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Slope instability is a challenge in both mining and civil engineering industries. Current ap-proaches to slope stability analysis are mostly based on slope deformation data provided by mon-itoring equipment. This study proposes a new method to estimate slope stability using amplitude and coherence obtained from slope stability radar data. More than 160,000 data points from 10 slope failures were collected with GroundProbe’s slope stability radar systems. They were used as input dataset in a Naive Bayes model for classification into two groups of stable and unstable slopes. The classifications were conducted based on different range limit values for amplitude and coherence. The findings were validated against slope deformation behavior in each case. The results show that 91 percent of the data that are classified as unstable slope by the Naive Bayes Gaussian method belong to slope failure events and are categorized correctly. The coherence and amplitude range values proposed in this research can be utilized by mining operations to determine the stability of slopes in conjunction with slope deformation and inverse velocity data.

Wall control and blasting are two major activities that significantly impact the productivity and safety of open-pit mining operations. Although many monitoring equipment are used for improving slope stability, there is still a need for understanding slope behaviour during a blast. This paper describes a new technology called Blast Vision®, developed by Ground Probe, for monitoring the interaction between blasting and slope stability with a temporal resolution in the range of milliseconds. This technology represents an innovative departure from standard blast vibration sensors by measuring ground luminance changes on the ground surface through drone-based computer vision. Blast Vision application for slope stability, misfires and fly rocks is investigated in this publication.