Health diagnosis of major transportation infrastructures in Shanghai metropolis using high- resolution persistent scatterer interferometry

Health diagnosis of major transportation infrastructures in Shanghai metropolis using high- resolution persistent scatterer interferometry

Qin, Xiaoqiong (Wuhan University; Ministry of Land and Resources)
Yang, M. (TU Delft Mathematical Geodesy and Positioning; Wuhan University)
Zhang, L. (Wuhan University)
Yang, Tianliang (Ministry of Land and Resources; Shanghai Institute of Geological Survey)
Liao, Mingsheng (Wuhan University; Ministry of Land and Resources)

2017-12-01

Since the Persistent Scatterer Synthetic Aperture Radar (SAR) Interferometry (PSI) technology allows the detection of ground subsidence with millimeter accuracy, it is becoming one of the most powerful and economical means for health diagnosis of major transportation infrastructures. However, structures of different types may suffer from various levels of localized subsidence due to the different structural characteristics and subsidence mechanisms. Moreover, in the complex urban scenery, some segments of these infrastructures may be sheltered by surrounding buildings in SAR images, obscuring the desirable signals. Therefore, the subsidence characteristics on different types of structures should be discussed separately and the accuracy of persistent scatterers (PSs) should be optimized. In this study, the PSI-based subsidence mapping over the entire transportation network of Shanghai (more than 10,000 km) is illustrated, achieving the city-wide monitoring specifically along the elevated roads, ground highways and underground subways. The precise geolocation and structural characteristics of infrastructures were combined to effectively guide more accurate identification and separation of PSs along the structures. The experimental results from two neighboring TerraSAR-X stacks from 2013 to 2016 were integrated by joint estimating the measurements in the overlapping area, performing large-scale subsidence mapping and were validated by leveling data, showing highly consistent in terms of subsidence velocities and time-series displacements. Spatial-temporal subsidence patterns on each type of infrastructures are strongly dependent on the operational durations and structural characteristics, as well as the variation of the foundation soil layers.

Deformation
High-resolution InSAR
Large infrastructures
Shanghai

http://resolver.tudelft.nl/uuid:5bd0b964-ed2d-463b-bcdf-d61221a0a259

https://doi.org/10.3390/s17122770

1424-8220

Sensors, 17 (12)

Institutional Repository

journal article

© 2017 Xiaoqiong Qin, M. Yang, L. Zhang, Tianliang Yang, Mingsheng Liao