Hybrid-SAR Technique: Joint Analysis Using Phase-Based and Amplitude-Based Methods for the Xishancun Giant Landslide Monitoring

Abstract

Early detection and early warning are of great importance in giant landslide monitoring because of the unexpectedness and concealed nature of large-scale landslides. In China, the western mountainous areas are prone to landslides and feature many giant complex landslides, especially following the Wenchuan Earthquake in 2008. This work concentrates on a new technique, known as the "hybrid-SAR technique", that combines both phase-based and amplitude-based methods to detect and monitor large-scale landslides in Li County, Sichuan Province, southwestern China. This work aims to develop a robust methodological approach to promptly identify diverse landslides with different deformation magnitudes, sliding modes and slope geometries, even when the available satellite data are limited. The phase-based and amplitude-based techniques are used to obtain the landslide displacements from six TerraSAR-X Stripmap descending scenes acquired from November 2014 to March 2015. Furthermore, the application circumstances and influence factors of hybrid-SAR are evaluated according to four aspects: (1) quality of terrain visibility to the radar sensor; (2) landslide deformation magnitude and different sliding mode; (3) impact of dense vegetation cover; and (4) sliding direction sensitivity. The results achieved from hybrid-SAR are consistent with in situ measurements. This new hybrid-SAR technique for complex giant landslide research successfully identified representative movement areas, e.g., an extremely slow earthflow and a creeping region with a displacement rate of 1 cm per month and a typical rotational slide with a displacement rate of 2-3 cm per month downwards and towards the riverbank. Hybrid-SAR allows for a comprehensive and preliminary identification of areas with significant movement and provides reliable data support for the forecasting and monitoring of landslides.

Diagnosing Subsidence Geohazard at Beijing Capital International Airport, from High-Resolution SAR Interferometry

“…Monitoring and controlling the subsidence of runways are of great significant to ensure the safe operation of the whole airport and avoid the potential extensive loss of life and property.During the last three decades, interferometric synthetic aperture radar (InSAR) technology has developed into a powerful tool, providing high-resolution, day-and-night, weather-independent wide-coverage and high-accuracy measurements of the earth surface [6]. It has been widely used in various applications, such as the displacements monitoring of city subsidence [7][8][9][10][11][12], important infrastructures [13][14][15][16] and landslides geohazards [17][18][19][20][21]. Compared to traditional geodetic measuring methods-e.g., leveling and global positioning system (GPS)-InSAR measurements do not need any on-site installation and power supply, thus they will not have any impact on the regular operation of the airport.…”

Multi-Temporal X-Band Radar Interferometry Using Corner Reflectors: Application and Validation at the Corvara Landslide (Dolomites, Italy)

“…This represents a good complementary approach to MTI for a more complete utilization of SAR data as OT is not only able to measure displacements in north-south direction but can also be applied to faster ground displacement; however, only with a comparably low spatial accuracy and only in X and Y direction. This technique was already effectively applied for glaciers surface velocity field monitoring, and it could be useful at least to monitor the fastest zone of the landslide [72][73][74][75][76]. A preliminary application of OT to the Corvara landslide presenting its spatial accuracy limits is given in Mulas et al [77].…”

Radar Remote Sensing Applications in Landslide Monitoring With Multi-Platform Insar Observations: A Case Study From China

“…The complexity of topographic conditions and slope gradient are the main factors controlling the occurrence of geological hazards, which are further deteriorated under the damage of the "5.12" Wenchuan earthquake. A Spatial Sensor Network ( Figure 2) is also deployed on Xishancun Landslide with multiple boreholes and in-situ sensors since 2014 (Qu et al, 2016;.…”