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Metal Mine ›› 2015, Vol. 44 ›› Issue (03): 143-147.

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Monitoring and Prediction of Mining Subsidence based on D-InSAR and Gray Verhulst Model

Yang Junkai1,2,Fan Hongdong1,2,Zhao Weiying1,2,Feng Jun1,2   

  1. 1.NASG Key Laboratory of Land Environment and Disaster Monitoring,Xuzhou 221116,China;2.School of Environmental Science & Spatial Informatics,China University of Mining and Technology,Xuzhou 221116,China
  • Online:2015-03-15 Published:2015-07-31

Abstract: It is not easy to obtain the observation data of mining subsidence of the mining area with complex terrain.In order to solve the problem,a new mining subsidence monitoring and prediction method based on the combination of synthetic aperture radar differential interferometry(D-InSAR) technique and grey Verhulst model is proposed.Firstly,the 12 Terra SAR-X images that covered the experimental areas in the one working face of Daliuta coal mine are processed by using D-InSAR technique to obtain the subsidence values of observation stations.Secondly,the prediction function of grey Verhulst model is established based on the relationship of subsidence value and time to analyze the development law of mining subsidence.The experimental results show that,the absolute and the relative errors of D-InSAR monitoring values for three points are varied from 2.8 to 15 mm,and 0.9% to 6% respectively;The absolute error and relative error in prediction based on the grey Verhulst model Combined with D-InSAR technique are varied from 3.4 to 18.8 mm,and from 1.2% to 5.7% respectively.The experimental results above further indicate that,the method proposed in this paper can effectively make up the inadequacy of the measured data and provide reference for realizing the integration of mining subsidence monitoring and prediction.

Key words: Mining subsidence monitoring and prediction, D-InSAR, Grey Verhulst model, Prediction function