An Efficient and Fully Refined Deformation Extraction Method for Deriving Mining-Induced Subsidence by the Joint of Probability Integral Method and SBAS-InSAR

This study proposes a novel approach to derive the mining-induced goaf deformation, named the fully refined deformation extraction method (FRDEM). In this method, the probability integral method (PIM) and the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique are geographically integrated in a low-cost way to derive the fully refined goaf deformation and, therefore, to improve the detection ability for mining subsidence with fast deformation rate and large gradient. To achieve this, we first established a functional relationship model to connect the 3-D parameters of PIM with SBAS-InSAR. Then, an improved genetic algorithm (IGA) was presented for parameter inversion, and thus, the optimal parameter set for PIM and the predicted displacements of the mining goaf was achieved economically. Afterward, we developed a geographically weighted data fusion model by presenting a data fusion strategy to eliminate the spatial heterogeneity in goaf boundary areas, and the fully refined goaf deformation field for the working face 2302 in the Guotun coal mining area was finally derived. Results demonstrate that FRDEM-derived displacements are highly consistent with field measurements, with root-mean-square error (RMSE) decreasing to 0.053, 0.057, and 0.044 m, respectively, for the entire goaf, goaf center, and goaf boundary field, compared with those of
$\sim $
0.092,
$\sim $
0.095, and
$\sim $
0.084 m for PIM and
$\sim $
0.578,
$\sim $
0.696, and
$\sim $
0.046 m for SBAS-InSAR, respectively. This implies that the proposed FRDEM has significantly improved the detection ability in deriving the mining-induced deformation and, thus, can be a very promising tool to forecast and evaluate potential geohazards in the coal mining area.