Beijing, China’s capital city, has experienced decades of severe land subsidence due to the long-term overexploitation of groundwater. The implementation of the South-to-North Water Diversion Project (SNWDP) and artificial ecological restoration have significantly changed Beijing’s hydro-ecological and geological environment in recent years, leading to a widespread rise in groundwater levels. However, whether the related land subsidence has slowed down or reversed under these measures has not yet been effectively monitored and quantitatively analyzed in terms of time and space. Accordingly, in this study, we proposed using an improved time-series deformation method, which combines persistent scatterers and distributed scatterers, to process Sentinel-1 images from 2015 to 2022 in the Beijing Plain region. We performed a geospatial analysis to gain a better understanding of how the new hydrological conditions changed the pattern of deformation on the Beijing Plain. The results indicated that our combined PS and DS method provided more measurements both in total quantity and spatial density than conventional PSI methods. The land subsidence in the Beijing Plain area has been effectively alleviated from a subsidence region of approximately 1377 km² in 2015 to only approximately 78 km² in 2022. Ecological restoration areas in the northeastern part of the Plain have even rebounded over this period, at a maximum of approximately 40 mm in 2022. The overall pattern of ground deformation (subsidence and uplift) is negatively correlated with changes in the groundwater table (decline and rise). Local deformation is controlled by the thickness of the compressible layer and an active fault. The year 2015, when anthropogenic water transfers were eliminated and ecological measures to recharge groundwater were implemented, was the crucial turning point of the change in the deformation trend in the subsidence history of Beijing. Our findings carry significance, not only for China, but also for other areas where large-scale groundwater extractions are causing severe ground subsidence or rebound.

Urban agglomerations (UA) are attracting increasing research attention as a global emergent phenomenon, whereby regional collaborative linkages between cities attracts and agglomerates development. However, these studies also acknowledge that ecological values may be negatively impacted by re-development, ecological fragmentation, and proximity or downstream impacts. Sustainable development, therefore, requires balancing forces from economic attraction and ecological repulsion. Forces similar to economic ones may also operate in attracting ecological enhancement towards higher-valued ecological regions; however, research regarding the role of the self-collaborative gravity-like forces shaping UA is limited in land use optimization. To assist planners, this study developed a new multi-objective land use optimization of UA that explored the intensity of economic ties and ecological gradients using the multi-objective NSGA-II algorithm. In this model, economic linkage intensity (ELI) and accessibility were used to calculate a modified GDP (gross domestic product), while the NDVI (normalized difference vegetation index) was used for the modified ESV (ecosystem services value). Spatial allocation with implicit economic accessibility relationships was enhanced through a two-step mutation operator, including a “gravity flip” spatial orientation factor. Compared to the standard NSGA-II algorithm, models of future land use of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in 2030 have shown that the modified GDP value in our model increased by 7.41%, while the conversion rate of high-density vegetation reduced by 7.92%. The results highlighted the importance of linkage and accessibility factors in enhancing the clustering of cities. In tandem, the modified ESV also enhances ecosystem services contributions of higher value vegetated land through decentralized built-up developments. The proposed model provides managers with a comprehensive and efficient land use solution model that accounts for intrinsic linkage factors shaping the development of compact urban agglomerations.

Land reclamation in the Yan’an New District (YND) on the Chinese Loess Plateau is one of the largest earthworks projects in the world, involving the excavation of loess from ridges and the deposition of the material in adjacent valleys, flattening an area of more than 78 km2. It can take multiple years for the landscape to adjust to the new topography after the earthworks are completed, with subsidence in the fill areas and uplift in the excavation areas. Understanding the pattern and extent of this differential vertical movement has great importance for ensuring the structural integrity of any infrastructure built on the site. We, therefore, studied the spatial deformation field of the YND from January 2015 to December 2018 using satellite synthetic aperture radar interferometry (InSAR) technology. Persistent scatterers (PS) and distributed scatterers (DS) were combined in a novel two-tier network to overcome problems with temporal decorrelation of the InSAR phase signals. The derived deformation field was validated with in-situ ground leveling and GNSS measurements and interpreted using a forward geophysical model. The results indicate that our approach provides a more detailed understanding of the deformation than conventional PSI and SBAS methods. Subsidence of up to 87 mm/yr occurred over about 4.4 km2 of the fill region and uplift of up to 26 mm/yr in the excavated areas. There is a strong linear relationship between these displacements and prior topographic elevation change. The primary cause of subsidence in fill areas is compaction of remoulded loess. Instantaneous elastic and gradual poroelastic deformation are the main causes of uplift in excavated areas.