4.7 Article

Three-dimensional time-varying large surface displacements in coal exploiting areas revealed through integration of SAR pixel offset measurements and mining subsidence model

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 240, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2020.111663

Keywords

Synthetic aperture radar; Deformation monitoring; Coal mining; Pixel offset tracking; Time series analysis; Time-varying displacement

Funding

  1. Natural Science Foundation of China [41702375, 51574132, 41671395]
  2. Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
  3. Basic Research Program of Jiangsu Province (Natural Science Foundation) [BK20160218]
  4. Hunan Province Key Laboratory Foundation of Coal Resources Clean-utilization and Mine Environment Protection [E21801]
  5. Natural Science Foundation of Jiangsu Province [BK20181474]
  6. Research Project of Jiangsu Normal University [15XLR018]
  7. UK NERC through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) [come30001]
  8. LICS project [NE/K010794/1]
  9. CEDRRIC project [NE/N012151/1]
  10. European Space Agency through the ESA-MOST DRAGON-4 project [32244]
  11. NERC [NE/K010794/1, NE/N012151/1, come30001] Funding Source: UKRI

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Underground mining activities usually induce large surface displacements thus causing serious safety hazards and potential ecological damage. The capability of conventional Interferometric Synthetic Aperture Radar (InSAR) to monitor tectonic movements, volcanic eruptions and city subsidence has been fully demonstrated, but its application to mining subsidence is limited because of the failure caused by localized surface displacements with strong spatial gradients. In this paper, a new method is presented to utilize SAR pixel Offset Tracking (OT) with a single pair of SAR images to resolve three-dimensional (3D) large surface displacements caused by underground coal mining. Coal mining subsidence theory is utilised to analytically separate the vertical and horizontal components. This method is applied to the Daliuta coal mining area in Shaanxi Province, China, where a dense GPS network is available. Results show the RMS differences of OT derived displacements against GPS in both horizontal and vertical directions are in the sub-centimeter level. In addition, a prediction of mining-induced ground movements is performed with the Support Vector Regression algorithm and RMS differences of 12.4, 13.1 and 14.4 cm are observed compared to GPS, in the vertical, easting and northing directions respectively. The framework demonstrated in this paper is not only able to derive the evolution of the 3D large surface displacements with multi-temporal SAR images in a single-geometry, but also has a potential for short-term predication, which can provide early warnings and promote strategic decision-making for engineering management in the process of coal mining.

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