Deformation along a subway rail network is related to the safe operation of the subway and the stability of construction facilities on the surface, making long-term deformation monitoring imperative. Long-term monitoring of surface deformation along the subway network and statistical analysis of the overall deformation situation are lacking in China. Therefore, targeting 35 Chinese cities whose subway mileage exceeds 50 km, we extracted their surface deformation along subway networks between 2018 and 2022, using spaceborne synthetic aperture radar (SAR) interferometry (InSAR) technology and Sentinel-1 satellite data. We verified the results with the continuous global navigation satellite system (GNSS) stations’ data and found that the root mean square error (RMSE) of the InSAR results was 3.75 mm/year. Statistical analysis showed that ground subsidence along the subways was more prominent in Beijing, Tianjin, and other areas in the North China Plain, namely Kunming (which is dominated by karst landforms), as well as Shanghai, Guangzhou, Qingdao, and other coastal cities. In addition, an analysis revealed that the severity of surface subsidence correlated positively with a city’s gross domestic product (GDP) with a Pearson correlation of 0.787, since the higher the GDP, the more frequent the construction and maintenance of subway, and the more commuters there are, which in turn exacerbates the disturbance to the surface. Additionally, the type of land cover also affects the ground deformation. Our findings provide a reference for constructing, operating, and maintaining the urban subway systems in China.

China, with its complex geology and diverse climate, is highly prone to landslides, endangering public safety and infrastructure. To address disaster prevention needs, this study comprehensively assesses national landslide susceptibility. We divided China into 37 geomorphic districts, diverging from traditional methods. By using a 2018–2022 surface deformation dataset, we introduced a rarely—considered dynamic aspect for more accurate mapping of landslide—prone areas. Nine key environmental factors were carefully considered, including terrain, geology, meteorology, hydrology, seismic activities, and engineering activities. Based on these innovative methods and data, we created a 40 m—resolution landslide susceptibility map (LSM) for the whole country. Our assessment showed high accuracy, with an AUC of 0.927, precision of 0.859, recall of 0.815, F1—score of 0.828 and Matthews correlation coefficient of 0.773. Seven high—risk regions, like the Tianshan Mountains and the southern Tibetan valleys, were analyzed. The study revealed regional differences in landslide occurrences and key influencing factors. The LSM and findings enrich landslide susceptibility theory and offer a valuable resource for engineering, disaster management, and mitigation in China, helping reduce potential landslide losses.

The Middle Route of the South-to-North Water Diversion Project (SNWD-MR) serves as a strategic infrastructure critical to safeguarding water security in Northern China. Traversing complex geographical units, the project is perpetually exposed to long-term risks of land subsidence. Conventional Interferometric Synthetic Aperture Radar (InSAR) monitoring is hampered by waterbody isolation, causing spatial discontinuities in the retrieved deformation fields; furthermore, relying solely on deformation metrics fails to comprehensively quantify multidimensional risks. To address these issues, this study proposes an integrated assessment framework that couples time-series InSAR observations with the Analytic Hierarchy Process-Fuzzy Comprehensive Evaluation (AHP-FCE) model. To specifically mitigate the challenge of waterbody isolation, we developed a connectivity-aware multiscale down-sampling phase unwrapping strategy. By exploiting cross-canal bridges to construct a spatial connection network, a highly accurate, spatiotemporally continuous deformation field across the entire alignment was successfully reconstructed. Using the derived deformation field as the core dynamic indicator, an AHP-FCE model integrating hydrogeological features and human perturbations was constructed. A complementary evaluation process comprising sensitivity analysis and an internal physical consistency assessment was subsequently implemented. The results demonstrate that (1) the proposed algorithm effectively resolves the spatial discontinuity issue of the cross-canal deformation fields, reducing the deformation-velocity RMSE from 7.9 to 5.7 mm/y, corresponding to an approximately 27.8% reduction in RMSE relative to the traditional Minimum Cost Flow (MCF) method; (2) land subsidence along the alignment exhibits prominent spatial heterogeneity, with the northern Henan and southern Hebei sections identified as very-high-risk zones; and (3) InSAR deformation magnitude and the groundwater elevation indicator emerge as the most influential factors in the modeled risk distribution. Overall, this study expands conventional deformation monitoring into a systematic, quantitative risk assessment framework, thereby providing scientific insights and theoretical support for the early warning of geo-hazards and the smart operation and maintenance of large-scale water diversion projects.