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Remote Sens. 2017, 9(9), 897; doi:10.3390/rs9090897

Elevation Extraction and Deformation Monitoring by Multitemporal InSAR of Lupu Bridge in Shanghai

1
College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China
2
Department of Land Surveying and Geo-Informatics, Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hong Kong, China
3
Shenzhen Water Science and Technology Development Company, Shenzhen 518000, China
*
Author to whom correspondence should be addressed.
Academic Editors: Timo Balz, Uwe Soergel, Mattia Crespi, Batuhan Osmanoglu, Zhong Lu and Prasad S. Thenkabail
Received: 11 July 2017 / Revised: 4 August 2017 / Accepted: 28 August 2017 / Published: 30 August 2017
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications)
View Full-Text   |   Download PDF [10266 KB, uploaded 30 August 2017]   |  

Abstract

Monitoring, assessing, and understanding the structural health of large infrastructures, such as buildings, bridges, dams, tunnels, and highways, is important for urban development and management, as the gradual deterioration of such structures may result in catastrophic structural failure leading to high personal and economic losses. With a higher spatial resolution and a shorter revisit period, interferometric synthetic aperture radar (InSAR) plays an increasing role in the deformation monitoring and height extraction of structures. As a focal point of the InSAR data processing chain, phase unwrapping has a direct impact on the accuracy of the results. In complex urban areas, large elevation differences between the top and bottom parts of a large structure combined with a long interferometric baseline can result in a serious phase-wrapping problem. Here, with no accurate digital surface model (DSM) available, we handle the large phase gradients of arcs in multitemporal InSAR processing using a long–short baseline iteration method. Specifically, groups of interferometric pairs with short baselines are processed to obtain the rough initial elevation estimations of the persistent scatterers (PSs). The baseline threshold is then loosened in subsequent iterations to improve the accuracy of the elevation estimates step by step. The LLL lattice reduction algorithm (by Lenstra, Lenstra, and Lovász) is applied in the InSAR phase unwrapping process to rapidly reduce the search radius, compress the search space, and improve the success rate in resolving the phase ambiguities. Once the elevations of the selected PSs are determined, they are used in the following two-dimensional phase regression involving both elevations and deformations. A case study of Lupu Bridge in Shanghai is carried out for the algorithm’s verification. The estimated PS elevations agree well (within 1 m) with the official Lupu Bridge model data, while the PS deformation time series confirms that the bridge exhibits some symmetric progressive deformation, at 4–7 mm per year on both arches and 4–9 mm per year on the bridge deck during the SAR image acquisition period. View Full-Text
Keywords: deformation monitoring; elevation extraction; InSAR; LLL lattice reduction; long–short baseline iteration; Lupu Bridge deformation monitoring; elevation extraction; InSAR; LLL lattice reduction; long–short baseline iteration; Lupu Bridge
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhao, J.; Wu, J.; Ding, X.; Wang, M. Elevation Extraction and Deformation Monitoring by Multitemporal InSAR of Lupu Bridge in Shanghai. Remote Sens. 2017, 9, 897.

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