Slope deformation area division method based on dynamic time warping and k-means clustering

Abstract

The invention provides a slope deformation area division method based on dynamic time warping and k-means clustering, and the method comprises the steps: selecting a reference point displacement time sequence through comparing the change conditions of the accumulated displacement of each monitoring point in a monitoring interval; then, moving average smoothing preprocessing is adopted, the change trend of each monitoring point in the monitoring area is extracted, a monitoring point coordinate position set for follow-up classification is screened by setting a threshold value, and therefore the displacement time sequence similarity in the set is calculated through a dynamic time warping algorithm; and finally, establishing a monitoring point displacement time sequence classification model based on a k-means unsupervised clustering algorithm by taking the accumulated displacement in the monitoring interval and the DTW similarity matrix as input characteristics, thereby obtaining a preliminary division result of the slope deformation area under different cluster numbers, and comprehensively evaluating the classification result under different cluster numbers by calculating multiple indexes, and therefore, a simple and efficient classification method is provided for slope deformation area division.

Description

technical field [0001] The invention belongs to the technical field of microwave remote sensing and geological hazard prediction and early warning, and in particular relates to a slope deformation area division method based on dynamic time warping and k-means clustering. Background technique [0002] Based on the ground-based synthetic aperture radar differential interferometry technology, the displacement information of the monitoring area can be obtained based on the phase information by performing differential interference processing on two radar images acquired at the same position and at different times. Accurately extracting deformation areas from a wide range of target areas, combined with the time evolution and spatial distribution information of each deformation area, is conducive to analyzing the overall stability of the monitoring area and evaluating the risk level of landslides. Therefore, the division of slope deformation regions is an important step in landslid...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the problems in the unsupervised division of slope deformation regions, such as large amount of calculation and using displacement rate as a single index, the present invention provides a method for division of slope deformation regions based on dynamic time warping and k-means clustering, which can realize slope deformation Efficient Division of Deformation Regions

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