Semi-automated classification of layered rock slopes using digital elevation model and geological map

Abstract

Abstract Layered rock slopes are the most widely distributed slopes with the simplest structure. The classification of layered rock slopes is the basis for correctly analyzing their deformation and failure mechanisms, evaluating their stability, and adopting reasonable support methods. It is also one of the essential indicators to support the evaluation of urban and rural construction suitability and the assessment of landslide hazards. However, the present-day classification methods for layered rock slopes are not sufficiently automated. In the application process of these methods, a lot of manual intervention is still needed, and sufficient strata orientation data obtained through field surveys is required, which is not effective for large-scale applications and involves high subjectivity. Thus, this study proposes a semi-automated classification method for layered rock slopes based on digital elevation model (DEM) and geological maps, which greatly reduces human intervention. On the basis of slope unit division, the method extracts structural information of slopes using DEM and geological maps and classifies slopes according to their structural characteristics. An experiment has been carried out in the northern region of Mount Lu in Jiangxi Province, and the results demonstrate the effectiveness of this semi-automated classification method. Compared to the existing manual or semi-automated classification methods, the method proposed in this article is objective and highly automated, which can meet the requirements of classification of layered rock slopes over large areas, even in the case of sparse measured orientation data.