Optimizing the landscape pattern of blue-green space is more effective than simply increasing the area for cooling effect

Background Blue-Green Space (BGS) is critical for mitigating the Urban Heat Island (UHI) effect amid rapid global urbanization. However, the comparative cooling efficiency of BGS landscape configuration versus simple area expansion remains understudied, particularly regarding long-term spatiotemporal non-stationarity in large-scale economic zones. Methods This study investigates the spatiotemporal evolution of BGS and its regulatory effects on Land Surface Temperature (LST) in the Yangtze River Economic Belt (YEB) from 2000 to 2024. Using Landsat-derived metrics, we employed Global/Local Moran’s I to identify thermal clustering and the Spatiotemporal Geographically Weighted Regression (GTWR) model to quantify non-stationary relationships, explicitly comparing the marginal cooling contributions of landscape pattern indices against area proportion (PLAND). Results The YEB exhibited a “downstream cooling, mid-upstream warming” trend with significant spatial clustering. The GTWR model ( R 2 = 0.840) revealed that optimizing landscape configuration yields superior cooling benefits to mere area expansion in specific spatiotemporal contexts. High patch connectivity (CONTAG) significantly mitigated heat in early urbanization stages, while complex patch shapes (FRAC_MN) and edge density (ED) were more effective in high-density urban cores. Conclusion These findings challenge the “area-first” planning paradigm, supporting an “efficiency-first” strategy. To maximize urban climate resilience, we propose differentiated optimization pathways that prioritize contiguous preservation in mountainous regions and hydrological connectivity in water-rich networks.