Science Service System

Summary of Proposal MTH1532

TitleInvestigation of spatiotemporal 3D surface displacement of Southern California by using multi-track and multi-temporal TerraSAR-X Data
Investigator Hu, Jun - Central South University, School of Geosciences and Info-Physics
Team Member
Prof. Zhu, Jianjun - School of Geosciences and Info-Physics, Central South University, Department of Geomatics
Mrs Yu, Xiaoyin - School of Geosciences and Info-Physics, Central South University, Department of Geomatics
Mr Yang, Yafu - School of Geosciences and Info-Physics, Central South University, Department of Geomatics
Miss Zhao, Rong - School of Geosciences and Info-Physics, Central South University, Department of Geomatics
SummaryThe surface displacement of Southern Californiais a complex of tectonic and anthropogenic signals, which is continued monitored by the Southern California Integrated GPS Network (SCIGN). However, the spatial resolution is very low for the GPS observations. On the other sides, Interferometric synthetic aperture radar (InSAR) technique is also widely used in the investigation of the surface deformation for the advantages of wide spatial coverage, all-day and all-weather. However, only the one-dimensional displacement (1D) in Line-Of-Sight (LOS) direction can be monitored by InSAR. This may obscure the effects of the tectonic contraction and seasonal groundwater occurred in the area of Southern California. This project will serve to (1) infer completely three-dimensional (3D) surface displacements of the Southern California area from the multi-track and multi-temporal TerraSAR-X data and GPS observations, (2) improve InSAR technology to monitor and discriminate the ground deformations due to the geophysical and engineering processes. The observations from InSAR and GPS will be integrated to extend 1D LOS measurements to 3D, and improve the accuracies of 3D deformation measurements. Besides, the multi-track and multi-temporal observations would also be combined to improve the temporal resolution of the 3D surface displacement measurements. The approaches of variance component estimation (VCE) and Kalman filter are both introduced in our study, which are crucial in better integration of the observations. The deliverables of this project may include several peer-reviewer journal papers, several presentations in the international conference, and some algorithms on the integration of multi-track and multi-temporal InSAR observations and GPS observations. The study is also funded by the National Science Foundations of China.

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DLR 2004-2016