InSAR-Based Surface Deformation Analysis and Trend Prediction in Permafrost Areas Along the Qinghai-Tibet Railway Using Sentinel-1A and Environmental Factors

Global warming is accelerating the permafrost degradation along the Qinghai-Tibet railway (QTR), causing the surface deformation (SD) of the railway subgrade. Especially in the Salt Lake to Wuli section of the QTR, the permafrost is widely distributed, and the SD has been the most serious. However, the spatiotemporal characteristics and mechanism of SD are still unclear. In addition, it is very important to predict the future trend of SD. Therefore, we acquired time series SD results from 2019 to 2022 based on small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) and analyzed the spatiotemporal characteristics and mechanism of SD in the Salt Lake to Wuli section. Subsequently, the EnvCA-GRU model for SD prediction was developed, integrating the multihead cross-attention mechanism and gated recurrent unit (GRU) to account for changes in environmental factors. The model was then employed to forecast SD trends over the next two years. Our results showed that the SD was uneven in the Salt Lake to Wuli section of the QTR from 2019 to 2022, there were six typical deformation areas, and the maximum cumulative ground subsidence reached 126.79 mm. The SD velocity of the sunny slope was higher than that of the shady slope, and the closer to the QTR, the greater the ground subsidence. Land surface temperature (LST), normalized difference vegetation index (NDVI), and precipitation are the main factors affecting SD. Our proposed EnvCA-GRU prediction model fusing NDVI, LST, and precipitation showed a root mean square error of 0.153 and an R² of 0.991, the proposed model was reliable. The maximum cumulative ground subsidence of six typical areas by July 2024 reached 177.52, 268.08, 287.73, 270.99, 190.70, and 211.89 mm, respectively. The results of this study can play a guiding role in the early warning and mitigation of ground subsidence disasters along the QTR.