Monitoring Subsidence Deformation of Suzhou Subway Using InSAR Timeseries Analysis

Xiaobo Xu,Dajun Lian,Dezheng Zhao,Chao Ma

doi:10.1109/access.2020.3047574

Abstract

Subway subsidence and the consequent geological hazards have become one of the major concerns especially in China's large cities. Large spatial-scale and temporally continuous measurements of surface deformation due to subway subsidence is the basis of the intelligent management for urban transit, as well as the guarantee for the early warning of geological disasters. In this paper, we used persistent scatterer interferometric synthetic aperture radar (PS InSAR) measurements to study and characterize the deformation process resulted from subway-induced subsidence in the construction and operation periods of Suzhou subway using 24-scene high-resolution TerraSAR data (from December 2009 to April 2015) and 19-scene low-resolution Sentinel-1A SAR data (from May 2017 to February 2020). Our results indicate spatially different subsidence rates at different segments along the Suzhou subway lines 1, 2, 3, 4, 5 and 6. TerraSAR data indicate the maximum subsidence rate of -13 mm/yr, while Sentinel-1A data demonstrate the maximum subsidence rate of -20 mm/yr. The decadal-scale subway subsidence deformation is generally characterized by its multistage dynamic processes. The significant subway subsidence is mainly distributed around interchange hubs at the intersection area of railway lines. The Peck function model is used to fit the subway subsidence displacement profiles, which reveals the normal distribution characteristics of the subway surface subsidence. Based on our timeseries analysis in different time periods, the logistic cycle function is used to invert the subway subsidence timing, which reveals four first-order stages during subway subsidence: slow acceleration period, fast acceleration period, decay period and steady-state period.

Highlights

Subway plays an important role in modern urban traffic systems, which to a great extent helps to relieve pressure of the ground traffic for large cities
In this paper, we used high-resolution TerraSAR data from 2009 to 2015 and the low-resolution Sentine-1A SAR data from 2017 to 2020 to measure the subsidence of Suzhou subway in Jiangsu Province, China based on PS InSAR method
We analyzed the subsidence of different subway lines based on subsidence velocity field, InSAR time series and some subsidence profiles

Summary

INTRODUCTION

Subway plays an important role in modern urban traffic systems, which to a great extent helps to relieve pressure of the ground traffic for large cities. We used PS InSAR to study the subsidence during the construction and operation period of Suzhou subway using 24 X-band TerraSAR images from December 2009 to April 2015 and 19 C-band Sentinel-1A images from May 2017 to February 2020. B. SAR DATA We use 24 high-resolution TerraSAR images from December 2009 to April 2015 (6 years), and 19 Sentinel-1A SAR images from May 2017 to February 2020 (3 years) to measure the subsidence of Suzhou subway. PS InSAR technique [29]–[31] is a widely used approach used to measure and continuously monitor small-magnitude surface deformation, including subsidence deformation, produced by anthropogenic activities in cities It analyzes both the amplitude and phase information contained in the radar return signal reflected from identified persistent scatterers (phase-stable targets) such as roads, bridges, or motorways. Appropriate spatiotemporal baseline distribution ensures good coherence of the interferometric pairs, which is suitable for PS InSAR processing [38]–[40]

MODELING METHOD

REGIONAL SUBWAY SUBSIDENCE

SPATIAL DISTRIBUTION CHARACTERISTICS OF

CONCLUSION