Slope failures along the road sections cause huge problems every year in Sikkim. A slope instability analyses was performed along the road sections in parts of West Sikkim. The study was supported by geotechnical analyses like rock mass rating (RMR) and slope mass rating (SMR). In order to identify different failure types stereographic plotting based kinematic analyses was performed. Out of 33 study sites for the geotechnical analyses, 24 sites were identified as wedge failure and the remaining 9 sites were identified as the planar failure. Highly metamorphosed rocks like quartzite, phyllite and gneiss were the common rocks found in the area, comprising the discontinuities like joints were found up to 4 sets in certain locations. Other tectonic discontinuities include main central thrust (MCT), Tista lineament and other inferred thrust. Several such structural discontinuities and the weak lithology have made the area extremely vulnerable. The RMR_basic values varies from 26–60 in the study area which falls in the good to average category rocks. Adjustment factors were added to the RMR_basic to calculate the SMR values, which ranges between 26–74 and falls in good to bad rock mass description. Based on the different values for the SMR ratings, supportive measures were recommended for the different study locations. These are spot or systematic bolting, spot shotcrete, systematic anchors, systematic shotcrete, toe wall, dental concrete, systematic reinforced shotcrete, re-excavation, deep drainage, etc. and bioengineering treatment.

The Indian Himalayan Region (IHR), due to its topography, geography, and active tectonics, a rough mountain zone, is among the most vulnerable zones to the landslip danger. The most cutting-edge and accurate ways for creating a landslip susceptibility model (LSM) are advanced statistical techniques. The goal of the current work was to use advanced statistical techniques to analyse and evaluate the updated landslip susceptibility for East District in the NE Himalayas of Sikkim, India. The spatiotemporal landslip inventory for the years are produced using literature surveys, historical satellite imageries and on-site observations. Slope, aspect, elevation, curvature, plane curvature, profile curvature, topographic wetness index (TWI), lithology, distance to faults, distance to streams, distance to roads, normalised difference vegetation index (NDVI), rainfall, drainage density and land use/ land cover (LULC) are some of the topographic, environmental, geologic, and anthropogenic factors that were included in the spatial database. These LCFs were chosen to study the area's periodic landslip vulnerability. An inventory of 151 landslides from historical published records, field visits and Imagery interpretations, respectively, were used in the experimental design. Information Value Model (IVM), was used to evaluate the vulnerability to landslides as determined by fifteen LCFs. The goal of the study is to reduce the number of fatalities and possible economic harm caused by the region's frequent slope instabilities. It is expected that the application of statistical algorithms would assist relevant authorities and organisations in properly planning for and managing the region's landslip threat.