Urban trees are important for adapting to climate change; however, the absence of fine-grained data describing the distribution of urban tree crown cover and carbon stocks hinders recognition of the contribution of urban systems to climate change mitigation. Here, we present an approach for extracting fine-grained tree crown cover by coupling the Segment Anything Model and vegetation indices using Google Earth imagery with a spatial resolution of 0.298m. We estimated the aboveground biomass of tree-covered regions in Wuhan, representative of China's urbanization, using multi-source remote sensing data and machine-learning techniques. We show that tree crown cover accounts for 18.86% of the study area, implying that the nationwide proportion of urban trees probably represents 1.88–2.69% of the total forested area. Tree growth in urban regions remains reasonably stable owing to the high level of human management, with a 60–86 Mg C ha-1 carbon density of aboveground biomass in the tree-covered region in Wuhan. Street trees at specific distances from infrastructure represented an average level of aboveground biomass, whereas urban trees at relatively distant locations were the dominant contributors to aboveground biomass. Our study highlights the carbon stocks of urban trees and the various mechanisms that indirectly influence carbon emissions, representing a potentially promising nature-based solution. We recommend enhancing the socio-ecological characteristics of urban systems to address future climate change.
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