**4.2 Soil**

Soil plays an active role a landslide control factor especially in rugged terrains such as Himalayas. In the study area the soil class area differentiated into coarse loamy, fine loamy and loamy skeletal (**Table 5**). Fine loamy soils in these areas make up about 95.6% of the study area. The rest of the soils coarse loamy and loamy skeletal makes up about 4.2% of the area. Fine soil loamy soil has as clay content of between 18 to 35% and the reminder covered by sand and silt (**Figure 5**). Fine loamy


**145**

**4.3 Geomorphology**

*Soil with WOM and fuzzy overlay values.*

**Figure 4.**

**Table 5.**

*Landuse and Landcover.*

to mass movement.

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

soils are moderately prone to landslides due to their high clay content. These types of soils are prone to mass movements when the water stress in the soil particle exceeds the effective stress of the soil. Coarse loamy and loamy skeletal soil have less clay content between 10 to 18% which are considerably more prone to landslides than fine loamy soil. These soil particles without any vegetation cover are more suscep-

 Coarse Loamy 6 1.63% 4 0.6 Fine Loamy 352 95.65% 3 0.4 Habitation 5 1.36% 4 0.8 Loamy Skeletal 5 1.36% 3 0.5 368 100.00%

**coverage (%)**

**Weighted overlay model**

**Fuzzy logic**

The geomorphology has been differentiated into Habitation, Undifferentiated Hillside and Mountainside slopes (**Table 6**). Undifferentiated mountainside slopes cover about 97.83% and the hillside slopes and habitation covers only minor quantities about 0.5% and 1.6% in the study area (**Figure 6**). Geomorphologically Shimla Tehsil is moderately prone to landslides while the settlement areas are highly prone

tible to mass movements when the deformation rate in the ground is high.

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

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

#### **Table 4.** *LULC with WOM and fuzzy overlay values.*

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

**Figure 4.** *Landuse and Landcover.*

*Slope Engineering*

**4. Result and discussion**

**4.1 Landuse and landcover**

season in the stud area.

**Sl. no Class Area** 

*LULC with WOM and fuzzy overlay values.*

**(hectares)**

Total 36,824 100.00%

**4.2 Soil**

comes under high and very high risk areas. The results were validated with accuracy of 80% with the data". The fuzzy logic method uses a value of 0 to 1 to evaluate the relation between landslide occurrences with it respective causative factors. Then the causative factors are analyzed and integrated in the GIS environment to create landslide risk maps and landslide inventory data collected from the field is used to establish the degree of association with each causative factors. "Weighted Overlay Model (WOM)" uses numerical based rating method to classify the parameters ranging from very low to very high based on its degree of importance for landslide initiation and each sub factor is classified into sub categories at a scale of 1 to 5

Landuse and Landcover is one of the important causative factor for landslide risk and initiation. Urbanization along hilly areas and unstable constructions lead to slope instability causing slope failure. The LULC has interpreted from LANDSAT OLI imagery for the year 2020. Supervised classification method has been use to map Land cover of the study area. Shimla Tehsil has been classified into four classes namely Forest, Agriculture, Slopes and Settlement (**Table 4**). The classification was

Among the various land covers forest is comprised of 63.4% of the total area. Agriculture and barren land together makes 26.7% of the study area. Settlement account for only about 9.7% of the study area (**Figure 4**). The occurrences of mass movements of landslides are minimal along forest due to its soil binding capacity. Tree root bind the soil to the ground avoiding soil erosion due to torrential and monsoon rainfall. In places such as slopes and settlements soils are exposed without vegetation cover and hence prone to a large No. of landslides during monsoon

Soil plays an active role a landslide control factor especially in rugged terrains such as Himalayas. In the study area the soil class area differentiated into coarse loamy, fine loamy and loamy skeletal (**Table 5**). Fine loamy soils in these areas make up about 95.6% of the study area. The rest of the soils coarse loamy and loamy skeletal makes up about 4.2% of the area. Fine soil loamy soil has as clay content of between 18 to 35% and the reminder covered by sand and silt (**Figure 5**). Fine loamy

> **Percent (%)**

 Agriculture 5225.31 14.19% 2 0.3 Forest 23,354.53 63.42% 1 0.1 Build-up 3605.37 9.79% 4 0.7 Slope 4639.24 12.60% 5 0.8

**Weighted overlay model Fuzzy logic**

where 1 indicating the very low risk and 5 indicates very high risk.

based NRSC Level I classification system of Landuse.

**144**

**Table 4.**


#### **Table 5.**

*Soil with WOM and fuzzy overlay values.*

soils are moderately prone to landslides due to their high clay content. These types of soils are prone to mass movements when the water stress in the soil particle exceeds the effective stress of the soil. Coarse loamy and loamy skeletal soil have less clay content between 10 to 18% which are considerably more prone to landslides than fine loamy soil. These soil particles without any vegetation cover are more susceptible to mass movements when the deformation rate in the ground is high.

#### **4.3 Geomorphology**

The geomorphology has been differentiated into Habitation, Undifferentiated Hillside and Mountainside slopes (**Table 6**). Undifferentiated mountainside slopes cover about 97.83% and the hillside slopes and habitation covers only minor quantities about 0.5% and 1.6% in the study area (**Figure 6**). Geomorphologically Shimla Tehsil is moderately prone to landslides while the settlement areas are highly prone to mass movement.

#### **Figure 5.** *Soil.*


#### **Table 6.**

*Geomorphology with WOM and fuzzy overlay values.*
