Chinese experts propose novel approach for precise geological disaster prediction

Using satellite imagery, the study team has put forth a novel method for landslide prediction. This is reported by Xinhua News Agency, a partner of TV BRICS.

An essential component of the early warning system about the risks connected to landslides is the prediction of landslide deformations. Site-based geotechnical monitoring produces positive outcomes. However, regular application of this approach over wide areas is hindered by its high cost and spatial restrictions.

Employees from Peking University and the China University of Geosciences joined the research endeavour. They used machine learning techniques to obtain information about the movement of mountain weather from satellite observations, which serves as basic data for early warning and forecasting.

The practical application of the new method on the Yangtze River has shown that multi-temporal interferometric synthetic aperture radar (MT-InSAR) allows accurate tracking of rock deformation, and machine learning algorithms can accurately establish a nonlinear relationship between rock deformation and its triggers.

The new solution can more accurately, more economically, and more effectively predict geological disasters such as landslides in large areas, the article notes.

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