Low and Moderate area covers about 23% and 9.13% of the study area. Higher risk areas only account for about 0.46%. Higher percent of the study area is mostly covered by settlements. National highways, Metal roads, Slopes and Denser settlements are located along the Moderate

**Sl. no Slope (degrees) Angle Weighted overlay** 

 < 5 Very gentle 1 0.1 6 to 15 Moderately gentle 2 0.3 16 to 25 Moderately steep 3 0.5 26 to 45 Very steep 4 0.8 45 Extremely steep 5 0.9

**model**

**Fuzzy logic**

*DOI: http://dx.doi.org/10.5772/intechopen.94347*

*Comparative Evaluation of Various Statistical Models and Its Accuracy for Landslide Risk… DOI: http://dx.doi.org/10.5772/intechopen.94347*

#### **Figure 9.**

*Slope.*

*Slope Engineering*

**Table 8.**

**Table 7.**

*DEM with WOM and fuzzy overlay values.*

*Geology with WOM and fuzzy overlay values.*

**148**

**4.6 Slope**

*Digital elevation model.*

**Figure 8.**

gentle to very steep (**Table 9**) in nature.

Slope aspect plays a crucial in highly dissected mountainous regions for landslide movements. The steeper the angle of the slopes the higher the possibility of the mass movements. In the research SRTM DEM data has been used for deriving slope parameters (**Figure 9**). The slopes has been classified into five ranging from very

**Sl. no Elevation (mts) Weighted overlay model Fuzzy logic** 820 to 1300 1 0.3 1301 to 1600 3 0.6 1601 to 1800 4 0.8 1801 to 2100 4 0.7 2101 to 2200 2 0.3

 Habitation 7 1.90% 4 0.8 Schist 8 2.17% 3 0.6 Slate 353 95.92% 3 0.4 368 100.00%

**coverage (%)**

**Weighted overlay model**

**Fuzzy logic**

**Sl. no Soil class Area (sq.km) Percent** 


#### **Table 9.**

*Slope with WOM and fuzzy overlay values.*

#### **4.7 Landslide risk mapping**

#### *4.7.1 Fuzzy logic model*

For the current study two statistical models were employed "Fuzzy logic and Weighted Overlay model (WOM)" for landslide risk mapping. Factor including LULC, Geology, Geomorphology, Soil, slope (**Table 10**) were used as factoring parameters for risk mapping. Each causative factors were assigned a value of 0 to 1 based on it degree of association between causative factors. The factors are then processed in the GIS environment to derive fuzzy logic based landslide risk mapping.

Based on the results it can be concluded that most of the study area falls under very low risk with a total coverage of 67.34%. Low and Moderate area covers about 23% and 9.13% of the study area. Higher risk areas only account for about 0.46%. Higher percent of the study area is mostly covered by settlements. National highways, Metal roads, Slopes and Denser settlements are located along the Moderate and low risk areas (**Figure 10**).


#### **Table 10.**

*Fuzzy logic landslide risk categories.*

**Figure 10.** *Fuzzy logic based landslide risk assessment.*
