Full coverage and continuous deformation information retrieval are key aspects for dam health diagnosis. Ground-based synthetic aperture radar (GB-SAR) interferometry is used for the remote monitoring of the Geheyan Dam, China. Although the monitoring of a dam with ground-based interferometry is not an innovation, specific issues have been found out in the case study discussed due to the large dimension of the monitored structure. More than 400 images were used for interferogram generation. Radar signals reflected from the dam were carefully analyzed: a sort of tunneling effect caused by multireflection is observed, and deformations caused by water level and temperature variations were detected during a six-day monitoring campaign. Radar monitoring results were compared to the data recorded by plummets installed in the dam. The agreement between the displacements retrieved from interferometric data and the plummets demonstrates the capability of GB-SAR for deformation monitoring, with the advantage of large area coverage.
How to select a common master image is one of the key points in multi-temporal InSAR processing. In this paper, three
main decorrelation factors, spatial baseline, temporal baseline, Doppler centroid frequency difference, are focused on to
establish a correlation model of SAR interferometry, especially, a seasonal factor is presented to reflect correlation
change in a cycle of seasons, then the model for optimum selection of common master image based on a criterion called
mean total pre-coherence was presented, followed by the corresponding computing algorithm. The experiments of master
image selecting are performed using the 22 ERS-2 SAR images of Nanjing from 1996 to 2000, and the results
demonstrate the effectiveness of the algorithm.
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