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Remote Sens. 2015, 7(1), 72-88; doi:10.3390/rs70100072

Investigation of Slow-Moving Landslides from ALOS/PALSAR Images with TCPInSAR: A Case Study of Oso, USA

1
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
2
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong 999077, China
*
Author to whom correspondence should be addressed.
Academic Editors: Richard Gloaguen and Prasad S. Thenkabail
Received: 5 September 2014 / Accepted: 15 December 2014 / Published: 24 December 2014
View Full-Text   |   Download PDF [9481 KB, uploaded 24 December 2014]   |  

Abstract

Monitoring slope instability is of great significance for understanding landslide kinematics and, therefore, reducing the related geological hazards. In recent years, interferometric synthetic aperture radar (InSAR) has been widely applied to this end, especially thanks to the prompt evolution of multi-temporal InSAR (MTInSAR) algorithms. In this paper, temporarily-coherent point InSAR (TCPInSAR), a recently-developed MTInSAR technique, is employed to investigate the slow-moving landslides in Oso, U.S., with 13 ALOS/PALSAR images. Compared to other MTInSAR techniques, TCPInSAR can work well with a small amount of data and is immune to unwrapping errors. Furthermore, the severe orbital ramps emanated from the inaccurate determination of the ALOS satellite’s state vector can be jointly estimated by TCPInSAR, resulting in an exhaustive separation between the orbital errors and displacement signals. The TCPInSAR-derived deformation map indicates that the riverside slopes adjacent to the North Fork of the Stillaguamish River, where the 2014 mudslide occurred, were active during 2007 and 2011. Besides, Coal Mountain has been found to be experiencing slow-moving landslides with clear boundaries and considerable magnitudes. The Deer Creek River is also threatened by a potential landslide dam due to the creeps detected in a nearby slope. The slope instability information revealed in this study is helpful to deal with the landslide hazards in Oso. View Full-Text
Keywords: interferometric synthetic aperture radar (InSAR); temporarily-coherent point InSAR (TCPInSAR); ALOS PALSAR; Oso; landslides; deformation monitoring interferometric synthetic aperture radar (InSAR); temporarily-coherent point InSAR (TCPInSAR); ALOS PALSAR; Oso; landslides; deformation monitoring
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Sun, Q.; Zhang, L.; Ding, X.; Hu, J.; Liang, H. Investigation of Slow-Moving Landslides from ALOS/PALSAR Images with TCPInSAR: A Case Study of Oso, USA. Remote Sens. 2015, 7, 72-88.

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