Landslides are one of the major geohazards in the Qinghai-Tibet Plateau (QTP). Due to global warming and more frequent extreme climate events in recent years, the frequency and spatial scale of small-scale landslides in permafrost areas of the QTP have increased, which seriously affected the regional ecological environment and the stability of construction projects. 

In recent years, the high-resolution Synthetic Aperture Radar interferometry technique (InSAR) has proven to be an excellent tool to monitor the landslide on both the site-specific and the regional scale. However, the InSAR using in the QTP aiming for small-scale landslide events are rare. 

Recently, a research group led by WU Tonghua from the Northwest Institute of Eco-Environment and Resources (NIEER) of the Chinese Academy of Sciences investigated the performance of Small Baseline Subsets method (SBAS) in monitoring small-scale landslide and further developed a new deformation model to obtain the absolute deformation time series. Their findings were published in Remote Sensing. 

The scientists used the SBAS method and the absolute deformation model to monitor surface displacement in landslide area using Sentinel-1 data (2016-2017), and further developed a kinematic model to explain the formation of small-scale landslide, and then discussed the results. 

The results showed that SBAS could well capture the small-scale landslide characteristics including spatiotemporal abnormal displacement and progressive failure processes. 

The newly developed absolute deformation model further detected the process of landslide details, such as instances of noticeable creeps induced by rainfall and snowmelt.