Expressway deformation mapping using high-resolution TerraSAR-X images

• Published in: Remote Sensing Letters
• Main Authors: Shi, Xuguo, Liao, Mingsheng, Wang, Teng, Zhang, Lu, Shan, Wei, Wang, Chunjiao
• Other Authors: Earth Science and Engineering Program, Physical Science and Engineering (PSE) Division, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China, Engineering Consulting and Design Institute, Northeast Forestry University, Harbin, China
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Informa UK Limited 2014
• Subjects: permafrost
• Online Access: http://hdl.handle.net/10754/563354; https://doi.org/10.1080/2150704X.2014.891774

Monitoring deformation of linear infrastructures such as expressway and railway caused by natural processes or anthropogenic activities is a vital task to ensure the safety of human lives and properties. Interferometric Synthetic Aperture Radar (InSAR) has been widely recognized as an effective technology to carry out large-area surface deformation mapping. However, its application in linear infrastructure deformation monitoring has not been intensively studied till now. In this article, a modified Small BAseline Subset (SBAS) method is proposed to retrieve the deformation patterns of the expressway. In our method, only the point-like targets identified on the expressway were kept in our analysis, and two complementary subsets of interferograms were formed to better separate the signals of height error and deformation from inteferometric phase observations. We successfully applied this method with multitemporal high-resolution TerraSAR-X images to retrieve the spatialoral pattern of surface deformation along the Beian-Heihe expressway that is located in island-permafrost areas and threatened by geohazards. © 2014 Taylor & Francis. This work is financially supported by the National Key Basic Research Program of China [grant number 2013CB733204, 2013CB733205]; the National Natural Science Foundation of China [grant number 61331016, 41271457, 41174120, 41021061] and the Shanghai Academy of Spaceflight Technology Innovation Fund [grant number SAST201214].