Terminologically, landslide susceptibility mapping (LSM) is used to categorize land surface into areas and to arrange them according to the degree of vulnerability of different causative factors. Landslide susceptibility analysis is a pre-disaster management which deals with the past landslide data and dominant factors of landslide occurrence. From the past, researchers and planners are divided landslide studies into two parts, pre-disaster and post-disaster study.
To show the distractive power landslide and reduce divesting power of landslide, researchers considered different approaches of methodology on our globe. In India, 12.6% of total area is landslide-prone area therein, about 43% is captured by Darjeeling–Sikkim Himalaya region, about 33% is covered by northwest Himalaya, 22% area is acquired by western hill, Konkan Ghat, and about 2% area is captured by eastern hill, Aruku ( ). Landslide is a semimajor disaster in India and hit lives, infrastructure, roads, communication and resources in the hill region. A huge amount of economic losses, injuries and death are caused by landslide, nearly about 18,414 people died, 4.8 million people were affected and 8 billion US$ resources were damaged in the period of 1998–2017 all over the world. Landslide is renowned as a mountainous disaster and responsible for massive economic and social losses. Landslide is a type of mass movement, and it is the rapid fall of the large volume of rocks and soils from upslope to downslope mainly because of gravity. Landslide is known as a natural hazard in hill and mountainous areas all over the world, and it has effect on the life of the people in hill region in general and traffic in particular. All these geo-environmental hazards have brought the beleful footprint over the earth. In the present time, our natural environment faces a number of destructive natural hazards such as earthquake, flood, drought, storm surge and landslide all over the world. The results revealed 88.9% prediction rate and 92.3% success rate, which means this model is validated with landslide susceptibility analysis in the study area. The map was compared with the validation of landslide location, and the model was verified by the receiver operating characteristic curve. The GIS-based landslide susceptibility analysis has been discussed with ten dominant factors by using frequency ratio model.
Ten influential causative factors of landslide occurrence are used for the susceptibility assessment, and they are slope angle, slope aspect, elevation, profile curvature, land use/land cover, normalized differences vegetation index, drainage density, road density, geology and rainfall.
The study utilized different types of data which include geological data, advanced spaceborne thermal emission and reflection radiometer-based digital elevation model, Sentinel-2A sensor data, published thematic map and precipitation data, and all data have been processed with the help of remote sensing and GIS tools. The main objectives of this study are to produce landslide susceptibility mapping by frequency ratio method and to find out the dominant parameters which are responsible for the occurrences of frequent landslide in Lachung River basin, the main tributary of Teesta River in Sikkim Himalaya. Landslide susceptibility map has become essential to identify the landslide-prone zones and to find out the probable causes of a landslide in an area. Landslide susceptibility assessment is very important to mark out the landslide susceptibility area, and researchers take some plans for the future. Landslide causes damage to property and life in the Himalayan region as well as Sikkim Himalaya.
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