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On 4 October 2023, a glacier lake outburst flood (GLOF) occurred at South Lhonak Lake in the northwest of Sikkim, India, posing a severe threat to downstream lives and property. Given the serious consequences of GLOFs, understanding their triggering factors is urgent. This paper conducts a comprehensive analysis of optical imagery and InSAR deformation results to study changes in the surrounding surface of the glacial lake before and after the GLOF event. To expedite the processing of massive InSAR data, an InSAR processing system based on the SBAS-InSAR data processing flow and the AI Earth cloud platform was developed. Sentinel-1 SAR images spanning from January 2021 to March 2024 were used to calculate surface deformation velocity. The evolution of the lake area and surface variations in the landslide area were observed using optical images. The results reveal a significant deformation area within the moraine encircling the lake before the GLOF, aligning with the area where the landslide ultimately occurred. Further research suggests a certain correlation between InSAR deformation results and multiple factors, such as rainfall, lake area, and slope. We speculate that heavy rainfall triggering landslides in the moraine may have contributed to breaching the moraine dam and causing the GLOF. Although the landslide region is relatively stable overall, the presence of a crack in the toparea of landslide raises concerns about potential secondary landslides. Our study may improve GLOF risk assessment and management, thereby mitigating or preventing their hazards. [ABSTRACT FROM AUTHOR]

Detecting the slow motions of highly elevated landslides in remote mountain areas has always been a problem. This paper takes the Woda landslide along the Jinsha River as an example to monitor landslide movement. Although some parts of the landslide body have been found to have moved in recent years, the timing and magnitude of motion have not been systematically monitored or interpreted. Here, we apply the SBAS time series strategy using 65-scene Sentinel-1A/B satellite InSAR images and study the spatial distribution and temporal behaviour of landslide movements between July 4, 2018, and August 29, 2020. Our research results show that the cumulative deformation on the left side of the landslide body with concentrated deformation was approximately 200 mm during the 2-year observation period. By calculating the relationship between the InSAR time series and the precipitation around the landslide, it is found that the landslide deformation is closely related to precipitation. GNSS technology is also deployed on the landslide mass and effectively complements InSAR technology. Simultaneously, based on the results of field surveys and hydrological data analysing the landslide's spatial deformation characteristics and deformation factors, the landslide deformation can also be inferred to be related to precipitation. [ABSTRACT FROM AUTHOR]

Although the atmospheric compensation models developed to date have been generally robust and effective for InSAR, how to choose the right atmospheric correction method for ground-based InSAR is worth studying. This paper uses different methods for atmospheric phase screen (APS) compensation based on studies of ground-based radar (GBR) to zero-baseline acquisitions over the Woda landslide in Sichuan, China. This landslide has a steep topography, thick fog, turbulent rivers and strong rains. Data were acquired at the Ku-band using a GAMMA Portable Radar Interferometer II (GPRI-II) in multiple campaigns (4 July 2019–13 July 2019). In 2019, the Miyun open-pit mine was also studied; the maximum deformation reached 4.03 mm/hour. The collected data were processed within one unit based on the small baseline set (SBAS) approach. The experimental results show the following (1) For long-distance monitoring with complex atmospheric disturbances, range- and/or height-dependent models fail. (2) The iterative decomposition (ITD) method can effectively address complex atmospheric disturbances. (3) If the threshold of wavelength is set to be large, the ITD method becomes a stratified model. [ABSTRACT FROM AUTHOR]

Detecting the slow motions of high and distant landslides in remote mountain areas has always been a problem. This paper takes the Woda landslide along the Jinsha River as an example to monitor landslide movement. Although some parts of the landslide body have been found to have moved in recent years, the timing and magnitude of motion have not been systematically monitored or interpreted. Here, we apply the SBAS time series strategy using 65-scene Sentinel-1A/B satellite InSAR images and study the spatial distribution and temporal behaviour of landslide movements between July 4, 2018, and August 29, 2020. Our research results show that the cumulative deformation on the left side of the landslide body with concentrated deformation was approximately 200 mm during the 2-year observation period. By calculating the relationship between the InSAR time series and the precipitation around the landslide, it is found that the landslide deformation is closely related to rainfall. GNSS technology is also deployed on the landslide mass and effectively complements InSAR technology. Simultaneously, based on the results of field surveys and hydrological data analysing the landslide's spatial deformation characteristics and deformation factors, the landslide deformation can also be inferred to be related to precipitation. The method used in this paper can be used for early recognition and early warning of high and remote landslides. [ABSTRACT FROM AUTHOR]

On March 20, 2019, a landslide (named Yagu landslide) occurred in eastern Tibetan Plateau. It produced a 10-m-high dam, resulting in a lake on the Songmai River, a tributary of the Jinsha River. This paper describes this slope failure and analyzes the process and cause of the landsliding based on the combination of Google Earth images, PlanetScope satellite optical images, field photography and geologic data. It is speculated that this event was likely induced by local human activity, such as quarrying rather than natural factors. This example raises a challenging issue whether the ongoing projects along the Jinsha River can induce landslides. In addition, the emergency responses of the government and the effort for risk removal of the dammed lake are presented. [ABSTRACT FROM AUTHOR]

• The landslide deformation is obtained by using Ground-based radar 8 km far away. • We present a GBR deformation extraction method in a complicated environment. • A 3D sliding distribution is achieved by combining two methods of measurement. • The present and future stability state of landslide is inferred. On Oct. 11 and Nov. 3, 2018, two large-scale landslides occurred in the same location in Baige Village, Tibet, and massive rocks fell and encroached into the Jingsha River. These landslides posed a severe risk to the upstream and downstream areas. The occurrence, development and evolution of landslides are accompanied by a large number of changes in measurable variables. The deformation data are one of most important parameters for characterizing change and development trends of a landslide. This paper is centered on the results derived from ground-based radar and space-borne Synthetic Aperture Radar (SAR) images in the post-event phase to monitor the Baige landslides and to assess their residual risk. Two technologies play important roles in identifying and characterizing impending catastrophic slope failures: ground-based radar reveals the horizontal deformation, and satellite SAR images reveal the azimuth and range offset deformation. By combining satellite and ground-based SAR observations, we obtained high-precision three-dimensional (3D) deformation results and found that the vast majority of the instability regions mainly occur in the source area of the slope failures and that the direction of collapse converges from all sides to the middle. Additional information from UAV orthophoto maps and GNSS measurements also reveal that several cracks are distributed on the trailing edge of the landslide and are still moving. The comprehensive results revealed that the moving rock mass has still been remarkably active after the two landslide events. This study combined ground-based and space-borne SAR data to develop a long-term monitoring and stability evaluation process for implementation after a large landslide disaster. Based on the distribution characteristics of the 3D deformation fields, the present and future stability of the Baige Landslide was analyzed. [ABSTRACT FROM AUTHOR]