Landslide Detection Using Time-Series InSAR Method along the Kangding-Batang Section of Shanghai-Nyalam Road

Due to various factors such as urban development, climate change, and tectonic movements, landslides are a common geological phenomenon in the Qinghai-Tibet Plateau region, especially on both sides of a road, where large landslide hazards often result in traffic disruptions and casualties. Identifying the spatial distribution of landslides and monitoring their stability are essential for predicting landslide occurrence and implementing prevention measures. In this study, taking the Kangding-Batang section of Shanghai-Nyalam Road as the study area, we adopted a semi-automated time-series interferometric synthetic aperture radar (InSAR) method to identify landslides and monitor their activity. A total of 446 Sentinel-1 ascending and descending SAR images from January 2018 to December 2021 were thus collected and processed by using open-source InSAR processing software. After a series of error corrections, we obtained surface deformation maps covering the study area, and a total of 236 potential landslides were subsequently identified and classified into three categories, namely slow-sliding rockslides, debris flows, and debris avalanches, by combining deformation maps, optical images, and a digital elevation model (DEM). For a typical landslide, we performed deformation decomposition and analyzed the relationship between its deformation and rainfall, revealing the contribution of rainfall to the landslide. In addition, we discussed the effect of SAR geometric distortion on landslide detection, highlighting the importance of joint ascending and descending observations in mountainous areas. We analyzed the controlling factors of landslide distribution and found that topographic conditions are still the dominant factor. Our results may be beneficial for road maintenance and disaster mitigation. Moreover, the entire processing is semi-automated based on open-source tools or software, which provides a paradigm for landslide-related studies in other mountainous regions of the world.

Automated summary

In this study, a semi-automated time-series interferometric synthetic aperture radar (InSAR) method was adopted to identify landslides and monitor their activity in the Kangding-Batang section of Shanghai-Nyalam Road. A total of 446 Sentinel-1 SAR images from January 2018 to December 2021 were collected and processed using open-source InSAR processing software. The results provide valuable information for road maintenance and disaster mitigation, and the semi-automated processing method can serve as a paradigm for landslide-related studies in other mountainous regions of the world.