Due to the overexploitation of water resources, ground subsidence is becoming increasingly problematic in Beijing, China's political, economic, and cultural capital. This article aims to investigate the relationship between ground subsidence and changes in groundwater depth, and water supply from a long-term point of view. Multisource synthetic aperture radar (SAR) data using the interferometric SAR (InSAR) technique were adopted in this research, combined with a set of leveling and ground subsidence data in the Beijing Plain area from 2003 to 2020. The InSAR results demonstrate that ground subsidence in the plain area increased steadily from 2003 to 2015, expanding from sporadic to continuous laminar dispersion and producing five major subsidence centers. The South-to-North Water Diversion Project (SNWDP) that was completed in 2008 and 2015 considerably reduced the demand for groundwater supply in the Beijing Plain area. Since then, the groundwater level depth has continued to increase. However, since 2016, the ground subsidence rate has dramatically slowed down. The obtained results showed that, thanks to the SNWDP, which resulted in a decline in groundwater exploitation and an increase in renewable water recycling, the ground subsidence in Beijing's plain area has been effectively managed.

Land subsidence, resulting from natural or human activities, is a global environmental geological disaster. The Interferometric Synthetic Aperture Radar (InSAR) time-series analysis technique offers high spatial and continuous temporal resolution, providing data and a foundation for investigating regional land subsidence and its evolution mechanism. Beijing Capital International Airport (BCIA) has experienced uneven land subsidence since 1935, together with severe fissures significantly affecting its normal operations. In this study, the time-series InSAR method was successfully applied to monitor the gradual increase in uneven local subsidence and ground fissures activity at BCIA from June 2003 to March 2023. Initially, ENVISAT-ASAR, Cosmo-SkyMed, and Sentinel-1 data were processed by time-series InSAR techniques to generate deformation rate maps and time series for the airport area. Subsequently, a comparison was made between the displacement time series from InSAR and ground leveling measurements to assess the accuracy of InSAR-derived measurements. Through a comprehensive analysis of the distribution characteristics of land subsidence at the airport, a long-standing ground fault was located within the airport was identified. A preliminary discussion on the development status of this ground fissure was carried out based on the visual interpretation of optical images. Lastly, the inducing factors and evolutionary conditions of land subsidence were discussed. This case demonstrates the applicability of InSAR technology in identifying and monitoring geological processes such as land subsidence and ground fissure activities. It provides a scientific approach to exploring and studying the causes and formation mechanisms of land subsidence and ground fissures in the Beijing Capital Airport area.

The upper Jinsha River, located in a high-mountain gorge with complex geological features, is highly prone to large-scale landslides, which could result in the formation of dammed lakes. Analyzing the movement characteristics of the typical Xiaomojiu landslide in this area contributes to a better understanding of the dynamics of landslides in the region, which is of great significance for landslide risk prediction and analysis. True displacement data on the surface of landslides are crucial for understanding the morphological changes in landslides, providing fundamental parameters for dynamic analysis and risk assessment. This study proposes a method for calculating the actual deformation of landslide bodies based on multi-track Interferometric Synthetic Aperture Radar (InSAR) deformation data. It iteratively solves for the optimal true deformation vector of the landslide on a per-pixel basis under a least-squares constraint based on the assumption of consistent displacement direction among adjacent points on the landslide surface. Using multi-track Sentinel data from 2017 to 2023, the line of sight (LOS) accumulative de-formation of the Xiaomojiu landslide was obtained, with a maximum LOS deformation of −126 mm/year. The true surface displacement of the Xiaomojiu landslide after activation was calculated using LOS deformation. The development of two rotational sub-slipping zones on the landslide body is inferred based on the distribution of actual displacements along the central profile line. Analysis of temporal changes in water body area data revealed that the Xiaomojiu landslide was activated after a barrier lake event and continuously moved due to the influence of higher water levels’ in the river channel. In conclusion, the proposed method can be applied to calculate the true surface displacement of landslides with complex mechanisms for analyzing the movement status of landslide bodies. Furthermore, the spatiotemporal analysis of the Xiaomojiu landslide characteristics can support analyzing the mechanisms of similar landslides in the Jinsha River Basin.

Lutan-1 is the first L-band SAR satellite launched by China with the core mission of geohazard monitoring, but few studies have been conducted to apply it in the field of earthquakes. In this paper, the capability of Lutan-1 data in coseismic deformation analysis and seismogenic fault parameter inversion was discussed by taking the 2023 Mw6.0 Jishishan earthquake as an example. Firstly, we utilized Lutan-1 data to acquire the coseismic deformation field of the Jishishan earthquake. Subsequently, the seismogenic fault parameter and slip distribution were inverted using both uniform slip and distributed slip models. Finally, a comprehensive comparison was conducted with Sentinel-1 data in terms of the coseismic deformation field, seismic source parameters, and coherence. The comparative results demonstrate that the coseismic deformation and seismogenic fault parameter inversion derived from Lutan-1 data are consistent with those obtained from Sentinel-1 data. Moreover, Lutan-1 data exhibit superior image quality and better coherence, confirming the effectiveness and superiority of Lutan-1 data for coseismic deformation and seismogenic fault analysis. This study provides a theoretical foundation for the application of Lutan-1 in the field of earthquake disaster monitoring.