
Proceedings Paper
Monitoring of landslide deformation based on the coherent targets of high resolution InSAR dataFormat | Member Price | Non-Member Price |
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Paper Abstract
Landslides are a kind of typical natural disaster in China, which pose serious threats to civil lives, property and living environment. Therefore, the identification, monitoring and prevention of landslides have been considered as a long-term geological work for the public welfare. In this article, 8 TerraSAR-X high resolution strip-map mode images, acquired in the period from January to March 2012 and covering Fanjinping landslide in Zigui county, Hubei province, were used to test the usability in monitoring the deformation of single landslide. The results of two-pass DInSAR sketched the region and the shape of the deformation field of Fanjiaping landslide. Corner reflectors’ linear deformation rate using CRInSAR method could be approximately validated by the in-situ GPS measurements. From the coherent pixels’ linear deformation rate map, it was inferred that the deformation could be more obvious in the tail of the Muyubao landslide while the lowest frontier of this landslide might prevent the slide. Due to its shorter revisiting period and high bandwidth,,the high resolution TerraSAR-X images can keep better coherence than previous satellite SAR data in the test area and provide basic guarantee to monitor the deformation of single landslides.
Paper Details
Date Published: 14 May 2014
PDF: 7 pages
Proc. SPIE 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 91580K (14 May 2014); doi: 10.1117/12.2064013
Published in SPIE Proceedings Vol. 9158:
Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China
Qingxi Tong; Jie Shan; Boqin Zhu, Editor(s)
PDF: 7 pages
Proc. SPIE 9158, Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, 91580K (14 May 2014); doi: 10.1117/12.2064013
Show Author Affiliations
Jinghui Fan, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Ye Xia, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
GFZ German Research Ctr. Geosciences (Germany)
Hongli Zhao, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Man Li, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Yi Wang, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Ye Xia, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
GFZ German Research Ctr. Geosciences (Germany)
Hongli Zhao, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Man Li, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Yi Wang, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Xiaofang Guo, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Pengfei Tu, China Three Gorges Univ. (China)
Guang Liu, Institute of Remote Sensing and Digital Earth (China)
Hao Lin, China Univ. of Geosciences (China)
Pengfei Tu, China Three Gorges Univ. (China)
Guang Liu, Institute of Remote Sensing and Digital Earth (China)
Hao Lin, China Univ. of Geosciences (China)
Published in SPIE Proceedings Vol. 9158:
Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China
Qingxi Tong; Jie Shan; Boqin Zhu, Editor(s)
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