Measuring the spatial configuration of urban tree canopy: A new metric for assessing concentrated-dispersed patterns and their association with urban air quality

Which spatial distribution pattern of urban tree cover—concentrated or dispersed—is more effective for improving air quality? This study proposes two novel indicators, namely the Urban Tree Cover Distribution (UTD) index and Urban Tree Cover Area (UTA) index, which are developed based on tree cover rate raster calculations. These indicators quantify the spatial structure and aggregation characteristics of tree cover across over 280 cities in China and reveal the spatiotemporal differentiation of tree cover configurations in these cities from 2000 to 2023. The analysis indicates that since 2016, the tree cover rate and spatial aggregation degree in Chinese cities have increased significantly, while urban PM₂.₅ concentrations have decreased. The spatial distributions of the UTD and UTA indices exhibit spatial autocorrelation, with distinct differences between northern and southern China. Empirical modeling shows that the concentration degree of the forest spatial pattern exerts a significant positive effect on urban air quality improvement, and this effect varies significantly across different regions of China. Index decomposition reveals that the spatial distribution effect of urban trees on air quality improvement is stronger than its scale effect. Additionally, the spatial spillover effect caused by variations in tree cover is highly significant, and the spatial agglomeration of urban tree planting shows a significant marginal increasing trend in suppressing PM₂.₅. This study concludes that cities should adopt a more concentrated tree-planting pattern, as this approach not only significantly improves air quality but also reduces economic costs.