With the rapid rate of urbanization, green infrastructure land is increasingly being converted to urban construction land, and the fragmentation of regional green infrastructure (GI) networks is intensifying. The connectivity of a GI network is of paramount importance for maintaining both regional biodiversity and regional ecosystem service capacity, among others. In this paper, an innovative approach to planning a GI network is presented. The proposed approach is based on the Morphological Spatial Pattern Analysis (MSPA) method, minimum path method, and circuit theory. Using the Zhengzhou–Kaifeng metropolitan area in China as a case study, we argue that the combination of the MSPA method and circuit theory can more fully and comprehensively identify the components of a GI network and its key areas. The methodology consists of three steps: (i) Identifying the cores and bridges of the GI by the MSPA method based on land use data, followed by determining the hubs of the GI network by assessing the connectivity of the core area; (ii) establishing potential connecting corridors between hubs by the minimum path method; (iii) identifying the “pinch point” area of the potential connecting corridors based on current density by applying circuit theory. This approach not only makes identification of the “hubs” and “links” in the green infrastructure network more scientific and comprehensive, but it also further identifies “pinch point” areas of the connecting corridors that require priority protection or recovery. The research results can be used as a practical reference for urban planners when planning urban land use.

Optimizing the layout of green infrastructure (GI) is an effective way to alleviate the fragmentation of urban landscapes, coordinate the relationship between urban development and urban ecosystem services, and ensure the sustainable development of cities. This study provides a new technical framework for optimizing GI networks based on a case study of Kaifeng, an exemplar of many ancient cities along the Yellow River in China. To do this, we used a morphological spatial pattern analysis (MSPA) methodology and combined it with Procedure for mAthematical aNalysis of lanDscape evOlution and equilibRium scenarios Assessment (PANDORA) model to determine the hubs of the GI network. Then we employed a least-cost path approach to simulate potential corridors linking the hubs. We further identify the key ‘pinch points’ of the GI network that need priority protection based on circuit theory. Altogether, this framework takes patches that have a high level of ecosystem services and are more important in maintaining overall connectivity as hubs, thereby improving the accuracy of hub identification. Moreover, it establishes a direct connection between GI construction and ecosystem services, and improves biodiversity conservation by optimizing the network structure of GI. The results of the case study show that this framework is suitable for GI planning and construction, and can provide effective technical support for the formulation of urban sustainable development strategies.