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金属矿山 ›› 2020, Vol. 49 ›› Issue (09): 173-178.

• 地质与测量 • 上一篇    下一篇

基于D-InSAR技术和改进GM(1,1)模型的矿区沉降监测与预计

石晓宇,魏祥平,杨可明,王 剑,姚树一   

  1. 1. 中国矿业大学(北京)地球科学与测绘工程学院,北京100083;2. 淮北矿业股份有限公司,安徽 淮北 235000
  • 出版日期:2020-09-15 发布日期:2020-10-19
  • 基金资助:
    中央高校基本科研业务费专项(编号:2009QD02);国家自然科学基金项目(编号:41971401)

Monitoring and Predicting the Subsidence of Mining Area Based on D-InSAR Technology and Improved GM(1,1) Models

SHI Xiaoyu,WEI Xiangping,YANG Keming,WANG Jian,YAO Shuyi   

  1. 1. College of Geoscience and Surveying Engineering,China University of Mining and Technology ( Beijing), Beijing 100083,China;2. Huaibei Mining Co., Ltd.,Huaibei 235000,China
  • Online:2020-09-15 Published:2020-10-19

摘要: 针对矿区地下资源大规模开采引发的地表沉陷,以淮北矿业集团袁二煤矿为试验区,联合合成孔径雷达差分干涉测量(D-InSAR)技术与灰色模型(GM(1,1)),建立了描述下沉量与时间关系的改进灰色模型,实现了地表沉降监测和预计的一体化。首先,基于哨兵一号A卫星(Sentinel-1A)影像,采用D-InSAR技术监测地面动态沉降过程,获得了2017年11月16日—2018年1月27日期间的时间序列沉降形变图;然后,依据所获取的各时间序列沉降量,建立了改进GM(1,1)的补偿最小二乘法估计半参数模型(BGM(1,1))和赋相对权重的补偿最小二乘法估计半参数模型(WGM(1,1))方程,实现了沉降值的拟合与预计。试验表明:D-InSAR技术在矿区地面沉降动态监测中具有明显优势,且其监测精度达毫米级;BGM(1,1)和WGM(1,1)预计模型均可弥补经典GM(1,1)模型的不足,结合WGM(1,1)预测的4个试验点的相对误差为1.99%~26.64%,可为矿区地面沉陷动态监测以及后续治理提供理论依据,具有一定的预警作用和借鉴意义。

关键词: 开采沉陷, D-InSAR, GM(1, 1)模型, 监测与预计

Abstract: Aiming at the problem of surface subsidence caused by large-scale mining of underground resources in mining area, an improved grey model describing the relationship between subsidence and time was proposed by taking Yuan'er Coal Mine of Huaibei Mining Group as the test area and combining differential synthetic aperture radar interferometry (D-InSAR) and grey model (GM (1,1)),which realizes the integration of monitoring and prediction of surface subsidence.The detail steps can be described as follows: firstly, in view of Sentinel-1A satellite and D-InSAR technology, the settlement deformation maps of the study area in different periods from November 16, 2017 to January 27, 2018 were obtained to analyze the process of dynamic subsidence. Then, according to the settlement value of different time series, the semi-parametric GM(1,1) model estimated by compensated least squares method(BGM(1,1)) and compensated least squares method with relative weight(WGM(1,1)) were established to fit and predict the settlement value.The test results show that D-InSAR technology has obvious advantages in dynamic monitoring of land subsidence in mining area, and its monitoring accuracy reaches millimeter level; in addition, BGM (1,1) and WGM (1,1) prediction models make up for the shortcomings of classical GM (1,1) model, the relative error of four test points predicted by WGM (1,1) is 1.99%~26.64%. The study can provide a theoretical basis for dynamic monitoring and subsequent treatment of ground subsidence in mining areas, furthermore, it has certain significance early warning function and reference.

Key words: mining subsidence, D-InSAR, GM(1, 1) model, monitoring and prediction