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• A new Three-dimensional Green Volume (3DGV) mapping method was proposed. • The capability of 3DGV for greening benefit evaluation was validated by using of GVI. • The 3DGV dynamics of central Yunnan were evaluated. • The citizens’ actual greening benefits was revealed by using per capita 3DGV. Urban greening benefits plays a crucial role in promoting public health and aligns with regional development strategies. Three-Dimensional Green Volume (3DGV) has emerged as a precise metric for evaluating greening benefits, yet its large-scale application remains limited. This study developed a satellite-derived 3DGV retrieval model using multi-source remote sensing data to assess urban greenery in central Yunnan, China. Field measurements were collected to establish UAV-derived 3DGV retrieval models, integrating Canopy Height Model (CHM), Leaf Area Index (LAI), and Fractional Vegetation Cover (FVC) from RGB images. We established a power regression model in large scale retrieval linking these UAV-derived parameters to Sentinel-1 and Sentinel-2 images, achieving strong performance (R 2 = 0.72; RMSE = 139.71 m 3 /pixel; AE = 120.69 m 3 /pixel; MAE = 10.54 %). Spatial analysis was used to revealed the distribution of retrieved 3DGV, and it showed a pronounced west-to-east gradient (Moran’s I = 0.772) and an obviously increase trend from 2018 to 2022. This study demonstrated that Sentinel-1 and Sentinel-2 images enable accurate large-scale 3DGV mapping and reveal 3DGV dynamics to evaluate the greening benefits, providing a feasible and effectiveness approach for sustainable urban greenery evaluation and ecological management.
Hong et al. (Wed,) studied this question.