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Mining large-gradient subsidence monitoring using D-InSAR optimized by GNSS.

Authors :
Fan, Haodi
Lian, Xugang
Yang, Wenfu
Ge, Linlin
Hu, Haifeng
Du, Zheyuan
Source :
Imaging Science Journal. Feb-Jun2021, Vol. 69 Issue 1-4, p207-218. 12p.
Publication Year :
2021

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13682199
Volume :
69
Issue :
1-4
Database :
Academic Search Index
Journal :
Imaging Science Journal
Publication Type :
Academic Journal
Accession number :
162174410
Full Text :
https://doi.org/10.1080/13682199.2022.2156667