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

被引:13
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
[1]   Monitoring of coal mining subsidence in peri-urban area of Zonguldak city (NW Turkey) with persistent scatterer interferometry using ALOS-PALSAR [J].
Abdikan, Saygin ;
Arikan, Mahmut ;
Sanli, Fusun Balik ;
Cakir, Ziyadin .
ENVIRONMENTAL EARTH SCIENCES, 2014, 71 (09) :4081-4089
[2]   Estimation of north Tabriz fault parameters using neural networks and 3D tropospherically corrected surface displacement field [J].
Aghajany, Saeid Haji ;
Voosoghi, Behzad ;
Yazdian, Amir .
GEOMATICS NATURAL HAZARDS & RISK, 2017, 8 (02) :918-932
[3]   Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations [J].
Alshawaf, F. ;
Fersch, B. ;
Hinz, S. ;
Kunstmann, H. ;
Mayer, M. ;
Meyer, F. J. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2015, 19 (12) :4747-4764
[4]  
Altun AO, 2010, SCI RES ESSAYS, V5, P3206
[5]   Spatio-temporal evolution of Yellowstone deformation between 1992 and 2009 from InSAR and GPS observations [J].
Aly, Mohamed H. ;
Cochran, Elizabeth S. .
BULLETIN OF VOLCANOLOGY, 2011, 73 (09) :1407-1419
[6]   Non-negative least-squares variance component estimation with application to GPS time series [J].
Amiri-Simkooei, A. R. .
JOURNAL OF GEODESY, 2016, 90 (05) :451-466
[7]   Measurement of the three-dimensional surface deformation of the Jiaju landslide using a surface-parallel flow model [J].
Ao, Meng ;
Zhang, Lu ;
Shi, Xuguo ;
Liao, Mingsheng ;
Dong, Jie .
REMOTE SENSING LETTERS, 2019, 10 (08) :776-785
[8]   External Validation of the ASTER GDEM2, GMTED2010 and CGIAR-CSI-SRTM v4.1 Free Access Digital Elevation Models (DEMs) in Tunisia and Algeria [J].
Athmania, Djamel ;
Achour, Hammadi .
REMOTE SENSING, 2014, 6 (05) :4600-4620
[9]   Blasting injuries in surface mining with emphasis on flyrock and blast area security [J].
Bajpayee, TS ;
Rehak, TR ;
Mowrey, GL ;
Ingram, DK .
JOURNAL OF SAFETY RESEARCH, 2004, 35 (01) :47-57
[10]   Parallel Structure from Motion for Sparse Point Cloud Generation in Large-Scale Scenes [J].
Bao, Yongtang ;
Lin, Pengfei ;
Li, Yao ;
Qi, Yue ;
Wang, Zhihui ;
Du, Wenxiang ;
Fan, Qing .
SENSORS, 2021, 21 (11)