Quantifying the Relationship Between Blue-Green Landscape Spatial Patterns and Carbon Storage: A Case Study of Zhengzhou Metropolitan Area

In the context of global warming, blue-green spaces (BGSs) are important means for carbon reduction and storage. However, research on the influence of blue-green space patterns (BGSPs) on carbon storage (CS) and their spatial mechanisms is still limited. Therefore, this study focused on the Zhengzhou metropolitan area to analyze the correlation between the overall and internal landscape patterns of BGS and CS, along with key indicators. We quantified the spatial relationship between BGSP and CS, revealing spatial mechanisms that influence them. The results indicate that, at the class level, area-edge and shape complexity negatively affect CS, while connectivity has no significant effect. At the landscape level, Shannon’s Diversity Index, Area-edge, and Connectivity suppress CS, while Shannon’s Evenness Index, Largest Patch Index and Shape complexity promote it. Moreover, the impact of BGSP on CS is spatially heterogeneous. Therefore, we utilized multiscale geographically weighted regression (MGWR) to measure the intervention intensity on BGSs. Based on these findings, we proposed refined optimization suggestions for BGS systems to promote the integrated development of urban blue-green systems and provide references for metropolitan planning practices and resource management.