Geospatial Approach on Landslide Hazards Zonation Mapping Using Analytic Hierarchy Process

Geospatial technology plays a critical role in monitoring and managing natural hazards, offering powerful tools for risk assessment and disaster response. This study applies geospatial methods, particularly remote sensing, geographic information systems (GIS), and the analytic hierarchy process (AHP), to landslide susceptibility mapping in the Mandakini River Basin, Uttarakhand, India. Key factors such as slope, lithology, rainfall, elevation, fault lines, aspect, land use and land cover (LULC), topographic wetness index (TWI), proximity to roads, and drainage networks were integrated to develop a comprehensive susceptibility model. Landslide Hazard Zonation Mapping categorizes areas based on their potential susceptibility to landslides using various geo-environmental factors. It provides critical information for disaster risk management and aids in identifying high-risk zones for implementing mitigation strategies. The pairwise comparison matrix used in the AHP method demonstrated high consistency, with a consistency ratio of 0.06261. The landslide susceptibility zones were classified into low (22.87 km 2 , 1.38%), moderate (673.99 km 2 , 40.75%), high (929.08 km 2 , 56.17%), and extreme (28.02 km 2 , 1.69%). A validation process using the receiver operating characteristic (ROC) curve and area overlap coefficient (AOC) confirmed the model’s accuracy, with an AOC value of 0.876, indicating strong predictive power. This research highlights the importance of integrating geospatial data and multi-criteria decision-making techniques for natural hazard risk assessment. By identifying high-risk zones, this study emphasizes the need for targeted mitigation and risk management strategies to minimize the impact of natural disasters, providing a valuable framework for future hazard management efforts.