Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas

Abstract

Sub-Pixel Offset Tracking (sPOT) is applied to derive high-resolution centimetre-level landslide rates in the Three Gorges Region of China using TerraSAR-X Hi-resolution Spotlight (TSX HS) space-borne SAR images. These results contrast sharply with previous use of conventional differential Interferometric Synthetic Aperture Radar (DInSAR) techniques in areas with steep slopes, dense vegetation and large variability in water vapour which indicated around 12% phase coherent coverage. By contrast, sPOT is capable of measuring two dimensional deformation of large gradient over steeply sloped areas covered in dense vegetation. Previous applications of sPOT in this region relies on corner reflectors (CRs), (high coherence features) to obtain reliable measurements. However, CRs are expensive and difficult to install, especially in remote areas; and other potential high coherence features comparable with CRs are very few and outside the landslide boundary. The resultant sub-pixel level deformation field can be statistically analysed to yield multi-modal maps of deformation regions. This approach is shown to have a significant impact when compared with previous offset tracking measurements of landslide deformation, as it is demonstrated that sPOT can be applied even in densely vegetated terrain without relying on high-contrast surface features or requiring any de-noising process.

Time Series Analysis of Very Slow Landslides in the Three Gorges Region through Small Baseline SAR Offset Tracking

“…With the availability of high-resolution SAR imagery, offset tracking is able to monitor very slow-moving landslides (16 mm·year −1 -1.6 m·year −1 as defined in Cruden and Varnes [4], Hungr et al [5]) and complement the applications of DInSAR. This has been demonstrated in our previous study of the Shuping landslide [3].…”

“…The azimuth and range offsets are derived using cross-correlation. As described in Sun and Muller [3] and recalled herein, the Normalized Cross Correlation (NCC) is applied to the amplitudes of the master and slave images, to derive two-dimensional (2D) offsets. The offsets of a point in any dimension are determined by its different positions in the master and slave images.…”

“…However, several difficulties arise when attempting to apply DInSAR in areas with steep slopes and rugged topography, high humidity, and dense vegetation cover. In addition to these difficulties, in previous studies [1][2][3], it is shown that the maximum detectable displacement gradient (DDG) of DInSAR can be exceeded in some case of very slow landslides (16 mm·year −1 -1.6 m·year −1 , as defined in Cruden and Varnes [4], Hungr et al [5]) even when using high resolution SAR imagery.…”

Earth Observations for Geohazards: Present and Future Challenges

“…Using the Slumgullion landslide (southwestern Colorado, USA) as an example, Wang et al [22] propose a fully polarimetric SAR offset tracking method to improve the precision of landslide movement monitoring. Taking the Shuping landslide (Three Gorges, China) as a case study, Sun and Muller [23] demonstrate the capability of sub-Pixel Offset Tracking techniques to monitor relatively fast slope movements in densely vegetated areas with and without the presence of artificial corner reflectors. Bardi et al [24] integrate ground-based and satellite InSAR data to study the Åknes rockslide (western coast of Norway).…”

An Improved Adaptive Template Size Pixel-Tracking Method for Monitoring Large-Gradient Mining Subsidence

“…This method was first used to monitor glacial drifts [29][30][31][32][33][34][35][36] and earthquakes [37][38][39][40]. With improvements in SAR resolution, this method has now been used to monitor landslide movements [27,28,[41][42][43] and ground subsidence caused by mining [23][24][25][26].…”