Abstract
The supply of coal is related to the stability of social development in China. Coal mining faces are generally located under farmland and wasteland to avoid destroying the livelihood and property of residents, which seriously affects the selection of permanent scatterer (PS) with time-series interferometric synthetic aperture radar (TS-InSAR) method. The advanced TS-InSAR (ATS-InSAR) method combining PS and distributed scatterer (DS) monitoring modules is a useful tool to increase measurement points. However, the number of DS and the accuracy of measurement are different with different thresholds of temporal coherence. On the basis of ATS-InSAR, we propose a modified method applying the multi-level processing strategy to obtain more reliable deformation information in this paper. 16 sentinel-1A images are used to monitor mining subsidence in Peixian, China. The results of three different methods are cross-verified. Meanwhile, reliable DS pixels are identified by using the thresholding of both temporal coherence and Pearson correlation coefficient through the hierarchical processing. The results show that the deformation of the modified method reveals a large subsidence with the maximum rate of -563 mm/yr. The number of measurement points selected by the modified method is about 6.6 times that of the TS-InSAR method, and 1.3 times that of the ATS-InSAR method. The modified strategy can extract a great number of reliable pixels and reduce error propagation to ensure measurement accuracy. This research offers information to relevant departments for risk management purpose.
Highlights
Coal is the most abundant and widely distributed conventional energy in the world
In this paper, the modified strategy is proposed to improve the ability of ATS-interferometric synthetic aperture radar (InSAR) stability monitoring in an area
All the image pixels are classified into four groups by thresholding the temporal coherence values and processed group-by-group applying the multi-level processing strategy. 16 images of Sentinel-1A data are used to detect mining subsidence
Summary
Coal is the most abundant and widely distributed conventional energy in the world. In recent years, the rapid development of electric power, building materials, chemical industry, and other industries has led to a substantial increase in the demand for coal in China [1]. Coal mining is to cause land subsidence, which brings geo-hazards and structural damage to people. Many domestic and foreign scholars have applied time-series SAR interferometry (TS-InSAR) techniques to monitor mining subsidence [3]–[10]. TS-InSAR techniques that are aimed to detect point-like targets with high reflectivity and slight influence of temporal and geometric decoherence, generally include two types, permanent scatterer (PS) interferometry with single master image and small baseline subset (SBAS) interferometry with multiple master images [11]–[18].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
