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Title: Investigation of slow-moving landslides from ALOS/PALSAR images with TCPInSAR : a case study of Oso, USA
Authors: Sun, Q
Zhang, L 
Ding, X 
Hu, J
Liang, H
Issue Date: 2015
Source: Remote sensing, Jan. 2015, v. 7, no. 1, p. 72-88
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.
Keywords: ALOS PALSAR
Deformation monitoring
Interferometric synthetic aperture radar (InSAR)
Landslides
Oso
Temporarily-coherent point InSAR (TCPInSAR)
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Remote sensing 
EISSN: 2072-4292
DOI: 10.3390/rs70100072
Rights: © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
The following publication Sun, Q., Zhang, L., Ding, X., Hu, J., & Liang, H. (2015). Investigation of slow-moving landslides from ALOS/PALSAR images with TCPInSAR : a case study of Oso, USA. Remote Sensing, 7(1), (Suppl. ), 72-88 is available athttps://dx.doi.org/10.3390/rs70100072
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