An Integrated
Landslide Susceptibility Mapping of Wayanad district, Kerala using AHP and FR Models:
A Lessons from the 2024 Landslides
Akhil Tej S., Ramya Swetha R., Venkata Rami Reddy Y., Padma Priya K.T. and Vishnu
Vardhan Reddy L.
Disaster Advances; Vol. 18(6); 42-57;
doi: https://doi.org/10.25303/186da042057; (2025)
Abstract
This study presents a comprehensive landslide susceptibility mapping (LSM) for Wayanad
district using a Multi-Criteria Decision-Making (MCDM) approach, integrating Geographic
Information Systems (GIS) with the Analytical Hierarchy Process (AHP) and Frequency
Ratio (FR) models. The methodology involves a six-step process: data collection
from USGS, SRTM-DEM and Bhukosh followed by the creation of thematic maps covering
elevation, slope, aspect, proximity to roads and rivers, geological features, rainfall
and land use/land cover. AHP is applied by rescaling thematic maps to a uniform
5-point scale, calculating the consistency index and determining weights. If the
consistency ratio (CR) is ≥ 0.10, adjustments are made to ensure accuracy. FR values
for each factor are computed to develop the LSM.
The LSM was validated using Receiver Operating Characteristic (ROC) curves and Area
under the Curve (AUC) values, with AUC scores of 0.913 and 0.896 for the AHP and
FR models, respectively indicating high prediction accuracy. The LSM is categorized
into five susceptibility classes: very low, low, moderate, high and very high, providing
critical insights for disaster preparedness and risk mitigation in Wayanad. The
study underscores the significant role of GIS and MCDM techniques in enhancing landslide
risk assessment and management.
