Wide-Area Landslide Deformation Mapping with Multi-Path ALOS PALSAR Data Stacks: A Case Study of Three Gorges Area, China

Abstract

Abstract:In recent years, satellite synthetic aperture radar interferometry (InSAR) has been adopted as a spaceborne geodetic tool to successfully measure surface deformation of a few well-known landslides in the Three Gorges area. In consideration of the fact that most events of slope failure happened at places other than those famous landslides since the reservoir impoundment in 2003, focusing on a limited number of slopes is insufficient to meet the requirements of regional-scale landslide disaster prevention and early warning. As a result, it has become a vital task to evaluate the overall stability of slopes across the vast area of Three Gorges using wide-coverage InSAR datasets. In this study, we explored the approach of carrying out joint analysis of multi-path InSAR data stacks for wide-area landslide deformation mapping. As an example, three ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) data stacks of neighboring ascending paths covering the area along the Yangtze River from Fengjie to Zigui were analyzed. A key problem to be solved is the separation of the tropospheric signal from the interferometric phase, for which we employed a hybrid description model of the atmospheric phase screen (APS) to improve APS estimation from time series interferograms. The estimated atmospheric phase was largely correlated with the seasonal rainfall in the temporal dimension. The experimental results show that about 30 slopes covering total areas of 48 km 2 were identified to be landslides in active deformation and should be kept under routine surveillance. Analyses of time series displacement measurements revealed that most landslides in the mountainous area far away from Yangtze River suffered from linear deformation, whereas landslides located on the river bank were destabilized predominantly by the influences of reservoir water level fluctuation and rainfall.

Landslide Detection and Susceptibility Mapping by AIRSAR Data Using Support Vector Machine and Index of Entropy Models in Cameron Highlands, Malaysia

“…SAR data have been applied to natural hazards' researches independently or in combination with data obtained from other remote sensing sensors [11,12]. The combination of optical and SAR data can also be used in geo-hazards' identification and susceptibility mapping and is especially popular in landslide studies [13][14][15][16][17]. Remote sensing is the foundation of landslide inventory maps and related thematic maps.…”

Detection and Characterization of Active Slope Deformations with Sentinel-1 InSAR Analyses in the Southwest Area of Shanxi, China

“…Each component in the unwrapped phase can be estimated by the corresponding characteristics. The orbital ramp can be estimated with a bilinear model [36]. Inaccuracy of the reference DEM can be linearly estimated by the least square method with perpendicular baselines and unwrapped phases.…”

Analysis of Mining Waste Dump Site Stability Based on Multiple Remote Sensing Technologies

“…Compared with the original SBAS method which only operates with isolated subsets of interferograms, the modified SBAS approach in the Stanford method for persistent scatterers (StaMPS) software can ensure temporal continuity by connecting separated subsets of interferograms with larger baselines [12,13]. It has been widely applied in the displacement monitoring of natural scenes with limited amounts of data [48]. Due to the above mentioned reasons, the modified SBAS approach in StaMPS developed for displacement monitoring of rural areas was well suited to this study [12].…”