Article
Remote Sensing
Hongdong Fan, Tengteng Li, Yantao Gao, Kazhong Deng, Hongan Wu
Summary: This paper proposes a method for locating and inversion of underground goaf based on a combination of InSAR techniques and PIM model. Through simulation and empirical analysis, the underground goaf is successfully detected with good results.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Geochemistry & Geophysics
Jian Wang, Li Yan, Keming Yang, Wei Tang, Hong Xie, Shuyi Yao, Zhihua Xu, Jianbing Yang
Summary: This study proposes a novel method based on InSAR to accurately estimate mining-induced 3-D surface deformations. The method integrates single InSAR interferogram, the Gompertz time function, and the probability integral model to derive the deformations at any moment. Experimental results demonstrate the accuracy of the method in subsidence, tilt, curvature, displacement, and strain, and its ability to accurately estimate deformations under different geological conditions.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Yang Chen, Shengwen Yu, Qiuxiang Tao, Guolin Liu, Luyao Wang, Fengyun Wang
Summary: InSAR was used to monitor surface subsidence in a mining area in Shandong Province, China. While InSAR can accurately detect the location, range, and spatial change trend of subsidence, it has limitations in detecting the subsidence center and areas with high displacement rates. By establishing a correction model based on the distance from leveling points to the subsidence center, more accurate monitoring results consistent with the actual situation were obtained.
Article
Environmental Sciences
Zhixian Hou, Keming Yang, Yanru Li, Wei Gao, Shuang Wang, Xinming Ding, Yaxing Li
Summary: Obtaining timely and accurate information of surface subsidence caused by mining is of great significance. The Probability Integral Method (PIM) model is widely used for mining subsidence prediction in China, but it has fast convergence issues at the edge of subsidence basin. The existing models also have difficulties in obtaining accurate information on large gradient subsidence and have defects in dynamic prediction. In this paper, an Improved PIM (IPIM) prediction model and IPIM-G dynamic prediction model were proposed, and parameters were inverted using D-InSAR technology for subsidence monitoring to improve prediction accuracy. The results show that the proposed model can provide theoretical support for mining and production planning.
ENVIRONMENTAL EARTH SCIENCES
(2022)
Article
Environmental Sciences
Zhihong Wang, Huayang Dai, Yueguan Yan, Jibo Liu, Jintong Ren
Summary: A three-dimensional deformation monitoring method based on single line-of-sight interferometric synthetic aperture radar technology is proposed to obtain detailed and accurate deformation information of a subsidence basin. By combining InSAR with the surface displacement vector depression angle model, this method can achieve more precise monitoring and better consistency with actual situations compared to traditional InSAR and PIM methods.
Article
Environmental Sciences
Mengyao Shi, Honglei Yang, Baocun Wang, Junhuan Peng, Zhouzheng Gao, Bin Zhang
Summary: This study introduces a new method for estimating mining subsidence based on TS-InSAR results, improving boundary constraints and dynamic parameter estimation in the PIM. The experiment demonstrates that the proposed method is more accurate in detecting displacement in mining areas.
Article
Chemistry, Multidisciplinary
Bang Zhou, Yueguan Yan, Jianrong Kang
Summary: In this study, a dynamic prediction model based on MMF (Morgan-Mercer-Flodin) time function was proposed to accurately predict the progressive surface subsidence caused by coal mining. Compared with other time functions, the prediction accuracy using MMF time function is higher, which can meet the requirements of practical engineering applications and provide good guidance for dynamic prediction during the coal mining process.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Aerospace
Keming Yang, Zhixian Hou, Xiangping Wei, Wei Gao, Yanru Li, Xinming Ding, Shuang Wang, Yaxing Li, Hengqian Zhao
Summary: The prediction of surface movement and deformation in the mining area is crucial for mining production. Traditional D-InSAR technology and PIM prediction models have limitations, hence a BPIM dynamic prediction model based on the PIM model was proposed in this study. The parameters of the BPIM model were determined by inverting D-InSAR monitoring data using an optimization algorithm, and the temporal and spatial characteristics of the mining area were dynamically predicted. The results demonstrated that the BPIM model accurately predicted deformation under subcritical extraction and provided valuable suggestions for mining area planning and production.
ADVANCES IN SPACE RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Zhihong Wang, Huayang Dai, Yueguan Yan, Jintong Ren, Jibo Liu, Yanjun Zhang, Guosheng Xu
Summary: This study explores ground point deformation along the strike line from the perspectives of dynamic subsidence and dynamic horizontal movement, developing prediction models based on the probability integral method and surface deformation features. Utilizing characteristic constraints, the Richards time function is applied to establish accurate time functions for dynamic subsidence and horizontal movement. Experimental findings demonstrate high accuracy of the prediction models under constraints.
Article
Engineering, Electrical & Electronic
Yu Chen, Jie Li, Huaizhan Li, Yandong Gao, Shijin Li, Si Chen, Guangli Guo, Fangtian Wang, Dongsheng Zhao, Kefei Zhang, Peiling Li, Kun Tan, Peijun Du
Summary: Regularly monitoring the surface deformation of filling coal mines and understanding their spatiotemporal evolution characteristics is important for mining management and disaster warning. However, there is a lack of research on extracting spatiotemporal evolution characteristics of large-scale and high-resolution surface deformation in backfill mining areas and on evaluating the filling effectiveness of subsidence restraint. In this study, the DS InSAR technique was used for time-series analysis in the Yineng Coal Mine in China. The results show that the proposed integration strategy improves monitoring and provides information on the surface deformation of the working face. Backfilling mining effectively reduces subsidence and threat to surface buildings.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Tao Wei, Guangli Guo, Huaizhan Li, Lei Wang, Qian Jiang, Chunmei Jiang
Summary: Based on literature study, this research summarizes and analyzes the influence of thick loose layer on the predicted parameters of the probability integral method. By considering the influence of the subsidence coefficient, a sine modification formula for the main influence radius and a logistic modification formula for the subsidence coefficient are established. A new subsidence basin demarcation point and a novel probability integral method segmental parameter modified prediction model are proposed. Simulated and real data experiments prove that the constructed model can reduce the convergence of surface subsidence basin edge and accurately predict subsidence inside the basin. The research findings provide scientific support for disaster warning, pollution management, ecological restoration, and coordination between coal mining and surface city construction in thick loose layer mining areas.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Environmental Sciences
Yaozong Xu, Tao Li, Xinming Tang, Xiang Zhang, Hongdong Fan, Yuewen Wang
Summary: The study conducted deformation observation experiments in the Datong coalfield using DInSAR, stacking-InSAR, and SBAS-InSAR methods and found that stacking-InSAR is an effective and efficient method for identifying the location and shape of mining deformations.
Article
Environmental Sciences
Xuemin Xing, Tengfei Zhang, Lifu Chen, Zefa Yang, Xiangbin Liu, Wei Peng, Zhihui Yuan
Summary: This paper introduces a new InSAR deformation modeling approach called CT-PIM, which has been tested using simulated and real data experiments. The results show a 37.2% improvement in prediction accuracy compared to traditional static PIM methods. This new approach provides a more robust tool for predicting mining-induced hazards in salt solution mining areas.
Article
Environmental Sciences
Hengyi Chen, Chaoying Zhao, Roberto Tomas, Liquan Chen, Chengsheng Yang, Yuning Zhang
Summary: The study combines SAR offset tracking and interferometric phase to obtain the large-gradient surface displacement. A multi-segment logistic model is proposed to simulate the temporal effect induced by repeated mining activities. The simplified probability integral method (SPIM) is used to separate the displacement of mining subsidence and landslide and assess their impact. The results show that repeated mining activities not only cause land subsidence and rock avalanches, but also accelerate landslide displacement.
Article
Environmental Sciences
Rui Wang, Kan Wu, Qimin He, Yibo He, Yuanyuan Gu, Shuang Wu
Summary: The probability integral model was used to process deformation data obtained from UAV, DInSAR, and SBAS-InSAR to obtain a complete deformation field. The results showed that the subsidence basin gradually expanded along the mining direction as the working face advanced, reaching a maximum subsidence value of 2.780 m under supercritical conditions. The fusion of various remote sensing data was used to construct a high-precision subsidence basin.
Article
Remote Sensing
Bingqian Chen, Kazhong Deng, Hongdong Fan, Yang Yu
EUROPEAN JOURNAL OF REMOTE SENSING
(2015)
Article
Computer Science, Information Systems
Ming Hao, Zhang Hua, Zhenxuan Li, Bingqian Chen
MULTIMEDIA TOOLS AND APPLICATIONS
(2017)
Article
Engineering, Civil
B. Q. Chen, K. Z. Deng
Article
Metallurgy & Metallurgical Engineering
Hong-dong Fan, Wei Gu, Yong Qin, Ji-qun Xue, Bing-qian Chen
TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA
(2014)
Article
Environmental Sciences
Xiang Luo, Liang Liang, Zhixiao Liu, Jiahui Wang, Ting Huang, Di Geng, Bingqian Chen
POLISH JOURNAL OF ENVIRONMENTAL STUDIES
(2020)
Article
Environmental Sciences
Bingqian Chen, Zhenhong Li, Chen Yu, David Fairbairn, Jianrong Kang, Jinshan Hu, Liang Liang
REMOTE SENSING OF ENVIRONMENT
(2020)
Article
Environmental Sciences
Bingqian Chen, Han Mei, Zhenhong Li, Zhengshuai Wang, Yang Yu, Hao Yu
Summary: The combination of SAR pixel offset tracking (OT) and an improved mining subsidence model allows for monitoring of three-dimensional large surface displacements in mining areas effectively.
Article
Engineering, Electrical & Electronic
Liang Liang, Ting Huang, Liping Di, Di Geng, Juan Yan, Shuguo Wang, Lijuan Wang, Li Li, Bingqian Chen, Jianrong Kang
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2020)
Article
Mining & Mineral Processing
Chen Bingqian, Deng Kazhong, Fan Hongdong, Hao Ming
INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY
(2013)
