The present study aims to develop a landslide susceptibility map (LSM) along National Highway-109 (NH-109) from Kakrighat to Chausali, comparing the Analytical hierarchy process (AHP) and Frequency ratio (FR) method. Numerous case records on landslide susceptibility mapping along various road networks within the Himalayas majorly rely on traditional factors related to topography, geology and hydrology. Conventional geospatial conditioning parameters were combined with field-based geo-mechanical parameter. The Schmidt Hammer Rebound (SHR) values were taken to incorporate near-surface rock mass strength into susceptibility mapping, adding novelty to the employed methods. Such an attempt distinguishes it from numerous existing case records on susceptibility mapping. The landslide inventory includes fifty-eight landslides gathered from Bhukosh, the Geological Survey of India database, Google Earth, and extensive field surveys. The generated LSMs were categorized into very low, low, moderate, high and very high susceptibility zones using the AHP (5.74%, 22.48%, 38.99%, 24.59%, and 8.19%) and FR model (13.27%, 25.98%, 28.87%, 14.44%, and 17.44%), respectively. Model performance was evaluated using receiver operating characteristic (ROC) analysis, yielding area-under-curve (AUC) values of 78.8% and 81.8% for AHP and FR methods, indicating good predictive capability of both models. The results show that high and very high susceptibility zones are predominantly concentrated along road-cut slopes, structurally controlled sections, and areas characterized by low SHR values. The study elucidates pivotal insights for planners, stakeholders, and decision-makers, providing analytical frameworks to tackle and adeptly mitigate the significant risks of landslide occurrences.
Khan et al. (Mon,) studied this question.
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