Can Spatial Patterns Moderate Nonlinearity Between Greenspace and Subjective Wellbeing? Evidence from China’s Urban Areas

Although extensive evidence notes a nonlinear relationship between urban greenspace and wellbeing, the conditional role of spatial patterns in this relationship has rarely been examined. To address this gap, this study investigates whether and how landscape metrics moderate the nonlinear association between greenspace coverage and life satisfaction (LS) in urban China. Using nationally representative data from the 2015 wave of the Chinese Social Survey (N = 4319 across 321 subdistricts), this study combines individual-level LS scores with high-resolution GlobeLand30 land use data. Moderated quadratic regression models and formal endpoint slope and turning point tests are applied to identify both the shape and dynamics of the greenspace–wellbeing relationship. The analysis reveals a robust U-shaped curve: LS is lowest at moderate greenspace levels and higher at both low and high extremes. Critically, spatial pattern features, including aggregation index, Euclidean nearest neighbor distance, patch density, and patch richness, significantly moderate this relationship. The turning point of the U-shape moves rightward with greater aggregation and leftward with higher fragmentation or richness. While visual presentation indicates that the curve flips at low patch isolation, further statistical analyses indicate insufficient curve steepness. These findings support that the “more is better” argument should be extended to consider both greenspace quantity and spatial configuration in urban planning for optimal wellbeing outcomes.