Risk Assessment of Unstable Rock Masses on High-Steep Slopes: An Attribute Recognition Model

To effectively control the collapse risk of unstable rock masses, an attribute recognition model for risk assessment of unstable rock mass on high-steep slopes is established using attribute mathematical theory. The lithology, geologic structural, slope gradient, slope shape, rainfall, slope, vegetation, and human activity are selected as risk assessment indices with grading criteria of each index. The weights of assessment indices are determined using a judgment matrix constructed using the analytic hierarchy process. The attribute measurement functions are used to compute attribute measurement of a single index and a synthetic attribute measurement. The identification and classification of risk assessment of the unstable rock mass are assessed using a confidence criterion. The fatalness of an actual unstable rock mass on high-steep slope is evaluated based on the previously established attribute recognition model. A method for geological disaster monitoring of the unstable rock mass in Yangjiao Town is determined based on the assessment results providing an effective approach to risk assessment of the unstable rock mass.