An Improved GNSS and InSAR Fusion Method for Monitoring the 3D Deformation of a Mining Area

被引:14
作者
Zhou, Wentao [1 ,2 ]
Zhang, Wenjun [1 ,2 ]
Yang, Xinchun [3 ]
Wu, Weiqiang [1 ,2 ]
机构
[1] Southwest Univ Sci & Technol, Sch Environm & Resource, Mianyang 621010, Sichuan, Peoples R China
[2] Natl Remote Sensing Ctr China, Mianyang S&T City Div, Mianyang 621010, Sichuan, Peoples R China
[3] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 611756, Peoples R China
基金
中国国家自然科学基金;
关键词
Strain; Global navigation satellite system; Extraterrestrial measurements; Monitoring; Geologic measurements; Area measurement; Satellites; GNSS; InSAR; HVCE-BPNN method; three-dimensional deformation; mining subsidence; SURFACE DEFORMATION; 3-DIMENSIONAL DEFORMATION; NEURAL-NETWORK; FIELD; INTERFEROMETRY; EARTHQUAKE; SUBSIDENCE; COMPONENT; LANDSLIDE; SECURITY;
D O I
10.1109/ACCESS.2021.3129521
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Accurate measurement of the surface three-dimensional deformation fields in a mined-out area is essential for understanding the law of mining subsidence and guiding the safe production and construction of mining areas. In this study, we proposed an improved fusion method to monitor this three-dimensional deformation. We used the Helmert variance component estimation (HVCE) method and the back-propagation neural network (BPNN) to fuse the global navigation satellite system (GNSS) and interferometric synthetic aperture radar (InSAR) measurements. Based on this improved fusion method, we measured the three-dimensional deformation in the West Second Mining Area of Jinchuan, Jinchang City, Gansu Province, China, from March 22, 2019, to June 8, 2020. The root mean square errors (RMSEs) based on our method for the three directions of east-west (E-W), north-south (N-S), and up-down (U-D) were 21.4 mm, 7.6 mm, and 34.2 mm, respectively. These RMSE values are lower than those obtained from previous methods. The results show that the spatial distribution of the three-dimensional deformation follows the law of mining subsidence.
引用
收藏
页码:155839 / 155850
页数:12
相关论文
共 66 条
[61]   Use of Multiplatform SAR Imagery in Mining Deformation Monitoring with Dense Vegetation Coverage: A Case Study in the Fengfeng Mining Area, China [J].
Zhang, Bochen ;
Wu, Songbo ;
Ding, Xiaoli ;
Wang, Chisheng ;
Zhu, Jiasong ;
Li, Qingquan .
REMOTE SENSING, 2021, 13 (16)
[62]   Optimization of three-dimensional multi-level surface deformation in mining areas through integration of deformation fusion model and Lagrange multiplier method based on single high resolution OTD-InSAR pair [J].
Zhang, Lele ;
Liu, Bo ;
Wang, Ying ;
Jia, Shili .
MEASUREMENT, 2021, 174 (174)
[63]   A Novel Weighting Approach for Variance Component Estimation in GPS/BDS PPP [J].
Zhang, Qieqie ;
Zhao, Long ;
Zhou, Jianhua .
IEEE SENSORS JOURNAL, 2019, 19 (10) :3763-3771
[64]   Analysis of Pre- and Post-Mine Closure Surface Deformations in Western Xuzhou Coalfield From 2006 to 2018 [J].
Zheng, Meinan ;
Zhang, Hongzhen ;
Deng, Kazhong ;
Du, Sen ;
Wang, Liuyu .
IEEE ACCESS, 2019, 7 :124158-124172
[65]   Monitoring and Analysis of Surface Deformation in Mining Area Based on InSAR and GRACE [J].
Zheng, Meinan ;
Deng, Kazhong ;
Fan, Hongdong ;
Du, Sen .
REMOTE SENSING, 2018, 10 (09)
[66]  
[周文韬 Zhou Wentao], 2021, [大地测量与地球动力学, Journal of Geodesy and Geodynamics], V41, P308