Monitoring of Land Subsidence Induced by Tunneling Works using Statistically Homogeneous Pixel (SHP) InSAR

Abstract

Tunnelling works in the construction of metro lines often induce ground subsidence, thus damaging facilities and threatening people s lives. Interferometric Synthetic Aperture Radar (InSAR) has become an important monitoring method for ground deformation. In previous studies, time series InSAR techniques, represented by StaMPS (Stanford Method for Persistent Scatterers), has been successfully applied to measure millimeter level ground subsidence in urban areas based on spaceborne SAR data stacks. However, several difficulties arise from the phase noise, the overestimate of interferometric coherence, and the great spatial-temporal variation of atmospheric phase delays in the coastal region. In this research, several modifications of StaMPS were proposed to address the above issues and form the “SHP StaMPS” algorithm. The improvements include: 1) adaptive multi-looking of interferograms based on Statistically Homogeneous Pixels (SHPs) without loss of Persistent Scatter (PS) candidates; 2) fine screening of PS candidates by adaptive thresholding of bias-mitigated coherence; 3) fine correction of atmospheric phase by combining GACOS (Generic Atmospheric Correction Online Service for InSAR) model and spatial-temporal filtering. A case study was carried out to monitor the land subsidence that occurred during the subway construction in Shenzhen, a coastal city in southeast China, using 52 acquisitions of Sentinel-1 TOPS SAR data acquired from 2016 to 2018. It was demonstrated that SHP StaMPS achieves higher accuracy than the original StaMPS. The derived displacement rates are in good agreement with the leveling measurements.