An intelligent mountain landslide remote monitoring method and system

Abstract

The application relates to the field of geological disaster monitoring, and discloses an intelligent mountain landslide remote monitoring method and system, which comprises the following steps: firstly, a basic data set is constructed by acquiring the unique ID and physical coordinates of a target monitoring area marker point; secondly, a mountain image is acquired based on a unified time reference, and a light point image coordinate is extracted through differential processing and converted into a point cloud data set; thirdly, displacement analysis is carried out to identify abnormal marker points, and the monitoring frequency is adjusted; fourthly, spatial clustering analysis is carried out to determine an aggregation area and calculate geometric features; fifthly, a weighted time sequence fitting of the displacement rate of the abnormal marker points in the aggregation area is carried out to obtain a weighted average displacement acceleration; sixthly, multi-modal environmental data are acquired, and correlation analysis is carried out on the multi-modal environmental data; seventhly, environmental factors and time delay characteristics are identified; eighthly, a landslide occurrence probability is output by inputting the machine learning prediction model; ninthly, it is determined whether to trigger an early warning and send the early warning to a remote terminal; and tenthly, mountain displacement can be accurately monitored, potential landslide risk areas can be identified in a timely manner, and a scientific basis for disaster prevention and reduction is provided to reduce disaster losses.

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