Abstract: The gob caused by mining production can result in the surface mining subsidence,collapse and other geological hazards,which is a serious threat to the ecological environment of the mining area and its surrounding area.Taking the Xihaozhuang iron mine as the study background,firstly,based on analyzing the monitoring principle of the GPS monitoring technique,the surface mining subsidence monitoring GPS network is established;then,based on the monitoring data of the mining subsidence GPS network,the G(1,1) grey prediction model is constructed,and the mining subsidence prediction formulas of the GPS monitoring points are given;the digital evaluation model of the mining area are established respectively based on the prediction data and monitoring data,besides that,the mining subsidence serious regions of the mining area are predicted effectively.The study results show that:①the accumulated mining subsidence value of the mining area are lower than 40 mm,the possibility of surface collapse is small in the mining area,the mining value of the surrounding areas of the CD3#、CD4#、CD5#、CD6# points are higher than others,about 30 mm;②the error between the prediction values obtained by the newly established G(1,1) prediction model and the monitoring data in the mining area are 1.38% (CD3#)、0.56% (CD9#),the digital evaluation model (DEM) established by the mining subsidence value is consistent to the one established by the actual monitoring value in the mining area,which indicated that the G(1,1) prediction model is suitable to predict the mining subsidence in the mining area,and the prediction accuracy is ideal.

Key words: Mining subsidence, GPS,Grey theory, G(1,1) model, Digital elevation model