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Session Overview
D2: ID.10650 Land Subsidence Monitoring
Tuesday, 05/Jul/2016:
11:30am - 12:30pm

Session Chair: Cécile Lasserre
Session Chair: Qiming Zeng
Workshop: Terrain & Geoid Measurement
Location: A-Li Mountain Room, 5.5 Floor, Junyi Dynasty Hotel

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Oral presentation

Mapping land subsidence with multi-source SAR images

Yonghong Zhang1, Chuanguang Zhu2, Hongan Wu1

1Chinese Academy of Surveying and Mapping, Beijing, China; 2Hunan University of Science & Technology, Xiangtan, Hunan province, China;

Multitemporal Interferometric Synthetic Aperture Radar (MT-InSAR) has been proved as a powerful technique for monitoring of deformation with high precision and high spatial resolution over large area. Usually better deformation accuracy can be expected when larger stack of SAR images is used in MT-InSAR analysis. Nevertheless, due to the limitation of imaging capability of one spaceborne SAR system alone, the number of available SAR images is just on the level meeting the minimum requirement of MT-InSAR analysis (for example, 10 scenes) in many areas. But sometimes there maybe exist more than one SAR stacks, e.g. stacks of SAR images acquired by multiple SAR systems. We have developed a methodology to integrate multitemporal ENVISAT ASAR and TerraSAR-X (TSX) images for MT-InSAR analysis. Firstly the deformation rate and DEM residual are calculated based on time-series ASAR images, which represents an initial estimation of the ground deformation velocity and DEM error. These information are then incorporated in the processing of time-series TSX images. Especially, the phase components contributed by the estimated deformation and DEM residual respectively will be subtracted from each TSX differential interferograms, and the rest analysis will be based on these double-differentiated TSX interferograms. Therefore, what we calculate from the TSX MT-InSAR analysis is the residual deformation, which together with the initial estimate derived from ASAR forms the full deformation. As the main component of deformation has already been subtracted, the phase of those double-differentiated TSX interferograms will be very smooth, which facilitates the process of phase unwrapping. As a result, the residual deformation can then be estimated more reliably and accurately from time-series TSX images. 14 ASAR images and 29 TSX images acquired between January 2009 and September 2010 over Tianjin, China are used as the test data. In the first experiment, all the 29 TSX images are integrated with the 14 ASAR images for MT-InSAR processing. The result from the integrated processing achieved an accuracy of 1.7 mm per year, 1.3 mm per year higher than that from the 29 TSX images alone. Especially, using the two SAR stacks the deformation rate can be derived very precisely even in areas presenting very large deformation gradient, where TSX data set alone may underestimate the deformation velocity due to the limit on measurable deformation gradient. In the second experiment, 14 of the 29 TSX images are integrated in the MT-InSAR analysis, and achieve an accuracy of 1.6 mm/yr. This experiment demonstrates that by integration with other course-resolution SAR images, high-accuracy deformation can still be achieved from a reduced subset of TSX stack. This is of great significance in practice because less budget will be spend in purchase of high resolution TSX data.

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