Application of InSAR Techniques to an Analysis of the Guanling Landslide

Abstract

Abstract: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.

Remote Sensing of Landslides—A Review

“…The mapped landslides show high consistency with results from optical images [2]. An extensive investigation of more than 90 landslides affecting a small river basin in Central Italy was performed by combining field surveys and remote sensing techniques [1].…”

“…Satellite SAR data used in this special issue include archived ERS and Envisat ASAR [1], ALOS/PALSAR [2,3], COSMO-SkyMed constellation [4], TerraSAR-X [5], TerraSAR-X/TanDEM-X [6], and Sentinel-1 [7]. In addition, "Envisat 2010+" data, which started on 22 October 2010 and lasted until the communication with the Envisat satellite was suddenly lost on 8 April 2012, were involved.…”

“…In addition, spatial autocorrelation changes induced by event landslides were measured in a set of multi-temporal Sentinel-1 intensity images [7]. Furthermore, potential landslides over large area were detected based on surface deformation maps from InSAR [2,8].…”

“…Time series surface deformation based on spaceborne satellite data are calculated with persistent scatterer interferometry (PSI) [1] and small baseline subset (SBAS) InSAR [2,3,8], as well as the integration of PS and Quasi-PS (QPS), which take advantage of two different image connection graphs in time-series InSAR processing [1]. The deformation retrieved from pre-installed corner reflectors imaged by X-band COSMO-SkyMed constellation SAR data can overcome the temporal decorrelation to obtain high-precision deformation results [16].…”

“…A pre-slide time-series deformation was monitored with SBAS InSAR technique over the Guanling landslide occurred on 28 June 2010 [2]. A complex earthflow with spatially varying …”