**3. Dataset and research method**

*Slope Engineering*

**Sl.no Year No. of socio economically** 

*Socio-economic significant landslides (1800–2011).*

**2. Study area**

**Table 2.**

these problems should be addressed together. The current research is focused on analyzing the accuracy of weighted Overlay model and Fuzzy logic model to estimate the landslide risk mapping along the Rampur tehsil, Himachal Pradesh, India.

**significant events**

 2018–2019 1 0 0 2007–2017 893 (Nasa Catalog) 6614 893 2011 26 74 19 2010 85 368 53 2009 47 270 46 2008 36 220 30 2007 54 409 39 1800–2007 123 2630 61

**Persons killed No. of fatal events**

The study area extends from "76°58′19" to 77°19′21″ longitude and 30°59′3″ to 31°14′10″ h latitude" with a total area of 368 Sq.km hectares (**Figure 3**). According to 2011 census the Shimla has a total of 576 villages. The total population of Shimla as of 2011 census is 1,71,640 people among which 1,69,578 reside in "Shimla

Municipal Corporation" and the rest in Shimla Rural and Jutogh cantonment board.

**142**

**Figure 3.** *Study area.*

The base map of the study area was digitized from Survey of India Toposheets. One cloud free satellite data LANDSAT 8OLI (26/01/2020) was downloaded from the earth explorer website. Soil data covering the study area was received from "Soil and Landuse Survey of India (SLUSI)". In addition, a 30 mts ASTERGDEM data was downloaded from USGS website for topographical analysis. Rainfall data has been acquired from Indian Meteorological Department, Shimla. The types of data used is given in (**Table 3**).

Weighted Overlay and Fuzzy logic models are the two type statistical methods used in the research. In the recent years many researchers and scientist have used the methodology to derive landslide risk mapping with higher accuracies [29–36]. "Barrile Vincenzo et.al, 2016 used Fuzzy logic method for mapping landslide susceptibilities. The province of Reggio Calabria, Italy chosen as study area. Parameters such as Elevation Slope, Lithology, Rainfall and Landuse were assigned values and processed in GIS environment. The output subdivides into five categories ranging from Very low to Very high. The results indicate that 22%, 36% and 20% of the area comes under Very high, High and Moderate risk zones". "Leonardi Geovani et.al, 2016 used a Fuzzy approach to analyze landslide susceptibility for Reggio Province, Calabria, Italy. Rainfall, Elevation, Slope, Landuse and Lithology were used as landslide influencing parameters. The output signifies that 22% and 36% of the area


**Table 3.** *Data used.* 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 where 1 indicating the very low risk and 5 indicates very high risk.
