Multiclassification Method of Landslide Risk Assessment in Consideration of Disaster Levels: A Case Study of Xianyang City, Shaanxi Province

Geological disaster risk assessment can quantitatively assess the risk of disasters to hazard-bearing bodies. Visualizing the risk of geological disasters can provide scientific references for regional engineering construction, urban planning, and disaster prevention and mitigation. There are some problems in the current binary classification landslide risk assessment model, such as a single sample type, slow multiclass classification speed, large differences in the number of positive and negative samples, and large errors in classification results. This paper introduces multilevel landslide hazard scale samples, selects multiple types of samples according to the divided multilevel landslide hazard scale grade, and proposes a landslide hazard assessment model based on a multiclass support vector machine (SVM). Due to the objective limitations of the single weighting method, the combined weights are used to determine the vulnerability of the landslide hazard-bearing body, and the analytic hierarchy process (AHP) and entropy method are combined to construct a landslide vulnerability assessment model that considers subjective and objective weights. This paper takes landslide disasters in Xianyang City, Shaanxi Province, as the research object. Based on the landslide hazard assessment model and the landslide vulnerability assessment model, a landslide risk assessment experiment is carried out. It generates the landslide risk assessment zoning map and summarizes the risk characteristics of landslides in various towns. The experimental results verify the feasibility and effectiveness of the proposed model and provide important decision support for decision makers in Xianyang City.

Landslide Hazard Assessment in a Monoclinal Setting (Central Italy): Numerical vs. Geomorphological Approach

A correct landslide hazard assessment (LHA) is fundamental for any purpose of territorial planning. In Italy, the methods currently in use to achieve this objective alternate between those based on mainly qualitative (geomorphological) and quantitative (statistical–numerical) approaches. The present study contributes to the evaluation of the best procedure to be implemented for LHA, comparing the results obtained using two different approaches (geomorphological and numerical) in a territorial context characterized by conditioning and triggering factors, favorable to the instability of the slopes. The results obtained, although preliminary, evidence the respective limitations of the methods and demonstrate how a combined approach can certainly provide mutual advantages, by addressing the choice of the best numerical model through direct observations and surveys.