Evaluation of statistical modeling (SM) approaches for landslide susceptibility mapping: geospatial insights for Bhutan

Abstract

Landslides pose a significant threat to human settlements, infrastructure, and the environment, necessitating proactive measures for disaster risk reduction (DRR). This study explores the integration of Remote Sensing (RS), Geographic Information Systems (GIS) and Statistical Modelling (SM) techniques to create a comprehensive landslide susceptibility mapping model. The objective is to enhance our understanding of the spatial distribution and factors influencing landslide susceptibility, ultimately aiding in effective land-use planning and disaster management. Because of the extensive impacts of topography, hydrology, geology, geomorphology, and climatic conditions, the susceptibility to landslide risks in mountainous places, exhibits obvious regionalism. As a result, we proposed three statistical models (i.e., Frequency Ratio (FR), Information Value (InV), and Shannon Entropy (SE)) to evaluate susceptibility at the national level. Validation of the susceptibility model is performed using 30% of the historical landslide events using Receiver Operating Characteristic (ROC) analysis and area under the curve (AUC). The results demonstrate the reliability and effectiveness of the integrated RS-GIS-SM approach in predicting landslide susceptibility. The three models demonstrate strong agreement with negligible differences in AUC of 0.910, 0.909, and 0.908 for FR, SE, and InV, respectively. The study's findings provide valuable insights into land-use planners, environmental agencies, and decision-makers to prioritize high-risk areas for mitigation strategies. Additionally, the developed model serves as a basis for future research and refinement, contributing to ongoing efforts to enhance landslide susceptibility mapping accuracy and applicability in diverse geographic regions. The integration of RS-GIS-SM technologies offers a powerful toolset for understanding and managing landslide risk, ultimately promoting safer and more resilient communities.