Deriving time-series three-dimensional displacements of mining areas from a single-geometry InSAR dataset
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This paper presents a method for deriving time-series three-dimensional (3-D) displacements of mining areas from a single-geometry interferometric synthetic aperture radar (InSAR) dataset (hereafter referred to as the SGI-based method). This is mainly aimed at overcoming the limitation of the traditional multi-temporal InSAR techniques that require SAR data from at least three significantly different imaging geometries to fully retrieve time-series 3-D displacements of mining areas. The SGI-based method first generates the multi-temporal observations of the mining-induced vertical subsidence from the single-geometry InSAR data, using a previously developed method for retrieving 3-D mining-related displacements from a single InSAR pair (SIP). The weighted least-squares solutions of the time series of vertical subsidence are estimated from these generated multi-temporal observations of vertical subsidence. Finally, the time series of horizontal motions in the east and north directions are estimated using the proportional relationship between the horizontal motion and the subsidence gradient of the mining area, on the basis of the SGI-derived time series of vertical subsidence. Seven ascending ALOS PALSAR images from the Datong mining area of China were used to test the proposed SGI-based method. The results suggest that the SGI-based method is effective. The SGI-based method not only extends the SIP-based method to time-series 3-D displacement retrieval from a single-geometry InSAR dataset, but also limits the uncertainty propagation from InSAR-derived deformation to the estimated 3-D displacements.
Keywords3-D displacements Mining subsidence InSAR SAR Time series
The work was supported by the National Natural Science Foundation of China (Nos. 41474008, 41474007, and 41404013), the Hunan Provincial Natural Science Foundation of China (No. 13JJ1006), the Primary Research & Development Plan of Hunan Province (No. 2016SK2002), the Major Projects of High Resolution Earth Observation System of China (Civil Part) (No. 03-Y20A11-9001-15/16), the NASG Key Laboratory of Land Environment and Disaster Monitoring (No. LEDM2014B07), and the China Scholarship Council (No. 201506370139). The authors would also like to thank the Japan Aerospace Exploration Agency (JAXA) for providing the PALSAR images of the study area (Nos. 582 and 1390).
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