Central Asia (CA) is experiencing rapid warming, leading to more Extreme precipitation events (EPEs). However, the anticipated changes in cropland and population exposure to EPEs are still unexplored. In this study, projected changes in EPEs characteristics, as well as cropland and population exposure from EPEs are quantified using global climate model simulations. Our findings reveal a significant increase in the exposure of cropland and population to extreme precipitation over time. Specifically, under the high-emission SSP5-8.5 future pathway, the amount, frequency, intensity, and spatial extent of extreme precipitation in CA are projected to considerably amplify, particularly in the high mountain regions. Under the SSP5-8.5 scenario, cropland exposure in CA increases by 46.4%, with a total cropland exposure of approximately 190.7 million km² expected between 2021 and 2100. Additionally, under the SSP3-7.0 scenario, population exposure in CA increases by 92.6%, resulting in a total population exposure of about 48.1 billion person-days during the same period. The future maximum centers of exposure are concentrated over northern Kazakhstan and the tri-border region of Tajikistan, Kyrgyzstan, and Uzbekistan. Notably, the climate effect is more dominant than the other effects, whereas changes in population effect contribute to the total change in population exposure. Given the heterogeneous distribution of population and cropland in CA, it is imperative for the countries in the region to implement effective measures that harness extreme precipitation and cope with the impacts of these extreme climate events.

Understanding vegetation evaluation is critical for exploring changes in terrestrial ecosystems and identifying upcoming challenges. However, analyses that simultaneously examine abrupt changes in vegetation greenness at the national, regional, biome and pixel scales in China are still rare. Using long-term (1982–2015) satellite time series data in conjunction with the Breaks for Additive Season and Trend (BFAST) technique, we identified breakpoints in the Normalized Difference Vegetation Index (NDVI) in China. Results showed that the annual mean NDVI gradually increased during the 34-year period. 68.8% of the vegetated area exhibited upward trends in NDVI, most of which was distributed in Southeast China and the Loess Plateau. Changes in NDVI trends occurred in 78.7% of the total vegetated areas, while hotspots were concentrated in Northwest and North China. A rapid increase in breakpoints was detected after 1999, mainly concentrated in North and Northwest China, and corresponding to the times and areas with the highest ecological engineering efforts. Positive shifts in NDVI trends were more common and generally distributed on the eastern side of the Hu Huanyong line, while browning (negative) shifts were mainly distributed on the western side and were gradually expanding, indicating a possible tendency towards environmental degradation. Although unstable vegetation areas had higher frequencies of breakpoints, the proportion of stable vegetation experiencing NDVI trend shifts was higher after 2000, probably because human intervention buffered external disturbances in unstable areas. Identifying hotspot areas of shifts in vegetation greenness can provide scientific reference for sustainable land development and carbon neutrality target achievements.