Comprehensive landslide prediction mapping using bivariate statistical models of Mizoram state of Northeast India
Jonmenjoy Barman, Jayanta Das
Abstract
Landslides in the state of Mizoram result in damage to life and properties annually. The study focuses on landslide susceptibility zones by frequency ratio (FR), evidential belief function (EBF) and index of entropy (IOE) models. A total of 1,486 landslide points were used to build a relationship between 16 factors and landslide occurrences. The results reveal 14.44%, 19.64% and 3.55% of the area as very high susceptible zones in FR, EBF and IOE models, respectively. The AUC results support the adoption of the EBF model in land use planning and decision-making processes to enhance natural resource management and mitigate landslide risks in Mizoram.
Topics & Concepts
Bivariate analysisLandslideGeographyGeologyWater resource managementPhysical geographyCartographyStatisticsEnvironmental scienceGeotechnical engineeringMathematicsLandslides and related hazardsFlood Risk Assessment and ManagementTree Root and Stability Studies