Fusion of DS-InSAR and THPF-LSTM for monitoring and predicting surface deformation in closed mines
ZHANG Jianyang
FAN Hongdong
ZHU Xiangyang
SUN Minghu
Abstract:After the closure of a mine,the overlying rock layer and the ground surface will deform again,this affects the safe opera-tion of buildings(structures).Due to the lack of supervision of mine closure,the spatial and temporal evolution of surface deforma-tion and prediction and warning models are not well studied.To this end,we proposed a prediction model for surface deformation of closed mines combining distributed scatter interferometric synthetic aperture radar(DS-InSAR),temporal high pass filtering(THPF),and a long short term memory network(LSTM).Taking the 98-view Sentinel-1A uptrack image as the data source,firstly,the DS-In-SAR method combined with persistent scatterer(PS)and DS points was used to obtain the time-series surface subsidence informa-tion of the closed mines in western Xuzhou for the period from November 2019 to December 2022;then the THPF was used to de-compose the original subsidence sequences to obtain the high frequency and low frequency,and then,LSTM was used to complete the deformation prediction of the high and low frequency sub-sequence,and the predicted values of the high and low frequency sub-sequence were superimposed to obtain the final prediction result.The results show that:the density of DS-InSAR monitoring points is uniformly distributed,and the coefficient of determination between the measured deformation and the monitoring results reached 0.95;compared with the LSTM model,the maximum RMSE(root mean square error)of the THPF-LSTM model in the prediction points is 3.0,and the mean absolute error(MAE)is 2.4,and the maximum Adjusted R-Square was 0.9,which is better than 4.5,3.9,and 0.6 of the traditional LSTM model,and the comprehensive prediction accuracy of the model is improved by more than 20%,and it can accurately reflect the trend and volatility of the surface deformation of the closed mine,and can effectively improve the predic-tion accuracy of mine settlement in the short term.The method of this paper realizes the integrated analysis of monitoring and predic-tion of surface deformation in closed mines.
Keywords:surface deformation predictionmine closureDS-InSARLSTM neural networktemporal high pass filtering
Publication Date:2025-06-20
Online Publishing Date:2025-08-15(First online date of this platform, not the publication date of the document)
Pages:11( 144-154 )
Safety in Coal Mines

Safety in Coal Mines

ISTICPKU
ISSN:1003-496X
Year, Vol.(Issue):2025,56(6)