Optimal Deployment of Monitoring Points Considering Spatial Deformation Correlation of Slopes

On-site surface displacement monitoring of slopes has become essential for slope warning and prediction. However, there is no specific regulation on scientifically and reasonably determining the number and location of monitoring points on the slope surface. The layout of monitoring points still requires clarification. To this end, combining the displacement data sequence and spatial position information of surface displacement monitoring points, the concept of spatial distance-related scale index is introduced, and a slope spatial deformation correlation calculation model based on spatial statistics is proposed to calculate the correlation between different monitoring points. Based on this theory, the correlation clustering analysis method divides the slope area. Redundant monitoring points in each zone are removed according to the zoning results, ultimately achieving the optimized layout of the overall monitoring points of the slope. This method has scientifically solved the division of slope deformation areas and the overlap of data collection during slope monitoring, thereby improving the efficiency and accuracy of slope monitoring. To verify the validity of this method, we studied a sandstone-mudstone interbedded anti-dip excavation slope in southwest China. We discussed the displacement data and spatial positions of 24 monitoring points on this slope for 13 months. The results showed that the proposed optimization method for monitoring point layout considering the spatial deformation correlation of the slope was feasible. Correlation analysis of monitoring points considering spatial distance.A slope zoning method considering spatial deformation correlation of slopes is proposed.A new method for optimal arrangement of monitoring points based on slope zoning.