China’s massive wave of urbanization may be threatened by land subsidence. Using a spaceborne synthetic aperture radar interferometry technique, we provided a systematic assessment of land subsidence in all of China’s major cities from 2015 to 2022. Of the examined urban lands, 45% are subsiding faster than 3 millimeters per year, and 16% are subsiding faster than 10 millimeters per year, affecting 29 and 7% of the urban population, respectively. The subsidence appears to be associated with a range of factors such as groundwater withdrawal and the weight of buildings. By 2120, 22 to 26% of China’s coastal lands will have a relative elevation lower than sea level, hosting 9 to 11% of the coastal population, because of the combined effect of city subsidence and sea-level rise. Our results underscore the necessity of enhancing protective measures to mitigate potential damages from subsidence.

Landslides modify the natural landscape and cause fatalities and property damage worldwide. Quantifying landslide dynamics is challenging due to the stochastic nature of the environment. With its large area of ~1 km²and perennial motions at ~10–20 mm per day, the Slumgullion landslide in Colorado, USA, represents an ideal natural laboratory to better understand landslide behavior. Here, we use hybrid remote sensing data and methods to recover the four-dimensional surface motions during 2011–2018. We refine the boundaries of an area of ~0.35 km²below the crest of the prehistoric landslide. We construct a mechanical framework to quantify the rheology, subsurface channel geometry, mass flow rate, and spatiotemporally dependent pore-water pressure feedback through a joint analysis of displacement and hydrometeorological measurements from ground, air and space. Our study demonstrates the importance of remotely characterizing often inaccessible, dangerous slopes to better understand landslides and other quasi-static mass fluxes in natural and industrial environments, which will ultimately help reduce associated hazards.

Active landslides cause fatalities and property losses worldwide. Landslide behaviors can be enigmatic in natural landscapes and therefore require high‐quality observations of their kinematics to improve our ability to predict landslide behavior. Here we use geodetic interferometric synthetic aperture radar (InSAR) observations to characterize the geometry and the spatio‐temporal deformation of the slow‐moving, deep‐seated Monroe landslide in northern California between 2007 and 2017. InSAR phase discontinuities show that the landslide is bounded by discrete strike‐slip faults at the lateral margins and segregated into distinct kinematic elements by normal and thrust faults. We find that the Monroe landslide has been moving consistently, with a maximum rate of about 0.7 m/year in the narrowest longitudinal center of the transport zone. The thickest landslide mass is estimated to be in a zone located between subsiding and the uplifting kinematic elements at the lower transport zone. The timing and magnitude of the landslide displacement are modulated by the intensity and duration of precipitation, as well as the antecedent water content of the landslide mass. In addition, we use a one‐dimensional pore‐water pressure diffusion model to estimate the rainfall‐modulated pore‐water pressure changes and hydraulic diffusivity. We find hydraulic diffusivity values between m²/s, which agrees with ground‐based measurements in this region. Displacement measurements on the hillslopes obtained from geodetic InSAR observations allow us to characterize the mobility, depth, and hydraulic diffusivity of slow‐moving landslides.