A Method for Predicting Landslides Based on Micro-Deformation Monitoring Radar Data

Mine slope landslides seriously threaten the safety of people’s lives and property in mining areas. Landslide prediction is an effective way to reduce losses due such disasters. In recent years, micro-deformation monitoring radar has been widely used mine landslide monitoring. However, traditional methods are not able make full use diversified data from these radars. This paper proposes a time method based on series radar. Specifically, deformation displacement, coherence volume, parametric degree (DOD) calculated combined with tangent angle method. Finally, effectiveness verified by using measured area. The experimental results show that our proposed can be identify characteristics imminent sliding advance, providing personnel more reliable results.