## 5 Conclusions  
One of the deadliest natural dangers in the mountainous terrain is a landslide. Due to man-made and natural events, the highly damaged mountainous landscape is vulnerable to landslides (such as earthquakes, climate change, and human intervention, respectively). Because of these threats, communities in West Bengal's northern Himalayan highlands live in a never-ending nightmare, leading to socio-economic losses. To protect property and livelihood, interim and long-term solutions to reduce the risk of landslides in this region are required. To aid in infrastructural development and socio-economic development planning, we must identify and map the most vulnerable areas. LSM may be a critical tool for assessing risk management in rugged terrain. For many years, the application of MCDA models for landslide hazard assessment has produced amazingly efficient and exact results. The primary goal of this study is to evaluate the efficacy of MCDA models AHP and to determine the most accurate and helpful approach for detecting landslide-prone places in the research region. The result is based on AHP, classified into four landslide susceptibility classes. The classes are very high, high, moderate, and low landslide susceptibility. The results show that 26.18% of the total area falls under high landslide susceptibility zones, and 11.68% falls into very high susceptibility areas. So, the entire 37.86% area is in a high to very high susceptibility zone. Our findings (based on LSM and AUC) show that the usual strategy is successful. The AHP MCDA algorithm achieved 96.8 percent for the AUC-ROC curve and 81.3 percent for the success rate curve. From the result, we can identify that most areas which fall under the high to very high susceptibility classes are in the eastern, south-eastern, and southern parts of the area. The pattern of landslide sites reveals that landslides often occur on heavily dissected slopes. Less debris-filled vegetation areas can increase the risk of landslides. The area's combined landslide categorization is  
Figure 10: The map shows the high to very high susceptibility zone of the study area.  
debris slide. Hence, it can be concluded that the most likely place for a landslide to occur in this study area is a severely dissected hill with debris and low to moderate vegetation, usually sparse forest, barren land, or a tea plantation area. This research successfully identified the landslide-prone locations, and the best location for planners for development in the hilly region of Darjeeling, West Bengal, India. Finally, the LSM established in this research may be used by decision-makers, land-use planners, and other governmental and non-governmental entities as an efficient tool for optimizing resource management, infrastructure development, and human activity in the studied area.  
Conceptualization, A.S.; methodology, A.S., V.G.K.V. and A.B.; software, A.S.; validation, A.S., V.G.K.V. and A.B.; formal analysis, A.S.; investigation, A.S., V.G.K.V., A.B. and S.K.; resources, A.S., V.G.K.V. and A.B.; writing--original draft preparation, A.S.; writing--review and editing, A.S., V.G.K.V., A.B. and S.K.; visualization, A.S., V.G.K.V., A.B. and S.K.; supervision, V.G.K.V. and A.B. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors are thankful to the Department of Mining Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, for providing an adequate environment for the research work. Authors thanks [PERSON] for the support during the study.  
The authors declare no conflict of interest.