This study presents a comprehensive review of landslides along National Highways in India, with a particular focus on the Himalayan Belt. By examining events over the past seven years, the paper delves into key drivers behind these frequent landslides and explores the efficacy of Remote Sensing (RS) and Geographic Information Systems (GIS) in landslide prediction and management. It is anticipated that the integration of these advanced tools will improve hazard assessments, enable precise interventions, and ultimately mitigate the socio-economic impacts of landslides. The study draws on publicly available data and aims to uncover gaps in the existing research on Indian landslides. Emphasizing an innovative approach, the paper proposes enhanced prediction methods to mitigate both direct and indirect losses resulting from landslides. These suggestions are grounded in the socio-economic realities of the affected regions.

Keywords: Landslide, National Highway, Remote Sensing, Geographic Information Systems (GIS), Hazard, Prediction, Mitigation, Disaster Management, Himalayan Region, Landslide Susceptibility Map.

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This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Competing Interests Statement:

The authors declare that they have no competing interests related to this work.

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Authors' contributions:

All the authors took part in literature review, analysis, and manuscript writing equally.

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Authors are willing to share data and material on request.

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