Deformation Monitoring and Analysis of Baige Landslide (China) Based on the Fusion Monitoring of Multi-Orbit Time-Series InSAR Technology

作者：Kai Ye, Zhe Wang, Ting Wang, Luo Ying, Yiming Chen, Jiaqian Zhang, Jialun Cai · 发表于：Sensors · 年份：2024 · DOI：10.3390/s24206760 · 被引用次数：13 · 研究领域：Synthetic Aperture Radar (SAR) Applications and Techniques、Landslides and related hazards、Cryospheric studies and observations

Due to the limitations inherent in SAR satellite imaging modes, utilizing time-series InSAR technology to process single-orbit satellite image data typically only yields one-dimensional deformation information along the LOS direction. This constraint impedes a comprehensive representation of the true surface deformation of landslides. Consequently, in this paper, after the SBAS-InSAR and PS-InSAR processing of the 30-view ascending and 30-view descending orbit images of the Sentinel-1A satellite, based on the imaging geometric relationship of the SAR satellite, we propose a novel computational method of fusing ascending and descending orbital LOS-direction time-series deformation to extract the landslide's downslope direction deformation of landslides. By applying this method to Baige landslide monitoring and integrating it with an improved tangential angle warning criterion, we classified the landslide's trailing edge into a high-speed, a uniform-speed, and a low-speed deformation region, with deformation magnitudes of 7~8 cm, 5~7 cm, and 3~4 cm, respectively. A comparative analysis with measured data for landslide deformation monitoring revealed that the average root mean square error between the fused landslide's downslope direction deformation and the measured data was a mere 3.62 mm. This represents a reduction of 56.9% and 57.5% in the average root mean square error compared to the single ascending and descending orbit LOS-direction time-series deformations, respectivel...