Evaluating sub-pixel offset techniques as an alternative to D-InSAR for monitoring episodic landslide movements in vegetated terrain

Spaceborne Synthetic Aperture Radar (SAR) sensors obtain regular and frequent radar images from which ground motion can be precisely detected using a variety of different techniques. The ability to measure slope displacements remotely over large regions can have many uses, although the limitations of the most commonplace technique, differential InSAR (D-InSAR), must be considered prior to interpreting the final results. One such limitation is the assumption that different rates of movement over a given distance cannot exceed a threshold value, dependent upon the pixel spacing of the SAR images and the radar wavelength. Characteristic features of landslides (Le. the sharp boundary between stable/active ground and the range of temporally-variable velocities) can exhibit high spatial displacement gradients, breaking a fundamental assumption for reliable D-InSAR analysis. Areas of low coherence are also known to hinder the exploitation of InSAR data. This study assesses the capability of TerraSAR-X Spotlight TerraSAR-X Stripmap and Envisat Stripmap images for monitoring the slow-moving Shuping landslide in the densely vegetated Three Gorges region, China. In this case study, the episodic nature of movement is shown to exceed the measurable limit for regular D-InSAR analysis even for the highest resolution 11-day TSX Spotlight interferograms. A Sub-Pixel Offset Time-series technique applied to corner reflectors (SPOT-CR) using only the SAR amplitude information is applied as a robust method of resolving time-varying displacements, with verifiable offset measurements presented from TSX Spotlight and TSX Stripmap imagery. Care should be exercised when measuring potentially episodic landslide movements in densely vegetated areas such as the Three Gorges region and corner reflectors are shown to be highly useful for SPOT techniques even when the assumptions for valid D-InSAR analysis are broken. Finally the capability to derive two-dimensional movements from sub-pixel offsets (in range and along-track directions) can be used to derive estimates of the vertical and northwards movements to help infer the landslide failure mechanism. (C) 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/).