Next Article in Journal
Spatiotemporal Variation of Snow Cover in Tianshan Mountains, Central Asia, Based on Cloud-Free MODIS Fractional Snow Cover Product, 2001–2015
Next Article in Special Issue
Remote Sensing of Landslides—A Review
Previous Article in Journal
Generative Adversarial Networks-Based Semi-Supervised Learning for Hyperspectral Image Classification
Previous Article in Special Issue
Evaluation of Remote-Sensing-Based Landslide Inventories for Hazard Assessment in Southern Kyrgyzstan
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Remote Sens. 2017, 9(10), 1046;

Application of InSAR Techniques to an Analysis of the Guanling Landslide

School of Geology Engineering and Geomatics, Chang’an University, Xi’an 710054, China
National Administration of Surveying, Mapping and Geoinformation, Engineering Research Center of National Geographic Conditions Monitoring, Xi’an 710054, China
Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275, USA
Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, China
Author to whom correspondence should be addressed.
Received: 13 June 2017 / Revised: 25 September 2017 / Accepted: 10 October 2017 / Published: 13 October 2017
(This article belongs to the Special Issue Remote Sensing of Landslides)
Full-Text   |   PDF [9677 KB, uploaded 13 October 2017]   |  


On the afternoon of 28 June 2010, an enormous landslide occurred in the Gangwu region of Guanling County, Guizhou Province. In order to better understand the mechanism of the Guanling landslide, archived ALOS/PALSAR data was used to acquire the deformation prior to the landslide occurrence through stacking and time-series InSAR techniques. First, the deformation structure from InSAR was compared to the potential creep bodies identified using the optical remote sensing data. A strong consistency between the InSAR detected deformed regions and the creep bodies detected from optical remote sensing images was achieved. Around 10 creep bodies were suffering from deformation. In the source area, the maximum pre-slide mean deformation rate along the slope direction reached 160 mm/year, and the uncertainty of the deformation rates ranged from 15 to 34 mm/year. Then, the pre-slide deformation at the source area was analyzed in terms of the topography, geological structure, and historical rainfall records. Through observation and analysis, the deformation pattern of one creep body located within the source area can be segmented into three sections: a creeping section in the front, a locking section in the middle, and a cracking section in the rear. These sections constitute one of the common landslide modes seen in the south-west of China. This study concluded that a sudden shear failure in the locking segment of one creeping body located within the source area was caused by a strong rainstorm, which triggered the Guanling landslide. View Full-Text
Keywords: Guanling landslide; stacking-InSAR; time-series InSAR; deformation; landslide mode Guanling landslide; stacking-InSAR; time-series InSAR; deformation; landslide mode

Graphical abstract

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).

Share & Cite This Article

MDPI and ACS Style

Kang, Y.; Zhao, C.; Zhang, Q.; Lu, Z.; Li, B. Application of InSAR Techniques to an Analysis of the Guanling Landslide. Remote Sens. 2017, 9, 1046.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top