Geospatial Analysis and Mapping of Regional Landslide Susceptibility: A Case Study of Eastern Tennessee, USA

Abstract

A landslide is the movement of rocks, debris, and/or soils down a slope, which often includes falls, topples, slides, flows, and spreads. Landslides, a serious natural hazard to human and human activity, often occur in the coastal and mountainous areas in the United States. Although there are some studies that have explored the landslide probability, which is typically directly modeled by inputting potential environmental variables into statistical regression models, this study designed an alternative geospatial analysis and modeling approach. We first conducted statistical diagnostic tests to examine the significance of potential driving factors including landform, land use/land cover, landscape, and climate. In eastern Tennessee, USA, we first applied the t-test and chi-squared test to select the significant factors driving landslides, including slope, clay percentage in the soil, tree canopy density, and distance to roads, having a p-value of less than 0.05. We then incorporated the four identified significant factors as covariates into logistic regression to model the relationship between these factors and landslides. The fitted logistic model, with a high area under the ROC (AUC) score of 0.94, was then applied to predict landslides and make a regional landslide susceptibility map for eastern Tennessee. The landslide’s potential impacts on eastern Tennessee were also discussed, and implications for local governments and communities for current physical infrastructure protection and new infrastructure development were summarized.