Urban greening amidst global change: A comparative study of vegetation dynamics in two urban agglomerations in China under climatic and anthropogenic pressures

Vegetation is crucial in enhancing the urban environment and benefiting human settlements. Consequently, monitoring and attributing vegetation dynamics in urban agglomerations are paramount. Nevertheless, quantitatively assessing the driving mechanisms of urban vegetation proves challenging due to its direct regulation by human land use activities and its susceptibility to influences from urban environmental changes intertwined with global environmental shifts. A critical obstacle arises from the scarcity of reliable long-term observation data, further amplifying the difficulty of such research. Using a newly developed technique that effectively resolves cross -sensor bias and low revisiting frequency issues, we generated Landsat-based long-term vegetation indices data (NDVI, EVI, and NIRv) during 1986-2020. Our study quantified spatiotemporal vegetation changes and examined the contributions of various drivers, including atmospheric CO2 concentration, climate variations, and land cover changes over the past four decades in two representative urban agglomerations in China: the Wuhan Metropolitan Area (WMA) and the Guangdong -Hong Kong -Macao Greater Bay Area (GBA). We found notable and prevalent rising trends of vegetation growth in WMA and GBA during 1986-2020, with considerable spatial and time -period variability. Greening was continuously observed in WMA with a significant increasing trend (0.0019 yr(-1) 0.01) before 2000 to increasing (0.0038 yr(-1), p < 0.01) after 2000. The disparities between WMA and GBA were due to urban development status variations across cities and periods. Elevated CO2 concentration and increased solar radiation were the primary factors behind the overall greening. However, land cover changes partially offset these positive contributions in WMA. Our results assist in understanding vegetation dynamics and the effects of climatic and anthropogenic factors at the urban scale, providing valuable insights for ecological management in metropolitan areas. , p < 0.01) in annual EVImax, while in GBA, the trends shifted from slightly decreasing (-0.0003 yr(-1), p <