Quality evaluation for measured data of slope displacement based on its spatial distribution

The landslide hazard warning relies on the monitoring data such as slope displacement. Therefore, data quality assessment is of great significance in practice. The multi-point measured data of slope profile displacement are analyzed. The results show that the slope can generally be divided into three regions with different displacement characteristics during the deformation and failure. The slope displacements of points in the same area are correlated, and the correlation degree decreases as the distance between the measuring points increases. Accordingly, an algorithm for the slope region division is designed. A correlation decay equation for measuring points is proposed, and then thus a method is set up for the rapid assessment on the quality of large data of slope displacement. The slope displacement measured in a centrifuge model test is analyzed to confirm the effectiveness of the proposed method. The method has low complexity of update iteration time and is suitable for fast processing of big data.