Mining large-gradient subsidence monitoring using D-InSAR optimized by GNSS. (19th May 2021)

• Record Type: Journal Article
• Authors: Fan, Haodi; Lian, Xugang; Yang, Wenfu; Ge, Linlin; Hu, Haifeng; Du, Zheyuan
• Is Part Of: Imaging science journal. Volume 69:Number 1/4(2021)
• Page Start: 207
• Page End: 218
• Publication Date: 2021-05-19
• Subjects: Mine -- large-gradient -- subsidence -- monitoring -- GNSS -- D-InSAR -- weight total least-squares method -- optimization; Imaging systems -- Periodicals; 621.36705
• DOI: 10.1080/13682199.2022.2156667
• Languages: English
• ISSNs: 1368-2199

Abstract

ABSTRACT: In the process of developing mine resources, mining subsidence is inevitable. The D-InSAR (differential interferometric synthetic aperture radar) technology has been widely used to monitor large-scale ground subsidence in mining areas in recent years. However, the limitations of this technology mean that large-gradient ground subsidence cannot be monitored. This paper describes a weighted total least-squares method that can be used to determine the piecewise linear mapping between GNSS (global navigation satellite system) data and D-InSAR data. This mapping can be applied to optimize the conventional D-InSAR monitoring results, particularly in large-gradient subsidence areas, enabling the mining subsidence to be comprehensively evaluated. The proposed method is used to extract the surface subsidence information for a certain area of the Sihe mine in Shanxi Province, China. It is found that the optimized data is more reliable and accurate than the conventional D-InSAR monitoring data in the case of large-gradient subsidence.