Application of a fast and efficient algorithm to assess landslide prone areas in sensitive clays – toward landslide susceptibility assessment, Sweden
Abstract. This work deals with susceptibility assessment in sensitive clays at national scale. The proposed methodology is based on a procedure which uses soil data and Digital Elevation Models to detect areas prone to landslides and has been applied in Sweden for several years. Specifically, we tested an algorithm which is able to detect soil and slope criteria guaranteeing a faster execution compared to other implementations and an efficient filtering procedure. The adopted computational solution allows using local information on depth to bedrock and several cross-sectional angle thresholds, and therefore opens up new possibilities to improve landslide susceptibility assessment. We tested the algorithm in the Göta River valley and evaluated the effect of filtering, depth to bedrock and cross-sectional angle thresholds on model performance. The thresholds were derived by analysing the relationship between landslide scarps and the Quick Clay Susceptibility Index (QCSI). The results gave us important insights on how to implement the filtering procedure, the use of depth to bedrock and the derived cross-sectional angle thresholds in landslide susceptibility assessment.