Research on Large-scale Mining Collapse Monitoring with InSAR Technology
|Course||Geodesy and Survey Engineering|
|Keywords||InSAR Small Baseline Subset Collapse Inversion Monitoring|
Interferometric Synthetic Aperture Radar (InSAR) is a new type of space-to-earth observation technology, which is developed on the basis of SAR in the late 1990s. It uses the SAR phase information to obtain accurate topographic and deformation information in various time span. InSAR technology has unique advantage to monitoring tiny surface deformation with its all-weather, all- covering a broad area, and high degree of automation monitoring ground deformation capacity. However, there are several special characteristics on mining collapse, such as large scale subsidence, frequent ground activities, serious temporal decorrelation and other factors. This is undoubtedly a great challenge for using InSAR to monitor coal mining collapse. This paper studied on algorithms to improve the InSAR monitoring precision on mining collapse area. In order to explain the reason and law of mining collapse, we use the dislocation model to do the inversion.Firstly, the paper introduces the principle and processing flow chart of InSAR and D-InSAR, then analyzes the particularity of InSAR technology for mining subsidence monitoring, compares the mining subsidence monitoring ability of L-band ALOS data and C-band ENVISAT data.Secondly, we focused on two typical mining regions located on Wulanmulun town, Inner Mongolia. In order to overcome DEM error, baseline inaccuracy and atmospheric inhomogeneity, we applied Small Baseline Subsets (SBAS) technique to achieve collapse time-series during December 2006 to August 2009 using ALOS data. In order to validate and contrast, using ENVISAT data to obtain collapse time-series during June 2007 to Septembe r 2010. By calculating the cumulative area of subsidence and plotting the cross-section to sum up some rules of coal mining subsidence.Thirdly, we apply Dislocation (Okada) model combined with underground galleries maps to derive the dike opening values, and analyze the relationship of mining depth, mining thickness and dike opening, thus enhancing the understanding of the mine collapse law, forecasting and prevention the disasters.Lastly, we put forward three methods to improve the large gradient limitation of InSAR. The first method is to improve the registration accuracy by eliminating registration offset outliers. The second method is to increase the maximum detectable deformation by reducing the pixel size or using full resolution interferometry. The third method is to improve phase unwrapping precision by removing and recovering act combined with the dislocation model.