ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume IV-3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 53–59, 2018
https://doi.org/10.5194/isprs-annals-IV-3-53-2018
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 53–59, 2018
https://doi.org/10.5194/isprs-annals-IV-3-53-2018

  23 Apr 2018

23 Apr 2018

ANALYSIS OF MINING-INDUCED SUBSIDENCE PREDICTION BY EXPONENT KNOTHE MODEL COMBINED WITH INSAR AND LEVELING

Lei Chen1, Liguo Zhang2, Yixian Tang3, and Hong Zhang3 Lei Chen et al.
  • 1College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
  • 2Shandong provincial institute of land surveying and mapping, Jinan, 250102, China
  • 3Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, CAS, Beijing, 100094, China

Keywords: InSAR, Levelling, Exponent Knothe Model, Mining-induced Subsidence, Fitting, Prediction

Abstract. The principle of exponent Knothe model was introduced in detail and the variation process of mining subsidence with time was analysed based on the formulas of subsidence, subsidence velocity and subsidence acceleration in the paper. Five scenes of radar images and six levelling measurements were collected to extract ground deformation characteristics in one coal mining area in this study. Then the unknown parameters of exponent Knothe model were estimated by combined levelling data with deformation information along the line of sight obtained by InSAR technique. By compared the fitting and prediction results obtained by InSAR and levelling with that obtained only by levelling, it was shown that the accuracy of fitting and prediction combined with InSAR and levelling was obviously better than the other that. Therefore, the InSAR measurements can significantly improve the fitting and prediction accuracy of exponent Knothe model.