We propose a method that integrates fuzzy set theory and a weighted Bayesian model to evaluate the hazard probability of land subsidence based on Interferometric Synthetic Aperture Radar technology. The proposed model can represent the uncertainty and ambiguity in the evaluation process, and results can be compared to traditional qualitative methods.

Land subsidence is a serious geo-hazard in Beijing Plain, which has threatened the safety of the operation of the metropolis. This study derived the vertical and the East-West deformation, and the spatial variation and the impact factors of the vertical and the East-West deformation were analyzed. It found that the extraction of groundwater is the dominant factor affecting the spatial distribution of the vertical displacement, while the dominant factor of East-West deformation is not obvious.

To overcome the problem that layover scatterers with no amplitude stability and spatial coherence are lead to reliability insufficient and accuracy reduction in monitoring urban land subsidence, we applied the Fast Fourier Transform to convert Persistent Scatterers to frequency domain during the PS-InSAR identification process. The method could identify and separate single and layover scatterers, reduced the effect of layover scatterers, improved the accuracy of urban land subsidence monitoring.