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

M Ramiz, MA Siddiqui, MS Salman, L Siddiqui… - Environmental Earth …, 2023 - Springer
Environmental Earth Sciences, 2023Springer
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 …
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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