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Landslide susceptibility mapping along Rishikesh–Badrinath national highway (Uttarakhand) by applying multi-criteria decision-making (MCDM) approach

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Abstract

Landslides occur when masses of rock, soil, or debris move down slopes due to various factors, such as heavy rainfall, earthquakes, or human activities, and they are among the most destructive hazards in the hilly regions posing serious threats to life and property. Identifying landslide prone areas is an essential step in minimizing losses and preparing mitigation plans. Therefore, in the present study, the landslide susceptibility mapping was conducted along Rishikesh–Badrinath national highway, using Analytical Hierarchy Process (AHP) method of Multi-Criteria Decision-Making (MCDM). Prior to performing landslide susceptibility mapping, a landslide inventory was prepared using high-resolution Sentinel-2 satellite imagery along with Google Earth image. In all total 156 landslides adjacent to the highway were identified and mapped in 2022. Afterwards, relative weights were assigned to a host of nine controlling and triggering factors using AHP. Subsequently, each factor was reclassified and converted to thematic layer and finally overlaid in the GIS environment for the generation of landslide susceptibility map. Furthermore, the generated landslide susceptibility map was validated with the landslide inventory of the region. Consequently, the validation revealed an AUC value of 0.81. Later, the created landslide susceptibility map was classified in five sub-classes of very low, low, moderate, high, and very high landslide susceptible zone. About 27% of the area was found to be highly landslide susceptible. This section is characterized with high slope and rainfall. The current study offers a comprehensive identification of landslide susceptible zones along Rishikesh–Badrinath national highway. The landslide susceptible zone map of this area may help in the preparedness and development of various mitigation plans for making disaster governance better. Additionally, landslide susceptibility map could be used as a guideline for the formulation of disaster management plan to avoid loss and reduce risk to landslide by the concerned authority. Moreover, this information can be used to raise awareness among the local people about the risk associated with the area.

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Data availability

The data supporting the findings of this study are held by the corresponding author and can be made available upon request.

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Acknowledgements

The authors are thankful to Natural Resources Data Management System (NRDMS), Department of Science & Technology, Ministry of Science & Technology, Government of India for providing financial support to the project. In addition to this, we are also thankful to European space agency for making satellite data open to public. The authors are also grateful to Geological Survey of India (GSI) for giving accessibility to various geological and lithological data. We are thankful to NASA for providing rainfall data. Further, the authors extend our appreciation to the Department of Geography, Jamia Millia Islamia, New Delhi for providing conducive environment for the research.

Funding

This work was supported by Natural Resources Data Management System (NRDMS), Department of Science & Technology, Ministry of Science & Technology, Government of India (Sanction No. NGP/LS/Masood/TPN-34315/2019 (G)).

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  1. Department of Geography, Jamia Millia Islamia, New Delhi, India

    Mohd Ramiz, Masood Ahsan Siddiqui, Mohd Sadiq Salman, Lubna Siddiqui, Mary Tahir, Hasan Raja Naqvi & Adnan Shakeel

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Contributions

MR: developed the framework of the study and completed the major part of the research. MAS: gave the geological account of the study area and all the research was done under his guidance. MSS: has contributed in writing the manuscript. LS and MT also helped in improving the manuscript writing. The contribution of HRN and AS was more in the result analysis. In addition to this, all other co-authors have contributed in the rating of various landslide controlling factors for the preparation of comparison-pair-wise matrix.

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Ramiz, M., Siddiqui, M.A., Salman, M.S. et al. Landslide susceptibility mapping along Rishikesh–Badrinath national highway (Uttarakhand) by applying multi-criteria decision-making (MCDM) approach. Environ Earth Sci 82, 591 (2023). https://doi.org/10.1007/s12665-023-11268-5

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